WO2021237520A1 - 外参标定方法、装置、设备及存储介质 - Google Patents
外参标定方法、装置、设备及存储介质 Download PDFInfo
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- WO2021237520A1 WO2021237520A1 PCT/CN2020/092652 CN2020092652W WO2021237520A1 WO 2021237520 A1 WO2021237520 A1 WO 2021237520A1 CN 2020092652 W CN2020092652 W CN 2020092652W WO 2021237520 A1 WO2021237520 A1 WO 2021237520A1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
- G01S7/497—Means for monitoring or calibrating
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
Definitions
- This application relates to the field of automatic driving, and in particular to an external parameter calibration method, device, equipment and storage medium.
- the related technology will first scan the entire room in a three-dimensional space (such as a room) with a measuring device in the process of Lidar calibration, and obtain the calibration object in the three-dimensional space according to the scanning result.
- the point coordinates of the mapped point under the coordinate system of the then, scan the entire room through the lidar in the three-dimensional space to obtain the point cloud data, and extract the point coordinates of the point mapped by the calibration object from the point cloud data; after obtaining two
- the correspondence relationship between the coordinate system of the lidar and the coordinate system of the three-dimensional space is determined according to the matching relationship between the points with the same name (that is, the points mapped by the calibration object in the two coordinate systems).
- the above method needs to extract the point coordinates of the point mapped by the calibration object from the point cloud data when determining the external parameters.
- the ranging error of the lidar itself and the insufficient resolution it is difficult to accurately extract the point mapped by the calibration object Therefore, the calibration accuracy of this method is poor.
- the embodiments of the present application provide an external parameter calibration method, device, equipment, and storage medium, which can improve the accuracy of external parameter calibration.
- the technical solution is as follows:
- an external parameter calibration method is provided.
- a first calibration parameter is obtained according to the measurement data of a first device by a measuring device, and the first calibration parameter is used to indicate the relationship between the measuring device and the The coordinate system conversion relationship between the first devices; determine at least one first plane mapped by the at least one calibration plane in the coordinate system of the measurement device according to the measurement data of the measurement device on the at least one calibration plane;
- the measurement data of the at least one calibration plane by the second device determine at least one second plane mapped by the at least one calibration plane in the coordinate system of the second device; according to the at least one first plane and the The at least one second plane determines at least one plane group, the plane group includes a first plane and a second plane, and the first plane in the plane group corresponds to the second plane; according to the at least one plane group, it is determined
- a second calibration parameter where the second calibration parameter is used to indicate the coordinate system conversion relationship between the measuring device and the second device; according to the first calibration parameter and the second calibration parameter, the
- the external parameter calibration timing is obtained by the above method. Because the external parameters are obtained through the determined plane group, there is no need to extract the points with the same name from the point cloud data, thus avoiding the influence of the extraction process of the points with the same name on the calibration accuracy, thus improving The calibration accuracy is improved. In addition, the method can be solidified into a computer automated execution process, avoiding the time-consuming and laborious problems caused by manual calculation of calibration parameters, thereby improving the calibration efficiency.
- the determining the second calibration parameter according to the at least one plane group includes: according to the at least one plane group, the first plane and the second plane in the plane group satisfy a matching condition, and determining the second Calibration parameters.
- the first plane and the second plane in the plane group satisfy a matching condition, including: the normal vector angle between the first plane and the second plane in the plane group is the smallest.
- the second calibration parameter includes a rotation matrix, and according to the at least one plane group, the normal vector angle between the first plane and the second plane in the plane group is the smallest, and the second calibration is determined
- the parameters include: determining the rotation matrix according to the at least one plane group and a first optimization function, where the rotation matrix makes the value of the first optimization function a minimum value.
- the first optimization function is constructed, multiple calibration data and the first optimization function are used, and the optimization method is used to automatically obtain the rotation matrix.
- the solution process of the rotation matrix can be calibrated by external parameters. The equipment is automated without manual intervention, thereby improving calibration efficiency and avoiding errors caused by manual intervention.
- the rotation matrix can be automatically obtained through multiple calibration data, reducing the error caused by a single calibration.
- the first plane and the second plane in the plane group satisfy a matching condition, including: the distance between the first plane and the second plane in the plane group is the smallest.
- the second calibration parameter includes a translation matrix, and according to the at least one plane group, the distance between the first plane and the second plane in the plane group is the smallest, and the second calibration parameter is determined, including : Determine the translation matrix according to the at least one plane group and the second optimization function, and the translation matrix makes the value of the second optimization function a minimum value.
- the optimization method is used to automatically obtain the translation matrix.
- the calculation process of the translation matrix can be calibrated by external parameters. It is completed automatically without manual intervention, thereby improving calibration efficiency and avoiding errors caused by manual intervention.
- the translation matrix can be automatically obtained through multiple calibration data, reducing the error caused by a single calibration.
- the second calibration parameter includes a translation matrix
- the determining the second calibration parameter according to the at least one plane group includes: using the rotation matrix and the initial translation matrix to perform a calculation on a point on the first plane Rotation transformation and translation transformation are used to obtain the projection point of the point; according to the at least one plane group, an initial translation matrix that minimizes the distance between the projection point and the second plane is determined as the translation matrix.
- the distance calculation between the two surfaces is converted into the distance calculation between the point and the plane. Since the first plane and the second plane are parallel or non-parallel, the difference between the projection point and the second plane is The distances are easy to solve, which ensures that the method of determining the translation matrix has a wider application range and improves the practicability.
- the acquiring the first calibration parameter according to the measurement data of the measuring device on the first device includes: according to the coordinate value of the mark point on the first device in the coordinate system of the first device and the coordinate value of the first device.
- the coordinate value of the marker point measured by the measuring device in the coordinate system of the measuring device is used to obtain the first calibration parameter.
- the coordinate system of the first device can be calculated by observing the mark points on the first device with the measuring device, which provides a way to obtain the coordinate system of the first device through passive observation, which helps Improve the accuracy of the obtained coordinate system of the first device (that is, the first calibration parameter).
- the measurement device is a total station, a laser scanner or a photogrammetry system
- the calibration plane is a calibration board or a wall
- the first device is an inertial navigation device, a vehicle or a first lidar
- the The second device is a second lidar, millimeter wave or camera.
- an external parameter calibration device in a second aspect, includes:
- An acquiring module configured to acquire a first calibration parameter according to the measurement data of the first device by the measuring device, where the first calibration parameter is used to indicate the coordinate system conversion relationship between the measuring device and the first device;
- a determining module configured to determine at least one first plane mapped by the at least one calibration plane in the coordinate system of the measuring device according to the measurement data of the at least one calibration plane by the measuring device;
- a determining module configured to determine at least one second plane mapped by the at least one calibration plane in the coordinate system of the second device according to the measurement data of the at least one calibration plane by the second device;
- a determining module configured to determine at least one plane group according to the at least one first plane and the at least one second plane, the plane group including a first plane and a second plane, the first plane in the plane group Corresponding to the second plane;
- a determining module configured to determine a second calibration parameter according to the at least one plane group, where the second calibration parameter is used to indicate a coordinate system conversion relationship between the measuring device and the second device;
- the acquiring module is further configured to acquire external parameters between the second device and the first device according to the first calibration parameter and the second calibration parameter.
- the external parameter calibration device is a device with computing capability, for example, the external parameter calibration device is a computing device, a processor, a chip, a personal computer, etc.
- the determining module is configured to determine the second calibration parameter according to the at least one plane group, and the first plane and the second plane in the plane group satisfy a matching condition.
- the first plane and the second plane in the plane group satisfy a matching condition, including: the normal vector angle between the first plane and the second plane in the plane group is the smallest.
- the second calibration parameter includes a rotation matrix
- the determination module is configured to determine the rotation matrix according to the at least one plane group and a first optimization function, and the rotation matrix enables the first optimization
- the value of the function is the minimum value.
- the first plane and the second plane in the plane group satisfy a matching condition, including: the distance between the first plane and the second plane in the plane group is the smallest.
- the second calibration parameter includes a translation matrix
- the determining module is configured to determine the translation matrix according to the at least one plane group and a second optimization function, and the translation matrix enables the second optimization
- the value of the function is the minimum value.
- the second calibration parameter includes a translation matrix
- the determining module is configured to use the rotation matrix and the initial translation matrix to perform rotation transformation and translation transformation on a point on the first plane to obtain Projection point; according to the at least one plane group, determine an initial translation matrix that minimizes the distance between the projection point and the second plane as the translation matrix.
- the acquisition module is configured to use the coordinate value of the marker point on the first device in the coordinate system of the first device and the marker point measured by the measuring device in the measurement
- the coordinate value in the coordinate system of the device is used to obtain the first calibration parameter.
- the measurement device is a total station, a laser scanner or a photogrammetry system
- the calibration plane is a calibration board or a wall
- the first device is an inertial navigation device, a vehicle or a first lidar
- the The second device is a second lidar, millimeter wave or camera.
- an external parameter calibration device in a third aspect, includes a processor for executing instructions so that the external parameter calibration device executes the first aspect or any one of the optional methods of the first aspect.
- the external parameter calibration method provided.
- a computer-readable storage medium stores at least one instruction.
- the instruction is read by a processor to enable an external reference calibration device to execute the first aspect or any one of the first aspects. Select the external parameter calibration method provided by the method.
- a computer program product is provided.
- the external parameter calibration device executes the external parameter provided in the first aspect or any one of the optional methods in the first aspect. Calibration method.
- a chip is provided, when the chip runs on an external parameter calibration device, the external parameter calibration device executes the external parameter calibration method provided in the first aspect or any one of the optional methods of the first aspect.
- an external parameter calibration system in a seventh aspect, includes an external parameter calibration device, a measuring device, a first device, and a second device.
- the external parameter calibration device is used to perform the first aspect or the first aspect described above. The method described in any of the optional manners in the aspect.
- FIG. 1 is a schematic diagram of an application scenario of external parameter calibration of lidar provided by an embodiment of the present application
- FIG. 2 is a schematic diagram of the architecture of a high-precision map collection system provided by an embodiment of the present application
- FIG. 3 is a schematic diagram of a calibration device for external parameters in a high-precision map acquisition system provided by an embodiment of the present application;
- FIG. 4 is a schematic diagram of the device name, specification parameters and reference diagram of an external parameter calibration device provided by an embodiment of the present application;
- FIG. 5 is a flowchart of an external parameter calibration method 300 provided by an embodiment of the present application.
- Fig. 6 is a schematic diagram of a coordinate system of a GNSS/IMU device provided by an embodiment of the present application.
- FIG. 7 is a flowchart of an external parameter calibration method 400 provided by an embodiment of the present application.
- FIG. 8 is a schematic structural diagram of an external parameter calibration device 500 provided by an embodiment of the present application.
- FIG. 9 is a schematic structural diagram of an external parameter calibration device 600 provided by an embodiment of the present application.
- Calibration is a process of obtaining equipment parameters. The purpose of calibration is to determine the values of some equipment parameters. Calibration includes internal parameter calibration and external parameter calibration.
- External parameter calibration refers to the process of determining the coordinate system conversion relationship between equipment A and equipment B.
- the point in the coordinate system of device A can be mapped to the coordinate system of device B after rotation and translation, or vice versa, the point in the coordinate system of device B can be passed through After rotation and translation, it is mapped to the coordinate system of device A.
- calibrating the external parameters between LiDAR (Light Detection and Ranging, LiDAR) and Global Navigation Satellite System (GNSS)/Inertial Measurement Unit (IMU) equipment is to obtain the coordinates of LiDAR
- the pose transformation relationship between the coordinate system to the GNSS/IMU device The external parameters between two devices are usually expressed by a rotation matrix and a translation matrix.
- the external parameters between the two devices can be used Express.
- R LI is an example of a rotation matrix
- T LI is an example of a translation matrix.
- the rotation matrix represents the rotation transformation relationship of the coordinate system between the device A and the device B.
- the rotation matrix is a matrix with three rows and three columns.
- the rotation matrix includes 3 degrees of freedom, which correspond to the x-axis, y-axis, and z-axis, respectively.
- the rotation matrix is represented by the following matrix R LI.
- the rotation matrix is represented by a quaternion, and the quaternion is denoted as q LI for example.
- the quaternion q LI is, for example, (w, x, y, z).
- R LI and q LI are equivalent, and both represent rotation transformation.
- the translation matrix represents the translation transformation relationship of the coordinate system between the device A and the device B.
- the rotation matrix is a 3*1 size matrix, the rotation matrix includes 3 degrees of freedom, which correspond to the x-axis, y-axis, and z-axis, respectively, and the translation matrix represents the three x, y, and z The translation in the axis direction.
- the translation matrix is represented by the following matrix T LI.
- T LI [t x t y t z ] T
- the external parameter calibration method provided by the embodiment of the present application can be applied to the external parameter calibration scenario of lidar.
- the following is a brief introduction to the external parameter calibration scene of the lidar.
- Lidar is a new type of sensor.
- Lidar includes a laser transmitter and receiver.
- the laser transmitter generates and emits a light pulse, the light pulse hits the object and reflects back, and finally the light pulse is received by the receiver.
- the receiver accurately measures the propagation time of the light pulse from emission to reflection. According to the height of the laser transmitter and the laser scanning angle, the coordinates of each spot relative to the center of the lidar are accurately calculated.
- lidar Since the distance measurement accuracy of lidar can reach several centimeters, and the distance measurement accuracy is relatively accurate, lidar is widely used in surveying and mapping, intelligent driving and other fields. In the application process, it is often necessary to convert the point cloud information obtained by the lidar from the lidar coordinate system to other coordinate systems. For example, in the production of high-precision maps, it is necessary to use the laser point cloud in the laser radar scanning collection area, and the position and attitude information obtained by the positioning and attitude system (such as GNSS/IMU equipment).
- the external parameter calibration of lidar and GNSS/IMU equipment is required, that is, the conversion relationship between lidar coordinate system and GNSS/IMU equipment coordinate system is obtained, so as to use the external parameters between lidar and GNSS/IMU equipment. Participate, combine the multi-frame laser point cloud with the pose information of each frame moment to form a world point cloud.
- the installation data of multiple sensors is obtained, and the relative position relationship between the sensors is calculated according to the installation data of each sensor, so as to calculate the external parameters between the sensors.
- the form of sensor installation data is not limited to all measurable mathematical models such as design drawings, computer aided design (CAD) drawings, and three-dimensional models.
- CAD computer aided design
- the center position of the lidar coordinate system is calculated. In the same way, calculate the center position of other sensors except lidar, and then calculate the relative positional relationship between lidar and other sensors in space.
- the three-dimensional coordinates of landmarks (such as wall corners, pillars, and other landmarks) in the entire room are obtained by scanning with high-precision three-dimensional measuring equipment. Then use the lidar to scan the entire room, extract the coordinates of each marker in the lidar point cloud, and determine the relationship between the lidar coordinate system and the three-dimensional space coordinate system through the matching relationship of the markers with the same name.
- the GNSS/IMU device determines the reference point of the multi-line lidar relative to the reference plane, and display it visually For the above reference point, adjust the calibration parameters between the GNSS/IMU device and the multi-line lidar according to the deviation between the displayed reference point and the corresponding actual point cloud.
- the deviation displayed according to the adjusted calibration parameter is When it is zero, it is determined that the calibration is over.
- the disadvantage of this method is that it is time-consuming and labor-intensive and requires professional operations, and cannot be solidified into a process; secondly, it relies on manual labor and cannot be automated, and its accuracy relies on human observation results.
- a multi-line lidar is used to scan a flat panel; according to the scanning results, the edge points of the flat panel are extracted and the flat panel edge lines are fitted; the corner points of the flat panel are obtained through the intersection of the two edge lines as the laser A known point in the radar coordinate system.
- the fitting edge line is a number of points (the number does not exceed the number of line bundles) obtained by scanning the edge of the flat panel with lidar, and its accuracy is difficult to guarantee.
- lidar In the scenario of external parameter calibration between lidar and GNSS/IMU equipment, since the GNSS/IMU equipment itself cannot actively observe, its coordinate system cannot be obtained indirectly, and other reference objects must be used to obtain the coordinate system of the GNSS/IMU equipment. Secondly, the lidar itself has a ranging error, and its resolution is not high enough, it may not be able to accurately obtain the position of a point in space. In summary, it is difficult to calibrate external parameters of lidar and GNSS/IMU equipment and the accuracy is not high enough to meet the needs of high-precision map mapping.
- a high-precision and highly automated method for calibrating external parameters of lidar is proposed for the scene of external parameter calibration between the lidar and GNSS/IMU equipment in the high-precision map acquisition system.
- Observe the coordinate system of the GNSS/IMU device by using high-precision three-dimensional measurement equipment (such as a total station) combined with the mechanical size parameters of the GNSS/IMU device, and use the total station and lidar to simultaneously observe the calibration plane (such as the calibration flat panel) , Use the fitting relationship of the plane with the same name to construct the matching condition, and solve the rotation matrix and translation matrix step by step. Since points with the same name are avoided from the laser point cloud, the calibration accuracy is improved.
- the system architecture 100 is an example of a high-precision map collection system.
- the "high precision" in the high-precision map includes two meanings. On the one hand, it means that the accuracy of the coordinates in the map is higher, for example, the accuracy of the coordinates is at the centimeter level. On the other hand, it means that the road traffic information elements contained in the map are richer and more detailed. For example, the map includes not only roads, but also road shapes, traffic lights and other information.
- the system architecture 100 includes a lidar 101, a GNSS/IMU device 102, a long focus camera 103, a short focus camera 104, an antenna 107, and a vehicle 105.
- the GNSS/IMU device 102 is rigidly connected and fixed with the lidar 101, the telephoto camera 103, and the short-focus camera 104.
- the lidar 101, the GNSS/IMU device 102, the antenna 107, the telephoto camera 103, and the short telephoto camera 104 are arranged on a base 106, and the base 106 is arranged on the roof of the vehicle 105.
- the lidar 101 is used to scan the laser point cloud in the collection area.
- the GNSS/IMU device 102 is used to obtain pose information.
- an embodiment of the present application provides a system architecture 200.
- the system architecture 200 is an example of a high-precision map collection system.
- the system architecture 200 is suitable for application in the external parameter calibration scenario between the lidar 101 and the GNSS/IMU device 102 in the system architecture 100.
- the system architecture 200 includes a lidar 101, a GNSS/IMU device 102, a total station 201, multiple calibration boards, and a personal computer (PC).
- the PC is another device with processing capabilities, such as a processor , Chips, etc.
- the PC is not shown in Figure 3.
- FIG. 4 is an example of the device name, specification parameters, and reference diagram of each device involved in the system architecture 200.
- the total station 201 is a laser total station.
- the ranging accuracy of the total station 201 is, for example, 0.1 millimeter (mm).
- the total station 201 is set in a position that is in line with the GNSS/IMU device 102 and the calibration board.
- the multiple calibration boards include a calibration board 2021, a calibration board 2022, and a calibration board 2023.
- the calibration board 2021, the calibration board 2022 and the calibration board 2023 are arranged in different positions.
- the calibration board 2021, the calibration board 2022, and the calibration board 2023 have different postures.
- the calibration plate is an enamel calibration plate.
- the calibration plate has a calibration aluminum oxide coating.
- the specification of the calibration board is 1.0m*1.0m, that is, the width and height are each 1m.
- the material of the aluminum oxide coating is a highly reflective material, and the diffuse reflection of the aluminum oxide coating is relatively small.
- the surface of the enamel glass is very flat and not easily deformed.
- the GNSS/IMU device 102 is an inertial navigation device to be calibrated.
- the appearance of the GNSS/IMU device 102 is a box.
- the lidar 101 is a multi-beam lidar 101.
- the lidar 101 is set at a position where the calibration board can be observed.
- the lidar 101 and the GNSS/IMU device 102 are rigidly connected and fixed.
- a solution program is installed and running in the PC, and the solution program is used to solve the rotation matrix and the translation matrix, so as to determine the external parameters between the lidar 101 and the GNSS/IMU device 102.
- the PC is connected to at least one of the lidar 101, the GNSS/IMU device 102, and the total station 201 through a wireless network or a wired network.
- the system architecture is introduced above, and the method 300 to the method 400 are used to exemplarily introduce the method flow of external parameter calibration based on the system architecture provided above.
- FIG. 5 is a flowchart of an external parameter calibration method 300 provided by an embodiment of the present application.
- the hardware devices involved in the method 300 include a measurement device, a first device, a second device, a calibration plane, and an external parameter calibration device.
- the measuring device is a high-precision three-dimensional measuring device.
- the measurement equipment is a total station, a laser scanner, or a photogrammetric system.
- the calibration plane is any hardware device with a flat surface.
- the calibration plane is a plane that the laser cannot penetrate.
- the calibration plane is a calibration board or wall. Among them, by using the calibration board, it is helpful to obtain higher calibration accuracy.
- the method 300 is used for external parameter calibration between the first device and the second device.
- the first device and the second device are any two different devices.
- the first device and the second device are any two different sensors.
- the first device and the second device are respectively a sensor and a non-sensor, for example, the first device and the second device are a sensor and a vehicle body respectively.
- the first device and the second device have the same device type.
- both the first device and the second device are lidars, the first device is the first lidar, and the second device is the second lidar.
- the first device and the second device have different device types.
- the first device is an inertial navigation device or vehicle 105
- the second device is a lidar, millimeter wave, or camera.
- the first device is a lidar
- the second device is a millimeter wave or a camera.
- the first device is a device that does not support the observation function.
- the first device is an inertial navigation device, for example, the first device is a GNSS/IMU device.
- the method 300 is executed interactively by the lidar 101, the total station 201, and the PC in the system architecture 200.
- S301 of method 300 is pre-executed by total station 201, and the data measured by total station 201 on GNSS/IMU equipment 102 and the data measured by total station 201 on the calibration board are obtained.
- S305 of method 300 is determined by lidar 101. Execute in advance to obtain the data measured by the lidar 101 on the calibration plate. The data obtained by the total station 201 and the lidar 101 respectively are used as the input of the PC, and the PC executes S307 to S312.
- the system architecture 200 can automatically obtain accurate external parameters between the lidar 101 and the GNSS/IMU device 102, that is, obtain the conversion relationship between the coordinate system of the lidar 101 and the coordinate system of the GNSS/IMU device 102.
- the external parameters between the lidar 101 and the GNSS/IMU device 102 multiple frames of laser point clouds can be combined with the pose information of each frame time to form a world point cloud.
- the method 300 includes S301 to S312.
- the measuring device measures the first device to obtain measurement data for the first device.
- the measurement data is the coordinate value of each landmark point in the coordinate system of the measuring device among the multiple landmark points on the first device.
- the mark point is located at a position with known coordinate values on the first device.
- the coordinate value of the marker point in the coordinate system of the first device can be determined in advance. Therefore, by using the coordinate values of the same marker point in the coordinate system of the first device and the coordinate values of the coordinate system of the measuring device, the coordinate system conversion relationship between the measuring device and the first device can be determined.
- the number of marking points on the first device is at least 4.
- multiple marking points on the first device are evenly distributed on the surface of the first device.
- manually mark the first device in the case that the first device itself does not have a mark point, manually mark the first device, and use the marked point as the mark point.
- the first device is a GNSS/IMU device
- the measuring device is a total station
- the calibration plane is a calibration board. Set up a total station in advance at a position visible to the GNSS/IMU equipment and the calibration board to complete the station construction.
- the total station observes multiple landmark points with known coordinates on the GNSS/IMU equipment, conducts a rear intersection, and obtains the measurement data of the GNSS/IMU equipment.
- the number of the multiple mark points is more than four.
- the measuring device transmits the measurement data of the first device to the external parameter calibration device.
- the measurement data obtained by the measurement device is stored in a storage device, and the external parameter calibration device reads the measurement data from the storage device, thereby transmitting the measurement data to the external parameter calibration device through the storage device.
- the storage device includes but is not limited to U disk or mobile hard disk.
- the measurement device directly transmits the measurement data of the first device to the external parameter calibration device.
- the measurement device establishes a wireless network connection with the external parameter calibration device, and the measurement device transmits the measurement data to the external device through wireless communication. Participate in the calibration equipment.
- the measuring device is connected to the external parameter calibration device through a cable, and the measuring device transmits the measurement data to the external parameter calibration device through the cable.
- the measuring device measures at least one calibration plane to obtain measurement data.
- the measuring device measures each calibration plane in at least one calibration plane to obtain measurement data corresponding to each calibration plane.
- each calibration plane has at least one mark point, and the measuring device measures each mark point in each calibration plane separately to obtain measurement data.
- all the marking points on a calibration plane are evenly distributed on the calibration plane, so as to prevent errors caused by the deformation of the calibration plane.
- the measuring equipment is a total station
- the calibration plane is a calibration board. Use the total station to observe several marking points on the calibration board to obtain measurement data.
- the measuring device sends the measurement data of at least one calibration plane to the external parameter calibration device.
- the second device measures at least one calibration plane to obtain measurement data.
- the second device measures each calibration plane in at least one calibration plane to obtain measurement data corresponding to each calibration plane.
- each calibration plane has at least one mark point, and the second device measures each mark point in each calibration plane separately to obtain measurement data.
- the second device is a lidar
- the calibration plane is a calibration board. The lidar is used to observe the calibration board and save point cloud data.
- the point cloud data is an example of the measurement data obtained by the second device.
- S303 and S305 are performed through multiple measurement processes.
- the calibration plane is the calibration board.
- the calibration board is first set at position i, so that the calibration board has an attitude i.
- the measuring equipment measures the calibration board of the position i and the posture i to obtain the measurement data of the i-th measurement.
- the second device measures the calibration board of position i and posture i, and obtains the measurement data of the i-th measurement.
- the position of the calibration plate is adjusted from position i to position i+1, and the posture of the calibration plate is adjusted from posture i to posture i+1.
- the measuring device measures the calibration board at the position i+1 and the posture i+1 to obtain the measurement data of the (i+1)th measurement.
- the second device measures the calibration board at the position i+1 and the posture i+1, and obtains the measurement data of the (i+1)th measurement.
- the data of n plane groups are obtained by performing n measurements on the calibration board.
- i is a positive integer
- i is greater than or equal to 1 and less than or equal to n.
- n is a positive integer
- n is greater than or equal to 2.
- n is greater than or equal to 20. In this way, due to repeated observations on the calibration plane, measurement errors can be reduced.
- the second device sends the measurement data of the at least one calibration plane to the external parameter calibration device.
- the external parameter calibration device acquires the first calibration parameter according to the measurement data of the first device by the measuring device.
- the first calibration parameter is used to indicate the coordinate system conversion relationship between the measuring device and the first device.
- the first calibration parameter is also called the coordinate system of the first device observed by the measuring device.
- the first calibration parameter includes at least one of a rotation matrix or a translation matrix.
- the rotation matrix represents the rotation transformation relationship from the coordinate system of the measuring device to the coordinate system of the first device.
- the translation matrix represents the translation transformation relationship from the coordinate system of the measuring device to the coordinate system of the first device. For example, for the point A in the coordinate system of the measuring device, the rotation matrix in the first calibration parameter is used to rotate the point A, and the translation matrix in the first calibration parameter is used to translate the point A. Get the point with the same name of point A in the coordinate system of the first device.
- the external parameter calibration device obtains the coordinate value of the mark point on the first device in the coordinate system of the first device, and according to the coordinate value of the mark point on the first device in the coordinate system of the first device And the coordinate value of the marker point measured by the measuring device in the coordinate system of the measuring device to obtain the first calibration parameter.
- the first device is a GNSS/IMU device
- the measuring device is a total station
- the external reference calibration device obtains the coordinate value of the marker point on the GNSS/IMU device in the coordinate system of the GNSS/IMU device, and calculates the total station The coordinate value of the marker point measured in the coordinate system relative to the coordinate system of the GNSS/IMU device, thereby obtaining the conversion relationship between the coordinate system of the total station and the coordinate system of the GNSS/IMU device.
- Figure 6 is an example of the coordinate system of the GNSS/IMU device.
- the conversion relationship between the coordinate system of the total station and the coordinate system of the GNSS/IMU device is an example of the first calibration parameter.
- a first calibration parameters and represented by the following equation T TI R TI (1) is, R TI and T TI also referred to a coordinate system of the total station observations GNSS / IMU device.
- Equation (1) is any point in C T p T after R TI for rotational transform, T TI and after translation transform, the same name can be obtained p T p I site in the C I.
- p T represents any point in the coordinate system of the total station.
- R TI represents the rotation matrix from the total station to the GNSS/IMU device.
- T TI represents the translation matrix from the total station to the GNSS/IMU device.
- p I represents a point in the GNSS/IMU device coordinate system.
- C T represents the coordinate system of the total station, and C I represents the coordinate system of the GNSS/IMU device.
- T is used to indicate that the data has been transposed, for example Represents the transposition of p T, Represents the transposition of p L.
- the subscript "capital English letter” is used to indicate the device corresponding to the data.
- the subscript "T” is used to indicate the data corresponding to the total station
- the subscript "I” is used to indicate the data corresponding to the GNSS/IMU device
- the subscript "L” is used to indicate the data corresponding to the lidar.
- p T represents a point in the total station coordinate system
- p L represents a point in the lidar coordinate system.
- the subscript "W" represents the world.
- the subscript "2 uppercase English letters” is used to indicate that the data is data corresponding to two devices. Specifically, the subscript “TI” indicates the data between the total station and the GNSS/IMU device, and the subscript “LT” indicates the data between the total station and the lidar.
- R TI represents the rotation matrix from the total station to the GNSS/IMU device.
- the coordinate system of the first device is calculated by observing the mark points on the first device with the measuring device, which provides a way to obtain the coordinate system of the first device through passive observation, which helps to improve the acquisition.
- the accuracy of the coordinate system of the first device (that is, the first calibration parameter).
- the measuring device is a total station, and the first device is a GNSS/IMU device.
- the GNSS is calculated
- the coordinate system of /IMU equipment solves the problem that the coordinate system of GNSS/IMU equipment is difficult to obtain.
- the accuracy of the acquired coordinate system of the GNSS/IMU device is also high.
- the external parameter calibration device determines at least one first plane mapped by the at least one calibration plane in the coordinate system of the measuring device according to the measurement data of the at least one calibration plane by the measuring device.
- the first plane is the plane mapped by the indicator plane in the coordinate system of the measuring device.
- the first plane is represented by parameters in the plane equation.
- the at least one first plane determined by the external parameter calibration device and the at least one calibration plane have a one-to-one correspondence.
- the i-th first plane determined by the external parameter calibration device is a plane mapped by the i-th calibration plane in the coordinate system of the measuring device.
- the first plane is determined by plane fitting.
- the plane fitting method is, for example, a principal component analysis (PCA) method.
- the PCA method includes, for example, centering the three-dimensional coordinates of the point cloud of the calibration plane, obtaining the covariance matrix and diagonalizing, and obtaining three eigenvalues.
- the eigenvector corresponding to the smallest eigenvalue is the normal vector of the calibration plane. . Bring in the coordinates of a point arbitrarily and normalize it to get the plane equation of the first plane.
- the calibration plane is a calibration board
- the measuring equipment is a total station
- the external parameter calibration equipment is a PC.
- the PC After using the total station to measure the calibration plate for the i-th time, the PC will calculate the space plane equation of the calibration plate in the total station coordinate system by plane fitting, as shown in the following equation (2).
- (a i, b i, c i) represents the plane of the calibration plate at a mapping coordinate system of the total station i measurement.
- the value of i is greater than or equal to 1 and less than or equal to n.
- n is the number of measurements.
- the external parameter calibration device determines at least one second plane mapped by the at least one calibration plane in the coordinate system of the second device according to the measurement data of the at least one calibration plane by the second device.
- the second plane is a plane where the indicator plane is mapped in the coordinate system of the second device.
- the second plane is represented by parameters in the plane equation.
- the at least one second plane determined by the external parameter calibration device and the at least one calibration plane have a one-to-one correspondence.
- the i-th second plane determined by the external parameter calibration device is a plane mapped by the i-th calibration plane in the coordinate system of the second device.
- the second plane is determined by plane fitting.
- the plane fitting method is, for example, the PCA method.
- the PCA method please refer to the introduction of S308 above.
- the calibration plane is a calibration board
- the second device is a lidar
- the external parameter calibration device is a PC.
- the point cloud data is obtained after the i-th measurement of the calibration board is carried out using lidar.
- the PC segmentation extracts the point cloud of the calibration plate in the point cloud data, and calculates the spatial plane equation of the calibration plate in the lidar coordinate system by plane fitting, as shown in the following equation (3).
- (A i , B i , C i ) represents the plane mapped by the calibration plate in the lidar coordinate system during the i-th measurement.
- the value of i is greater than or equal to 1 and less than or equal to n.
- n is the number of measurements.
- the external parameter calibration device determines at least one plane group according to the at least one first plane and the at least one second plane.
- a plane group includes a first plane and a second plane.
- the first plane in the plane group corresponds to the second plane.
- the first plane and the second plane in the plane group are two planes respectively mapped on the same calibration plane.
- the plane group i includes a first plane i and a second plane i.
- the first plane i is a plane mapped by the calibration plane i in the coordinate system of the measuring device.
- the second plane i is a plane mapped by the calibration plane i in the coordinate system of the second device.
- the plane is determined by the group i group i of the plane data obtained to achieve the data plane includes a group i (a i, b i, c i) and p i, (A i, B i, C i) P i, and , The normal vector of the plane and the center point of the plane.
- (a i, b i, c i) represents the i-th first plane measured.
- Pi represents a point on the plane under the coordinate system of the first device (such as a GNSS/IMU device).
- (A i, B i , C i ) represents the second plane obtained by the i-th measurement.
- P i represents a point on the plane under the coordinate system of the second device (such as lidar) corresponding to p i.
- the plane group i is an example of one plane group in at least one plane group.
- the number of plane groups determined by the external parameter calibration device is multiple.
- the number of plane groups determined by the external parameter calibration device is equal to the number of times of measuring the calibration plane. For example, after the measurement device and the second device are used to measure the calibration plane n times, the external parameter calibration device will determine n plane groups.
- the external parameter calibration device determines a second calibration parameter according to at least one plane group.
- the second calibration parameter is used to indicate the coordinate system conversion relationship between the measuring device and the second device.
- the second calibration parameter includes at least one of a rotation matrix or a translation matrix.
- the rotation matrix represents the rotation transformation relationship from the coordinate system of the measuring device to the coordinate system of the second device.
- the translation matrix represents the translation transformation relationship from the coordinate system of the measuring device to the coordinate system of the second device. For point A in the coordinate system of the measuring equipment, the rotation matrix in the second calibration parameter is used to rotate the point A, and the translation matrix in the second calibration parameter is used to translate the point A to obtain the point A point with the same name in the coordinate system of the second device.
- the measuring device is a total station
- the second device is a lidar
- the second calibration parameter is used to indicate the coordinate system conversion relationship between the total station and the lidar.
- the second calibration parameter can be determined by the following equation (4) Parameter representation.
- Equation (4) C L through any point p L R LT and after the rotational transformation T LT posterior translation transform, to obtain a point p T p L of the same name in the C T.
- p L represents any point in the coordinate system of the lidar.
- R LT represents the rotation matrix between the total station and the lidar
- T LT represents the rotation matrix between the total station and the lidar.
- p T represents the point in the coordinate system of the total station.
- CL represents the coordinate system of the lidar.
- C T represents the coordinate system of the total station.
- the external parameter calibration device uses the plane matching relationship to solve the second calibration parameter.
- the plane matching relationship refers to the matching relationship between the two planes respectively mapped on the same calibration plane in the coordinate system of the measuring device and the second device, that is, between the first plane and the second plane group in the same plane group.
- the matching relationship between. the external parameter calibration device determines the second calibration parameter according to at least one plane group, the first plane and the second plane in the plane group satisfy the matching condition. Wherein, the first plane and the second plane in the plane group satisfy the matching condition, including the following condition A and condition B.
- the angle between the normal vector of the first plane and the second plane in the plane group is the smallest.
- the first plane and the second plane are parallel or approximately parallel.
- the distance between the first plane and the second plane in the plane group is the smallest.
- the distance between the first plane and the second plane is zero or close to zero.
- the first plane and the second plane are coincident or approximately coincident.
- the solution is solved so that the first plane and the second plane have the same name.
- the calibration parameters of the plane are used as the second calibration parameters.
- the plane with the same name refers to the same plane in two coordinate systems.
- the fact that the first plane and the second plane are planes with the same name is an example of the first plane and the second plane satisfying the matching condition.
- the step of selecting the same-named point in the lidar is eliminated, so as to obtain higher The calibration accuracy.
- the second calibration parameter is solved by an optimization method.
- the rotation matrix and the translation matrix in the second calibration parameter are respectively determined by two optimization functions.
- the optimization function is also called the cost function or the objective function.
- the optimization function used to determine the rotation matrix is referred to as the first optimization function
- the optimization function used to determine the translation matrix is referred to as the second optimization function.
- the external parameter calibration device determines a rotation matrix in the second calibration parameter based on at least one plane group and the first optimization function, and the rotation matrix makes the value of the first optimization function the smallest value.
- the first optimization function is used to determine the normal vector angle between the first plane and the second plane according to the initial rotation matrix and at least one plane group.
- the input parameters of the first optimization function include an initial rotation matrix and at least one plane group, and the value of the first optimization function is used to indicate the size of the normal vector angle between the first plane and the second plane in the plane group.
- the expression of the first optimization function is as follows.
- f 1 represents the first optimization function.
- the meaning of f 1 is that the normal vector angle between the two matching planes is the smallest.
- " means or. (1-R LT *(A,B,C)*(a,b,c)) and (1+R LT *((A,B,C))) both represent the first plane and the first plane in the plane group
- the normal vector angle between the two planes specifically refers to the normal vector angle between the second plane represented by (A, B, C) and the first plane represented by (a, b, c).
- the rotation matrix in the second calibration parameter is adjusted on the basis of the initial rotation matrix in the first optimization function. For example, determine the initial rotation matrix in the first optimization function; bring the initial rotation matrix and the data of at least one plane group into the first optimization function respectively, and determine the value of the first optimization function. In this process, the initial rotation matrix in the first optimization function is adjusted. When the value of the first optimization function reaches the minimum value, the initial rotation matrix in the first optimization function is determined as the rotation matrix in the second calibration parameter.
- the optimization method is used to automatically obtain the rotation matrix.
- the calculation process of the rotation matrix can be automatically completed by the external parameter calibration equipment , Without manual intervention, thereby improving calibration efficiency and avoiding errors caused by manual intervention.
- the rotation matrix can be automatically obtained through multiple calibration data, reducing the error caused by a single calibration.
- the external parameter calibration device determines a translation matrix according to the at least one plane group and the second optimization function, and the translation matrix makes the value of the second optimization function a minimum value.
- the second optimization function is used to determine the distance between the first plane and the second plane according to the initial translation matrix and the at least one plane group.
- the input parameters of the second optimization function include an initial translation matrix and at least one plane group, and the value of the second optimization function is used to indicate the size of the distance between the first plane and the second plane in the plane group.
- the expression of the second optimization function is as follows.
- f 2 represents the second optimization function.
- the meaning of f 2 is the smallest distance between two matching planes.
- R LT represents the rotation matrix determined by the first optimization function.
- T LT represents the initial translation matrix.
- (R LT *P+T LT -p)*(a, b, c) represents the distance between the first plane and the second plane in the plane group, specifically referring to the first plane represented by (A, B, C) The distance between the second plane and the first plane indicated by (a, b, c).
- P represents a point on the first plane.
- p represents a point on the second plane.
- the translation matrix in the second calibration parameter is adjusted on the basis of the initial translation matrix in the second optimization function. For example, determine the initial translation matrix in the second optimization function; bring the initial translation matrix and the data of at least one plane group into the second optimization function respectively, and determine the value of the second optimization function. In this process, the initial translation matrix in the second optimization function is adjusted. When the value of the second optimization function reaches the minimum value, the initial translation matrix in the second optimization function is determined as the translation matrix in the second calibration parameter.
- the optimization method is used to automatically obtain the translation matrix.
- the calculation process of the translation matrix can be automatically completed by the external parameter calibration equipment , Without manual intervention, thereby improving calibration efficiency and avoiding errors caused by manual intervention.
- the translation matrix can be automatically obtained through multiple calibration data, reducing the error caused by a single calibration.
- the rotation matrix and the translation matrix are obtained step by step. Specifically, the rotation matrix is first determined according to at least one plane group; then, the translation matrix is determined according to the determined rotation matrix and the at least one plane group.
- the external parameter calibration device uses the determined rotation matrix and the initial translation matrix to perform rotation transformation and translation transformation on the point on the first plane to obtain the projection point of the point; the external parameter calibration device is based on at least A plane group determines the initial translation matrix that minimizes the distance between the projection point and the second plane as the translation matrix.
- the value of the second optimization function is the distance between the projection point of the point on the first plane and the second plane.
- the input parameters of the second optimization function include the rotation matrix.
- the rotation matrix and the initial translation matrix determined by the first optimization function are brought into the second optimization function.
- a point P is taken on the first plane; the rotation matrix determined by the first optimization function is used to rotate the point P, and the initial translation matrix is used to translate the point P, Obtain the projection point P'of the point P. Calculate the distance between the projection point P'and the second plane.
- the initial rotation matrix in the second optimization function is determined as the rotation matrix in the second calibration parameter.
- the effects achieved include: considering that even if the normal vector angle between the first plane and the second plane is the smallest, it may appear that the first plane and the second plane are not completely parallel, and It is a situation where the first plane and the second plane intersect, which makes it difficult to directly calculate the distance between the first plane and the second plane, which in turn makes it difficult to determine the translation matrix based on the distance between the planes.
- the distance calculation between the two surfaces is converted into the distance calculation between the point and the plane. Since the first plane and the second plane are parallel or non-parallel, the difference between the projection point and the second plane is The distances are easy to solve, which ensures that the method of determining the translation matrix has a wider application range and improves the practicability.
- the initial rotation matrix and the initial translation matrix include many ways.
- the first point on the first plane and the second point on the second plane are obtained, and the initial rotation matrix is determined by matrix decomposition according to the first point and the second point And the initial translation matrix.
- the first point is any point on the first plane
- the second point is any point on the second plane.
- the first point and the second point are not required to be points with the same name.
- the first point is the center point of the first plane.
- the second point is the center point of the second plane.
- the first device is a GNSS/IMU device
- the second device is a lidar.
- plane group i take a point p on the plane in the coordinate system of the GNSS/IMU device and a point P in the plane of the corresponding laser point cloud.
- the initial R LT and the initial T LT are obtained by matrix decomposition.
- the initial R LT is an example of the initial rotation matrix
- the initial T LT is an example of the initial translation matrix.
- the external parameter calibration device acquires the external parameter between the second device and the first device according to the first calibration parameter and the second calibration parameter.
- the coordinate system of the measuring device can serve as a gap between the coordinate system of the first device and the coordinate system of the second device.
- the relay According to the first calibration parameter obtained in step S307 and the second calibration parameter obtained in step S311, the external parameter between the second device and the first device can be determined.
- the external parameters between the second device and the first device include a rotation matrix between the second device and the first device and a translation matrix between the second device and the first device.
- Equation (6) The meaning of equation (6) is that any point p T in C T undergoes rotation transformation through R LT and R TI respectively, and after translation transformation through T LT and T TI respectively, the point p I of the same name in C I can be obtained.
- p L represents a point in the coordinate system of the lidar.
- R LT represents the rotation matrix between the total station and the lidar.
- T LT represents the rotation matrix between the total station and the lidar.
- R TI represents the rotation matrix from the total station to the GNSS/IMU device.
- T TI represents the translation matrix from the total station to the GNSS/IMU device.
- p I represents a point in the coordinate system of the GNSS/IMU device.
- C T represents the coordinate system of the total station
- C I represents the coordinate system of the GNSS/IMU device.
- CL represents the coordinate system of the lidar.
- the external parameter calibration device is based on the position and posture of the first device in the world coordinate system, and the relationship between the second device and the first device.
- the external parameter obtains the third calibration parameter, and the third calibration parameter is used to indicate the coordinate system conversion relationship between the second device and the world coordinate system.
- the third calibration parameter includes a rotation matrix between the coordinate system of the second device and the world coordinate system and a translation matrix between the coordinate system of the second device and the world coordinate system.
- the first device is a GNSS/IMU device
- the second device is a lidar.
- the absolute position and attitude of the origin of the GNSS/IMU device in the world coordinate system can be obtained.
- the coordinate system conversion relationship between the lidar and the world coordinate system is determined by the following equation (7).
- Equation (7) C L through any point p L and R IW rotational transformation after translation transform T IW, p L of the same name can be obtained in the point C W p W in.
- C L represents the coordinate system of the lidar
- C W represents the world coordinate system.
- p L represents a point
- T IW represents a position coordinate origin GNSS / IMU device in a world coordinate system of the coordinate system C L lidar
- R IW represents GNSS / IMU device in the world coordinate system Stance
- p W represents a point in the world coordinate system.
- S307, S308, and S309 are executed sequentially. For example, execute S307 first, then execute S308, and then execute S309; another example, execute S308 first, then execute S309, and then execute S307; another example, execute S308 first, then execute S307, and then execute S309.
- at least two of S307, S308, and S309 are executed in parallel, that is, at least two of S307, S308, and S309 are executed simultaneously.
- S301 and S303 can be executed sequentially. For example, S301 can be executed first, and then S303; or S303 can be executed first, and then S301. In other embodiments, S301 and S303 can also be executed in parallel, that is, S301 and S303 can be executed at the same time.
- S305 and S303 can be executed sequentially. For example, S305 can be executed first, and then S303; or S303 can be executed first, and then S305. In other embodiments, S305 and S303 can also be executed in parallel, that is, S305 and S303 can be executed simultaneously.
- this embodiment only uses the same external parameter calibration device to perform the above S307 to S312 as an example for description.
- the above S307 to S312 may be performed by multiple external parameter calibration devices in cooperation.
- the first device is measured by the measuring device, the coordinate system conversion relationship between the measuring device and the first device is determined, and the measurement is performed by using at least one calibration plane of the measuring device and the second device.
- the coordinate system of the measuring device can be used as a relay between the coordinate system of the first device and the coordinate system of the second device to find the external parameters between the first device and the second device.
- the method can be solidified into a computer automated execution process, avoiding the time-consuming and laborious problems caused by manual calculation of calibration parameters, thereby improving the calibration efficiency.
- the method 300 is illustrated below by using the method 400 as an example.
- the measuring device is a total station
- the calibration plane is a calibration board
- the first device is a GNSS/IMU device
- the second device is a lidar
- the external parameter calibration device is a PC.
- the method flow described in the method 400 is about how to use the measurement data of the total station and the lidar on the calibration board on the PC to determine the external parameters between the lidar and the GNSS/IMU device.
- FIG. 7 is a flowchart of a method 400 for calibrating external parameters of lidar provided by an embodiment of the application.
- the method 400 includes S401 to S404.
- the total station observes the marking points on the calibration board.
- the PC converts the observation result of the total station to the coordinate system of the GNSS/IMU device.
- Lidar scans the calibration board to obtain point cloud data.
- the PC performs plane extraction and plane fitting based on the observation result of the total station and the point cloud data.
- the PC calculates the external parameters according to the fitted plane, thereby completing the external parameter calibration, and saves the determined external parameters to the external parameter file.
- the method 300 or the method 400 of the embodiment of the present application is described above, and the external parameter calibration device of the embodiment of the present application is described below. It should be understood that the external parameter calibration device has any function of the external parameter calibration device in the above method 300 or method 400.
- FIG. 8 is a schematic structural diagram of an external parameter calibration device 500 provided by an embodiment of the present application.
- the device 500 includes: an acquisition module 501 for executing S307 and S312; and a determining module 502 for executing S308, S309, S310 and S311.
- the apparatus 500 corresponds to the external parameter calibration equipment in the above method embodiment, and the modules in the apparatus 500 and the above-mentioned other operations and/or functions are used to implement the external parameter calibration equipment in the method 300 or the method 400, respectively.
- the specific steps and methods please refer to the method 300 or the method 400 mentioned above.
- details are not repeated here.
- the device 500 when the device 500 is calibrating external parameters, only the division of the above-mentioned functional modules is used as an example. In practical applications, the above-mentioned function allocation can be completed by different functional modules as required, that is, the internal structure of the device 500 is divided into Different functional modules to complete all or part of the functions described above.
- the device 500 provided in the foregoing embodiment belongs to the same concept as the foregoing method 300 or method 400, and its specific implementation process is detailed in the method 300 or method 400, which will not be repeated here.
- the embodiments of this application also provide an external parameter calibration device.
- the hardware structure of the external parameter calibration device will be introduced below.
- the external parameter calibration device 600 corresponds to the external parameter calibration device or PC in the above method 300 or method 400.
- the hardware, modules and the above-mentioned other operations and/or functions in the external parameter calibration device 600 are used to implement the external parameter calibration in the method embodiment.
- the various steps and methods implemented by the device or PC, and the detailed process of how the external parameter calibration device 600 calibrates the external parameters can refer to the above method 300 or method 400 for specific details, and will not be repeated here for brevity. Wherein, the steps of the method 300 or the method 400 are completed by hardware integrated logic circuits in the processor of the external parameter calibration device 600 or instructions in the form of software.
- the steps of the method disclosed in the embodiments of the present application may be directly embodied as being executed and completed by a hardware processor, or executed and completed by a combination of hardware and software modules in the processor.
- the software module can be located in a mature storage medium in the field, such as random access memory, flash memory, read-only memory, programmable read-only memory, or electrically erasable programmable memory, registers.
- the storage medium is located in the memory, and the processor reads the information in the memory, and completes the steps of the above method in combination with its hardware. In order to avoid repetition, it will not be described in detail here.
- the external parameter calibration device 600 corresponds to the external parameter calibration device 500 described above, and each functional module in the device 500 is implemented by the software of the external parameter calibration device 600.
- the functional modules included in the apparatus 500 are generated after the processor of the external parameter calibration device 600 reads the program code stored in the memory.
- FIG. 9 shows a schematic structural diagram of an external parameter calibration device 600 provided by an exemplary embodiment of the present application.
- the external parameter calibration device 600 may be a host, a server, or a personal computer.
- the external parameter calibration device 600 can be implemented by a general bus architecture.
- the external parameter calibration device 600 includes at least one processor 601, a communication bus 602, a memory 603, and at least one communication interface 604.
- the processor 601 may be a general-purpose central processing unit (CPU), a network processor (NP), a microprocessor, or may be one or more integrated circuits used to implement the solutions of the present application, for example , Application-specific integrated circuit (ASIC), programmable logic device (programmable logic device, PLD) or a combination thereof.
- ASIC Application-specific integrated circuit
- PLD programmable logic device
- the above-mentioned PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a general array logic (generic array logic, GAL), or any combination thereof.
- the communication bus 602 is used to transfer information between the aforementioned components.
- the communication bus 602 can be divided into an address bus, a data bus, a control bus, and so on. For ease of presentation, only one thick line is used in FIG. 9, but it does not mean that there is only one bus or one type of bus.
- the memory 603 can be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, or it can be a random access memory (RAM) or can store information and instructions
- ROM read-only memory
- RAM random access memory
- Other types of dynamic storage devices can also be electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disk storage , CD storage (including compressed CDs, laser disks, CDs, digital universal CDs, Blu-ray CDs, etc.), disk storage media or other magnetic storage devices, or can be used to carry or store desired program codes in the form of instructions or data structures And any other media that can be accessed by the computer, but not limited to this.
- the memory 603 may exist independently and is connected to the processor 601 through the communication bus 602.
- the memory 603 may also be integrated with the processor 601.
- the communication interface 604 uses any device such as a transceiver for communicating with other devices or a communication network.
- the communication interface 604 includes a wired communication interface, and may also include a wireless communication interface.
- the wired communication interface may be, for example, an Ethernet interface.
- the Ethernet interface can be an optical interface, an electrical interface, or a combination thereof.
- the wireless communication interface may be a wireless local area network (WLAN) interface, a cellular network communication interface, or a combination thereof.
- WLAN wireless local area network
- the processor 601 may include one or more CPUs, such as CPU0 and CPU1 shown in FIG. 9.
- the external parameter calibration device 600 may include multiple processors, such as the processor 601 and the processor 605 shown in FIG. 9. Each of these processors can be a single-core processor (single-CPU) or a multi-core processor (multi-CPU).
- the processor here may refer to one or more devices, circuits, and/or processing cores for processing data (such as computer program instructions).
- the external parameter calibration device 600 may further include an output device and an input device.
- the output device communicates with the processor 601 and can display information in a variety of ways.
- the output device may be a liquid crystal display (LCD), a light emitting diode (LED) display device, a cathode ray tube (CRT) display device or a projector (projector), etc.
- the input device communicates with the processor 601 and can receive user input in a variety of ways.
- the input device can be a mouse, a keyboard, a touch screen device, or a sensor device.
- the memory 603 is used to store the program code 610 for executing the solution of the present application, and the processor 601 can execute the program code 610 stored in the memory 603. That is, the external parameter calibration device 600 can implement the external parameter calibration method provided by the method embodiment through the processor 601 and the program code 610 in the memory 603.
- the external parameter calibration device 600 in the embodiment of the present application may correspond to the external parameter calibration device in the above-mentioned method embodiments, and the processor 601, the communication interface 604, etc. in the external parameter calibration device 600 can implement the above-mentioned method embodiments
- the acquiring module 501 and the determining module 502 in the apparatus 500 are equivalent to the processor 601 or the processor 605 in the external parameter calibration device 600.
- the disclosed system, device, and method can be implemented in other ways.
- the device embodiments described above are only illustrative.
- the division of the modules is only a logical function division, and there may be other divisions in actual implementation, for example, multiple modules or components may be combined or may be Integrate into another system, or some features can be ignored or not implemented.
- the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or modules, and may also be electrical, mechanical or other forms of connection.
- modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, that is, they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the objectives of the solutions of the embodiments of the present application.
- the functional modules in the various embodiments of the present application may be integrated into one processing module, or each module may exist alone physically, or two or more modules may be integrated into one module.
- the above-mentioned integrated modules can be implemented in the form of hardware or software function modules.
- the integrated module is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium.
- the technical solution of this application is essentially or the part that contributes to the existing technology, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium It includes several instructions to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods in the various embodiments of the present application.
- the aforementioned storage media include: U disk, mobile hard disk, read-only memory (read-only memory, ROM), random access memory (random access memory, RAM), magnetic disk or optical disk and other media that can store program code .
- first, second and other words are used to distinguish the same or similar items with basically the same function and function. It should be understood that there is no logic or sequence between “first” and “second” The dependence relationship on the above does not limit the quantity and execution order. It should also be understood that although the following description uses the terms first, second, etc. to describe various elements, these elements should not be limited by the terms. These terms are only used to distinguish one element from another.
- the first calibration parameter may be referred to as the second calibration parameter
- the second calibration parameter may be referred to as the first calibration parameter.
- Both the first calibration parameter and the second calibration parameter may be calibration parameters, and in some cases, may be separate and different calibration parameters.
- the computer program product includes one or more computer program instructions.
- the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.
- the computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium.
- the computer program instructions can be passed from a website, computer, server, or data center.
- the computer-readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server or data center integrated with one or more available media.
- the usable medium may be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a digital video disc (DVD), or a semiconductor medium (for example, a solid-state hard disk), etc.
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Abstract
一种外参标定方法、装置、设备及存储介质,属于自动驾驶领域。该方法通过使用测量设备对第一设备进行测量,确定出测量设备与第一设备之间的坐标系转换关系,分别使用测量设备和第二设备对至少一个标定平面进行测量,确定出至少一个标定平面在测量设备和第二设备的坐标系下分别映射的至少一个平面组,利用至少一个平面组确定测量设备与第二设备之间的坐标系转换关系。由于外参是通过确定出的平面组获得的,而不需要从点云数据中提取同名点,从而避免了同名点的提取过程对标定精度的影响,因此提高了标定精度。
Description
本申请涉及自动驾驶领域,特别涉及一种外参标定方法、装置、设备及存储介质。
在测绘、自动驾驶等领域中,经常需要将设备测量的数据从设备本身的坐标系转换至其他坐标系,为了实现坐标系的转换,需要确定不同设备的坐标系之间的对应关系,即标定不同设备之间的外参。
以待标定的设备是激光雷达为例,相关技术在标定激光雷达的过程中,会首先在三维空间(如一个房间)中,通过测量设备扫描整个房间,根据扫描结果,获取标定物在三维空间的坐标系下映射的点的点坐标;然后,在该三维空间中通过激光雷达扫描整个房间,得到点云数据,在点云数据中提取出标定物映射的点的点坐标;在得到两个点坐标后,根据同名点(即标定物在两个坐标系下分别映射的点)之间的匹配关系,确定出激光雷达的坐标系与三维空间的坐标系之间的对应关系。
以上方法在确定外参时,需要从点云数据中提取出标定物映射的点的点坐标,而由于激光雷达本身存在测距误差并且分辨率不够高,难以精确地提取出标定物映射的点的点坐标,因此这种方法的标定精度较差。
发明内容
本申请实施例提供了一种外参标定方法、装置、设备及存储介质,能够提高外参标定的精度。所述技术方案如下:
第一方面,提供了一种外参标定方法,在该方法中,根据测量设备对第一设备的测量数据,获取第一标定参数,所述第一标定参数用于表示所述测量设备与所述第一设备之间的坐标系转换关系;根据所述测量设备对至少一个标定平面的测量数据,确定所述至少一个标定平面在所述测量设备的坐标系下映射的至少一个第一平面;根据第二设备对所述至少一个标定平面的测量数据,确定所述至少一个标定平面在所述第二设备的坐标系下映射的至少一个第二平面;根据所述至少一个第一平面和所述至少一个第二平面,确定至少一个平面组,所述平面组包括第一平面和第二平面,所述平面组中的第一平面与第二平面对应;根据所述至少一个平面组,确定第二标定参数,所述第二标定参数用于表示所述测量设备与所述第二设备之间的坐标系转换关系;根据所述第一标定参数和所述第二标定参数,获取所述第二设备与所述第一设备之间的外参。
通过以上方法来获取外参标定时,由于外参是通过确定出的平面组获得的,不需要从点云数据中提取同名点,从而避免了同名点的提取过程对标定精度的影响,因此提高了标定精度。此外,该方法能够固化为计算机自动化执行的流程,避免了人工计算标定参数会带来的费时费力的问题,因此提高了标定效率。
可选地,所述根据所述至少一个平面组,确定第二标定参数,包括:根据所述至少一个 平面组,所述平面组中的第一平面和第二平面满足匹配条件,确定第二标定参数。
可选地,所述平面组中的第一平面和第二平面满足匹配条件,包括:所述平面组中的第一平面和第二平面之间的法向量夹角最小。
可选地,所述第二标定参数包括旋转矩阵,所述根据所述至少一个平面组,所述平面组中的第一平面和第二平面之间的法向量夹角最小,确定第二标定参数,包括:根据所述至少一个平面组和第一优化函数,确定所述旋转矩阵,所述旋转矩阵使得所述第一优化函数的取值为最小值。
通过上述可选方式,由于构造了构造第一优化函数,利用多次标定数据和第一优化函数,使用优化方法自动地求取旋转矩阵,一方面,旋转矩阵的解算过程能够由外参标定设备自动化完成,而无需人工干预,从而提升标定效率,也避免人工干预带来的误差。另一方面,可以通过多次标定数据,自动地求取旋转矩阵,降低单次标定带来的误差。
可选地,所述平面组中的第一平面和第二平面满足匹配条件,包括:所述平面组中的第一平面和第二平面之间的距离最小。
通过采用上述可选方式,由于利用平面匹配关系求解设备之间的外参,免去了选取同名点的步骤,获得更高的标定精度。
可选地,所述第二标定参数包括平移矩阵,所述根据所述至少一个平面组,所述平面组中的第一平面和第二平面之间的距离最小,确定第二标定参数,包括:根据所述至少一个平面组和第二优化函数,确定所述平移矩阵,所述平移矩阵使得所述第二优化函数的取值为最小值。
通过上述可选方式,由于构造了第二优化函数,利用多次标定数据和第二优化函数,使用优化方法自动地求取平移矩阵,一方面,平移矩阵的解算过程能够由外参标定设备自动化完成,而无需人工干预,从而提升标定效率,也避免人工干预带来的误差。另一方面,可以通过多次标定数据,自动地求取平移矩阵,降低单次标定带来的误差。
可选地,所述第二标定参数包括平移矩阵,所述根据所述至少一个平面组,确定第二标定参数,包括:使用所述旋转矩阵和初始平移矩阵,对第一平面上的点进行旋转变换和平移变换,得到所述点的投影点;根据所述至少一个平面组,确定使得所述投影点和所述第二平面之间的距离最小的初始平移矩阵,作为所述平移矩阵。
通过上述可选方式,考虑到即使第一平面和第二平面之间的法向量夹角最小,也可能出现第一平面和第二平面并非完全平行,而是第一平面和第二平面之间相交的情况,导致难以直接计算出第一平面和第二平面之间的距离,进而导致难以根据平面之间的距离确定平移矩阵。而通过上述方式,将两个面之间的距离计算转换为点和平面之间的距离计算,由于第一平面和第二平面平行或非平行的情况下,投影点和第二平面之间的距离都是容易求解的,从而保证确定平移矩阵的方法的应用范围更广泛,提升了实用性。
可选地,所述根据测量设备对第一设备的测量数据,获取第一标定参数,包括:根据所述第一设备上的标志点在所述第一设备的坐标系下的坐标值和所述测量设备测量得到的所述标志点在所述测量设备的坐标系下的坐标值,获取所述第一标定参数。
在第一设备不支持观测功能的情况下,会存在难以获得第一设备的坐标系的技术问题。而通过上述可选方式,由于使用测量设备观测第一设备上的标志点,来推算出第一设备的坐标系,提供了一种通过被动观测获取第一设备的坐标系的方式,有助于提高获得的第一设备 的坐标系(即第一标定参数)的精度。
可选地,所述测量设备为全站仪、激光扫描仪或摄影测量***,所述标定平面为标定板或墙,所述第一设备为惯导设备、车辆或第一激光雷达,所述第二设备为第二激光雷达、毫米波或相机。
第二方面,提供了一种外参标定装置,该外参标定装置包括:
获取模块,用于根据测量设备对第一设备的测量数据,获取第一标定参数,所述第一标定参数用于表示所述测量设备与所述第一设备之间的坐标系转换关系;
确定模块,用于根据所述测量设备对至少一个标定平面的测量数据,确定所述至少一个标定平面在所述测量设备的坐标系下映射的至少一个第一平面;
确定模块,用于根据第二设备对所述至少一个标定平面的测量数据,确定所述至少一个标定平面在所述第二设备的坐标系下映射的至少一个第二平面;
确定模块,用于根据所述至少一个第一平面和所述至少一个第二平面,确定至少一个平面组,所述平面组包括第一平面和第二平面,所述平面组中的第一平面与第二平面对应;
确定模块,用于根据所述至少一个平面组,确定第二标定参数,所述第二标定参数用于表示所述测量设备与所述第二设备之间的坐标系转换关系;
所述获取模块,还用于根据所述第一标定参数和所述第二标定参数,获取所述第二设备与所述第一设备之间的外参。
其中,该外参标定装置是有计算能力的装置,例如,该外参标定装置是计算设备、处理器、芯片、个人计算机等。
可选地,所述确定模块,用于根据所述至少一个平面组,所述平面组中的第一平面和第二平面满足匹配条件,确定第二标定参数。
可选地,所述平面组中的第一平面和第二平面满足匹配条件,包括:所述平面组中的第一平面和第二平面之间的法向量夹角最小。
可选地,所述第二标定参数包括旋转矩阵,所述确定模块,用于根据所述至少一个平面组和第一优化函数,确定所述旋转矩阵,所述旋转矩阵使得所述第一优化函数的取值为最小值。
可选地,所述平面组中的第一平面和第二平面满足匹配条件,包括:所述平面组中的第一平面和第二平面之间的距离最小。
可选地,所述第二标定参数包括平移矩阵,所述确定模块,用于根据所述至少一个平面组和第二优化函数,确定所述平移矩阵,所述平移矩阵使得所述第二优化函数的取值为最小值。
可选地,所述第二标定参数包括平移矩阵,所述确定模块,用于使用所述旋转矩阵和初始平移矩阵,对第一平面上的点进行旋转变换和平移变换,得到所述点的投影点;根据所述至少一个平面组,确定使得所述投影点和所述第二平面之间的距离最小的初始平移矩阵,作为所述平移矩阵。
可选地,所述获取模块,用于根据所述第一设备上的标志点在所述第一设备的坐标系下的坐标值和所述测量设备测量得到的所述标志点在所述测量设备的坐标系下的坐标值,获取所述第一标定参数。
可选地,所述测量设备为全站仪、激光扫描仪或摄影测量***,所述标定平面为标定板或墙,所述第一设备为惯导设备、车辆或第一激光雷达,所述第二设备为第二激光雷达、毫米波或相机。
第三方面,提供了一种外参标定设备,该外参标定设备包括处理器,该处理器用于执行指令,使得该外参标定设备执行上述第一方面或第一方面任一种可选方式所提供的外参标定方法。第三方面提供的外参标定设备的具体细节可参见上述第一方面或第一方面任一种可选方式,此处不再赘述。
第四方面,提供了一种计算机可读存储介质,该存储介质中存储有至少一条指令,该指令由处理器读取以使外参标定设备执行上述第一方面或第一方面任一种可选方式所提供的外参标定方法。
第五方面,提供了一种计算机程序产品,当该计算机程序产品在外参标定设备上运行时,使得外参标定设备执行上述第一方面或第一方面任一种可选方式所提供的外参标定方法。
第六方面,提供了一种芯片,当该芯片在外参标定设备上运行时,使得外参标定设备执行上述第一方面或第一方面任一种可选方式所提供的外参标定方法。
第七方面,提供了一种外参标定***,该外参标定***包括外参标定设备、测量设备、第一设备以及第二设备,该外参标定设备用于执行上述第一方面或第一方面任一种可选方式所述的方法。
图1是本申请实施例提供的一种激光雷达的外参标定的应用场景的示意图;
图2是本申请实施例提供的一种高精地图采集***的架构示意图;
图3是本申请实施例提供的一种高精地图采集***中外参标定装置的示意图;
图4是本申请实施例提供的一种外参标定装置的装置名称、规格参数和参考图的示意图;
图5是本申请实施例提供的一种外参标定方法300的流程图;
图6是本申请实施例提供的一种GNSS/IMU设备的坐标系的示意图;
图7是本申请实施例提供的一种外参标定方法400的流程图;
图8是本申请实施例提供的一种外参标定装置500的结构示意图;
图9是本申请实施例提供的一种外参标定设备600的结构示意图。
为使本申请的目的、技术方案和优点更加清楚,下面将结合附图对本申请实施方式作进一步地详细描述。
为了便于理解,下面先对本申请实施例涉及的一些术语相关概念进行介绍。
标定是一种设备参数的获得过程,标定的目的是为了确定设备的一些参数的值。标定包 括内参标定和外参标定。
外参标定是指确定设备A与设备B之间的坐标系转换关系的过程。通过设备A与设备B之间的外参,能够将设备A的坐标系中的点经过旋转和平移后映射到设备B的坐标系中,或者反过来,将设备B的坐标系中的点经过旋转和平移后映射到设备A的坐标系中。例如,标定激光雷达(Light Detection and Ranging,LiDAR)与全球导航卫星***(Global Navigation Satellite System,GNSS)/惯性测量单元(Inertial measurement unit,IMU)设备之间的外参是求取激光雷达的坐标系至GNSS/IMU设备的坐标系之间的位姿变换关系。两个设备之间的外参通常利用旋转矩阵和平移矩阵表示。
旋转矩阵表示设备A与设备B之间的坐标系的旋转变换关系。可选地,旋转矩阵是三行三列大小的矩阵,旋转矩阵包括3个自由度,这3个自由度分别对应于x轴、y轴和z轴,旋转矩阵表示绕x轴、y轴和z轴这三个轴的旋转变换关系。可选地,旋转矩阵通过以下矩阵R
LI表示。
或者,为了简化表达,旋转矩阵通过一个四元数来表示,四元数例如记为q
LI。四元数q
LI例如为(w,x,y,z)。R
LI和q
LI是等同的,均表示旋转变换。
平移矩阵表示设备A与设备B之间的坐标系的平移变换关系。可选地,旋转矩阵是3*1大小的矩阵,旋转矩阵包括3个自由度,这3个自由度分别对应于x轴、y轴和z轴,平移矩阵表示x、y和z这三个轴方向的平移。例如,平移矩阵通过以下矩阵T
LI表示。
T
LI=[t
x t
y t
z]
T
本申请实施例提供的外参标定方法能够应用在激光雷达的外参标定场景。下面对激光雷达的外参标定场景进行简单的介绍。
激光雷达是一种新型传感器。激光雷达包括激光发射器和接收器。激光发射器产生并发射一束光脉冲,光脉冲打在物体上并反射回来,最终光脉冲被接收器所接收。接收器准确地测量光脉冲从发射到被反射回的传播时间。根据激光发射器的高度,激光扫描角度,准确地计算出每一个光斑相对于激光雷达中心的坐标。
由于激光雷达的测距精度可达几个厘米,测距精度较为精确,使得激光雷达被广泛应用于测绘、智能驾驶等领域。在应用过程中,经常需要将激光雷达所获取的点云信息,由激光雷达坐标系转换至其它坐标系。例如,在高精地图制作中,需要用到激光雷达扫描采集区域内的激光点云,以及定位定姿***(如GNSS/IMU设备)所获取的位姿信息。参见附图1,需要进行激光雷达与GNSS/IMU设备的外参标定,即获取激光雷达坐标系与GNSS/IMU设备坐标系间的转换关系,以便利用激光雷达与GNSS/IMU设备之间的外参,将多帧激光点云结合每帧时刻的位姿信息,拼接成世界点云。
以上介绍了激光雷达的外参标定场景,以下对激光雷达的外参标定场景在具体应用中的情况举例说明,并介绍本申请提供的方法在该应用场景中的技术效果。
在一种可能的实现中,获取多传感器的安装数据,依据每个传感器的安装数据,计算出各传感器间的相对位置关系,从而计算出各传感器间的外参。传感器的安装数据的形式不限于设计图纸、计算机辅助技术(Computer Aided Design,CAD)图纸、三维模型等一切可量测数学模型。例如,根据激光雷达的设计图纸内的公式,计算出激光雷达坐标系的中心位置。同理地,计算出激光雷达之外的其他传感器的中心位置,然后计算出激光雷达与其他传感器在空间中的相对位置关系。
然而,当采用上述方式时,由于实际安装存在误差,实际安装不能够精确的按照设计图纸的要求进行,所以会引入安装误差。故只依赖设计图纸数据计算出的外参精度不够高。
在一种可能的实现中,在一个三维场景,如一个房间,通过高精度的三维测量设备,扫描获得整个房间内标志物(如墙角、柱子、以及其它标志物)的三维坐标。然后使用激光雷达扫描整个房间,提取出各标志物在激光雷达点云中的坐标,通过同名标志物的匹配关系,确定出激光雷达坐标系与三维空间坐标系的关系。
然而,当采用上述方式时,第一,难以实现不支持观测功能的传感器(如GNSS/IMU设备)与所诉三维场景间坐标系转换关系的建立。即无法进行GNSS/IMU设备与激光雷达、相机之间的外参标定。第二,使用匹配点的方式进行校准,需要在激光点云中提取与三维模型对应的点,而实际上激光雷达精度一般在±2厘米(cm),所以使用这种方式精度较差。第三,建立三维场景模型需要的设备十分昂贵,精度较高的设备价格在百万级别,所以使用这种方式成本过高。
在一种可能的实现中,根据所记录的多线激光雷达的高度和GNSS/IMU设备读取的多线激光雷达的姿态角度信息,确定多线激光雷达相对于参考平面的参考点,可视化显示上述参考点,根据所显示的参考点和与之对应的实际点云之间的偏差,调整GNSS/IMU设备与多线激光雷达之间的标定参数,当根据调整后的标定参数显示的偏差为零时,确定标定结束。
然而,当采用上述方式时,需要专业人员人工根据方案原理及可视化结果不断调整标定参数。因此,该方式的缺陷在于比较费时费力且需要专业人员操作,无法固化为流程;其次依赖人工,无法进行自动化,且精度依赖人眼观察结果。
在一种可能的实现中,使用多线激光雷达扫描一个平板;根据扫描的结果,提取平板边缘点,拟合平板边缘线;通过两条边缘线的交点,求取平板的角点,作为激光雷达坐标系下的已知点。
然而,当采用上述方式时,拟合边缘线是利用激光雷达扫描平板边缘得到的若干点(数量不超过线束数),其精度难以得到保证。并且,无法获取角点在GNSS/IMU设备坐标系下的准确坐标。例如,在使用全站仪的情况下,无法准确照准角点。
在激光雷达与GNSS/IMU设备之间的外参标定场景下,由于GNSS/IMU设备本身无法主动观测,所以无法间接获得其坐标系,必须通过其它参照物来获取GNSS/IMU设备的坐标系。其次,激光雷达本身存在测距误差,再加上其分辨率不够高,可能无法精确获得空间中某一点的位置。综上,导致了激光雷达与GNSS/IMU设备外参标定比较困难且精度不够高,无法满足高精度地图制图的需求。
本申请的一些实施例中,针对高精地图采集***中激光雷达与GNSS/IMU设备这两个设 备之间外参标定场景,提出一种高精度、自动化程度高的激光雷达外参标定方法。通过利用高精度三维测量设备(如全站仪)结合GNSS/IMU设备的机构尺寸参数,观测出GNSS/IMU设备的坐标系,并使用全站仪与激光雷达同时观测标定平面(如标定平板),利用拟合出的同名平面的匹配关系,构造匹配条件,分步求解旋转矩阵和平移矩阵。由于避免从激光点云中选取同名点,从而提高了标定精度。
下面介绍本申请实施例提供的***架构。
参见附图2,本申请实施例提供了一种***架构100。***架构100是对高精地图采集***的举例说明。其中,高精地图中的“高精度”包括两个方面的含义。一方面是指地图中的坐标精度更高,例如坐标的精度在厘米级。另一方面是指地图所含有的道路交通信息元素更丰富和细致,例如地图不仅包括道路,还包括道路形状、红绿灯等信息。
***架构100包括激光雷达101、GNSS/IMU设备102、长焦相机103、短焦相机104、天线107和车辆105。
GNSS/IMU设备102与激光雷达101、长焦相机103和短焦相机104刚性连接固定。激光雷达101、GNSS/IMU设备102、天线107、长焦相机103、短焦相机104设置在基座106上,基座106设置在车辆105的车顶上。
在制作高精地图的过程中,激光雷达101用于扫描采集区域内的激光点云。GNSS/IMU设备102用于获取位姿信息。
参见附图3,本申请实施例提供了一种***架构200。***架构200是对高精地图采集***的举例说明。例如,***架构200适于应用在***架构100中激光雷达101与GNSS/IMU设备102之间的外参标定场景。***架构200包括激光雷达101、GNSS/IMU设备102、全站仪201、多个标定板和个人计算机(Personal Computer,PC),可选地,PC是其他具有处理能力的装置,例如是处理器、芯片等。其中PC在附图3中未示出。参见附图4,附图4是对***架构200涉及的每个装置的装置名称、规格参数和参考图的举例说明。
可选地,全站仪201是激光全站仪。全站仪201的测距精度例如是0.1毫米(mm)。全站仪201设置在与GNSS/IMU设备102和标定板均通视的位置。
多个标定板包括标定板2021、标定板2022和标定板2023。标定板2021、标定板2022和标定板2023设置在不同的位置。标定板2021、标定板2022和标定板2023具有不同的姿态。可选地,标定板是珐琅标定板。可选地,标定板具有标定氧化铝镀层。可选地,标定板的规格是1.0米*1.0米,即宽度和高度各为1米。其中,氧化铝镀层的材质是高反材料,氧化铝镀层的漫反射程度较小。珐琅玻璃表面非常平整且不易产生形变。
GNSS/IMU设备102为待标定的惯导设备。可选地,GNSS/IMU设备102的外形是一个盒子。
可选地,激光雷达101是多线束的激光雷达101。激光雷达101设置在可观测标定板的位置。激光雷达101与GNSS/IMU设备102刚性连接固定。
PC中安装和运行有解算程序,该解算程序用于求解旋转矩阵和平移矩阵,从而确定出激光雷达101、GNSS/IMU设备102之间的外参。PC通过无线网络或有线网络与激光雷达101、GNSS/IMU设备102、全站仪201中的至少一者相连。
以上介绍了***架构,以下通过方法300至方法400,示例性介绍基于上文提供的***架构进行外参标定的方法流程。
参见附图5,附图5是本申请实施例提供的一种外参标定方法300的流程图。
方法300涉及的硬件装置包括测量设备、第一设备、第二设备、标定平面和外参标定设备。
可选地,测量设备是高精度三维测量设备。例如,测量设备为全站仪、激光扫描仪或摄影测量***。
可选地,标定平面是任意具有平整表面的硬件装置。可选地,标定平面是激光无法穿透的平面。例如,标定平面为标定板或墙。其中,通过使用标定板,有助于得到较高的标定精度。
方法300用于第一设备与第二设备之间的外参标定。可选地,第一设备和第二设备是任意两个不同的设备。可选地,第一设备和第二设备是任意两个不同的传感器。可选地,第一设备和第二设备分别是传感器和非传感器,例如第一设备和第二设备分别是传感器和车体。可选地,第一设备和第二设备具有相同的设备类型。例如,第一设备和第二设备均是激光雷达,第一设备是第一激光雷达,第二设备是第二激光雷达。可选地,第一设备和第二设备具有不同的设备类型。例如,第一设备是惯导设备或车辆105,第二设备是激光雷达、毫米波或相机。例如,第一设备是激光雷达,第二设备是毫米波或相机。可选地,第一设备是不支持观测功能的设备。例如,第一设备是惯导设备,比如第一设备是GNSS/IMU设备。
可选地,方法300由***架构200中的激光雷达101、全站仪201和PC交互执行。例如,方法300的S301由全站仪201预先执行,得到全站仪201对GNSS/IMU设备102测量得到的数据、全站仪201对标定板测量得到的数据,方法300的S305由激光雷达101预先执行,得到激光雷达101对标定板测量得到的数据。全站仪201和激光雷达101分别得到的数据作为PC的输入,并由PC执行S307至S312。***架构200通过实施方法300,能够自动化地获得精确的激光雷达101与GNSS/IMU设备102间的外参,即获取激光雷达101坐标系与GNSS/IMU设备102坐标系间的转换关系。利用激光雷达101与GNSS/IMU设备102之间的外参,能够将多帧激光点云结合每帧时刻的位姿信息,拼接成世界点云。
示例性地,方法300包括S301至S312。
S301、测量设备对第一设备进行测量,得到对第一设备的测量数据。
在一些实施例中,第一设备上具有多个标志点,测量数据是第一设备上多个标志点中每个标志点在测量设备的坐标系下的坐标值。
标志点位于第一设备上已知坐标值的位置。换句话说,标志点在第一设备的坐标系下的坐标值是能够预先确定的。因此,利用同一个标志点在第一设备的坐标系下的坐标值和在测量设备的坐标系下的坐标值,能够确定测量设备与第一设备之间的坐标系转换关系。可选地,第一设备上标志点的数量是至少4个。可选地,第一设备上的多个标志点均匀分布在第一设备的表面上。可选地,在第一设备本身没有标志点的情况下,人工对第一设备上进行标记,将标记的点作为标志点。
例如,第一设备是GNSS/IMU设备,测量设备是全站仪,标定平面是标定板。预先在与GNSS/IMU设备以及标定板通视的位置架设全站仪,完成建站。在执行S301的过程中,全站仪观测GNSS/IMU设备上已知坐标的多个标志点,进行后方交会,得到对GNSS/IMU设备的 测量数据。其中,该多个标志点的数量在4个以上。
S302、测量设备将对第一设备的测量数据传输至外参标定设备。
如何将测量数据传输至外参标定设备包括多种方式。可选地,将测量设备测量得到测量数据保存至存储设备中,外参标定设备从存储设备中读取测量数据,从而通过存储设备将测量数据传输至外参标定设备。该存储设备包括而不限于U盘或移动硬盘等。可选地,测量设备直接将对第一设备的测量数据传输至外参标定设备,例如,测量设备与外参标定设备建立无线网络连接,测量设备通过无线通信的方式,将测量数据传输至外参标定设备。又如,测量设备与外参标定设备通过线缆相连,测量设备将测量数据通过线缆传输至外参标定设备。
S303、测量设备对至少一个标定平面进行测量,得到测量数据。
测量设备对至少一个标定平面中的每个标定平面进行测量,得到每个标定平面对应的测量数据。可选地,每个标定平面上具有至少一个标志点,测量设备对每个标定平面中的每个标志点分别进行测量,得到测量数据。可选地,一个标定平面上具有至少九个标志点。可选地,一个标定平面上的所有标志点均匀分布在标定平面上,从而防止由于标定平面变形带来的误差。例如,测量设备是全站仪,标定平面是标定板,使用全站仪观测标定板上若干标志点,得到测量数据。
S304、测量设备将对至少一个标定平面的测量数据发送至外参标定设备。
S305、第二设备对至少一个标定平面进行测量,得到测量数据。
第二设备对至少一个标定平面中的每个标定平面进行测量,得到每个标定平面对应的测量数据。可选地,每个标定平面上具有至少一个标志点,第二设备对每个标定平面中的每个标志点分别进行测量,得到测量数据。例如,第二设备是激光雷达,标定平面是标定板,使用激光雷达观测标定板,保存点云数据,该点云数据是对第二设备得到的测量数据的举例说明。
在一些实施例中,S303和S305通过多次测量过程执行。例如,标定平面是标定板,在执行第i次测量时,先将标定板设置在位置i,使得标定板具有姿态i。然后,测量设备对位置i和姿态i的标定板进行测量,得到第i次测量的测量数据。第二设备对位置i和姿态i的标定板进行测量,得到第i次测量的测量数据。之后,在执行第(i+1)次测量时,将标定板的位置从位置i调整至位置i+1,将标定板的姿态从姿态i调整至姿态i+1。然后,测量设备对位置i+1和姿态i+1的标定板进行测量,得到第(i+1)次测量的测量数据。第二设备对位置i+1和姿态i+1的标定板进行测量,得到第(i+1)次测量的测量数据。依次类推,通过对标定板进行n次测量,得到n个平面组的数据。其中,i是正整数,i大于或等于1且小于或等于n。n是正整数,n大于或等于2。可选地,n大于或等于20。通过这种方式,由于对标定平面进行了重复观测,能够减少测量误差。
S306、第二设备将对至少一个标定平面的测量数据发送至外参标定设备。
S307、外参标定设备根据测量设备对第一设备的测量数据,获取第一标定参数。
第一标定参数用于表示测量设备与第一设备之间的坐标系转换关系。第一标定参数也称测量设备所观测出的第一设备的坐标系。具体地,第一标定参数包括旋转矩阵或者平移矩阵中的至少一项。该旋转矩阵表示从测量设备的坐标系至第一设备的坐标系的旋转变换关系。该平移矩阵表示从测量设备的坐标系至第一设备的坐标系的平移变换关系。例如,对于测量设备的坐标系中的点A而言,利用第一标定参数中的旋转矩阵对点A进行旋转变换,并利用 第一标定参数中的平移矩阵对点A进行平移变换后,能够得到点A在第一设备的坐标系中的同名点。
如何确定第一标定参数包括多种实现方式。在一种可能的实现中,外参标定设备获取第一设备上的标志点在第一设备的坐标系下的坐标值,根据第一设备上的标志点在第一设备的坐标系下的坐标值和测量设备测量得到的标志点在测量设备的坐标系下的坐标值,获取第一标定参数。
例如,第一设备是GNSS/IMU设备,测量设备是全站仪,外参标定设备获取GNSS/IMU设备上的标志点在GNSS/IMU设备的坐标系下的坐标值,并计算出全站仪坐标系下测量出的标志点相对于GNSS/IMU设备坐标系的坐标值,从而得到全站仪的坐标系相对于GNSS/IMU设备的坐标系的转换关系。其中,请参见附图6,附图6是对GNSS/IMU设备的坐标系的举例说明。全站仪的坐标系相对于GNSS/IMU设备的坐标系的转换关系是对第一标定参数的举例说明。第一标定参数例如通过以下方程(1)中的R
TI和T
TI表示,R
TI和T
TI也称为全站仪观测出的GNSS/IMU设备的坐标系。
方程(1)的含义是C
T中任意一点p
T经过R
TI进行旋转变换,并经过T
TI平移变换后,能够得到p
T在C
I中的同名点p
I。在方程(1)中,p
T表示全站仪坐标系中的任意一点。R
TI表示从全站仪至GNSS/IMU设备的旋转矩阵。T
TI表示从全站仪至GNSS/IMU设备的平移矩阵。p
I表示GNSS/IMU设备坐标系中的点。C
T表示全站仪的坐标系,C
I表示GNSS/IMU设备的坐标系。
为了简明起见,本实施例涉及的每个方程中,用下标“大写英文字母”表示数据对应的设备。具体地,用下标“T”来表示全站仪对应的数据,用下标“I”表示GNSS/IMU设备对应的数据,用下标“L”表示激光雷达对应的数据。例如,p
T表示全站仪坐标系中的点,p
L表示激光雷达坐标系中的点。此外,下标“W”表示世界。
为了简明起见,本实施例涉及的每个方程中,用下标“2个大写英文字母”表示数据是2个设备对应的数据。具体地,下标“TI”标识全站仪与GNSS/IMU设备之间的数据,下标“LT”表示全站仪与激光雷达之间的数据。例如,如上述方程(1)中,R
TI表示从全站仪至GNSS/IMU设备的旋转矩阵。
本段对上述方式的技术效果进行介绍。在第一设备不支持观测功能的情况下,会存在难以获得第一设备的坐标系的技术问题。而上述方法中,通过使用测量设备观测第一设备上的标志点,来推算出第一设备的坐标系,提供了一种通过被动观测获取第一设备的坐标系的方式,有助于提高获得的第一设备的坐标系(即第一标定参数)的精度。例如,测量设备是全站仪,第一设备是GNSS/IMU设备。通过使用全站仪观测GNSS/IMU设备外表面上的标志点,结合GNSS/IMU设备机构尺寸参数(即GNSS/IMU设备上标志点在GNSS/IMU设备坐标系下的坐标值),推算出GNSS/IMU设备的坐标系,解决了GNSS/IMU设备的坐标系难以获取的问题。并且,由于全站仪的观测精度高,所以获取的GNSS/IMU设备的坐标系的精度也高。
S308、外参标定设备根据测量设备对至少一个标定平面的测量数据,确定至少一个标定平面在测量设备的坐标系下映射的至少一个第一平面。
第一平面是指标定平面在测量设备的坐标系下映射的平面。可选地,第一平面通过平面方程中的参数表示。可选地,外参标定设备确定的至少一个第一平面和至少一个标定平面是一一对应的。例如,外参标定设备确定的第i个第一平面是第i个标定平面在测量设备的坐标系下映射的平面。可选地,第一平面通过平面拟合的方式确定。平面拟合的方式例如是主成分分析(Principal Component Analysis,PCA)方法。
其中,PCA方法例如包括:将标定平面的点云的三维坐标进行中心化,求得协方差矩阵并对角化,求得三个特征值,最小特征值对应的特征向量就是标定平面的法向量。任意带入一点的坐标,并归一化即可得到第一平面的平面方程。
例如,标定平面是标定板,测量设备是全站仪,外参标定设备是PC。使用全站仪对标定板进行第i次测量后,PC通过平面拟合的方式,会计算出标定板在全站仪坐标系下空间平面的方程,如以下方程(2)所示。
a
iX+b
iY+c
iZ+1=0;方程(2)
在方程(2)中,(a
i,b
i,c
i)表示第i次测量时标定板在全站仪坐标系下映射的平面。i的取值是大于或等于1且小于或等于n。n是测量的次数。依次类推,使用全站仪对标定板进行n次测量后,会得到(a
1,b
1,c
1)、(a
2,b
2,c
2)……(a
i,b
i,c
i)和(a
n,b
n,c
n)这n组数据,这n组数据表示n个第一平面。
S309、外参标定设备根据第二设备对至少一个标定平面的测量数据,确定至少一个标定平面在第二设备的坐标系下映射的至少一个第二平面。
第二平面是指标定平面在第二设备的坐标系下映射的平面。可选地,第二平面通过平面方程中的参数表示。可选地,外参标定设备确定的至少一个第二平面和至少一个标定平面是一一对应的。例如,外参标定设备确定的第i个第二平面是第i个标定平面在第二设备的坐标系下映射的平面。可选地,第二平面通过平面拟合的方式确定。平面拟合的方式例如是PCA方法。PCA方法请参见上述S308的介绍。
例如,标定平面是标定板,第二设备是激光雷达,外参标定设备是PC。使用激光雷达对标定板进行第i次测量后,得到点云数据。PC分割提取出点云数据中标定板的点云,通过平面拟合的方式,计算出标定板在激光雷达坐标系下空间平面的方程,如以下方程(3)所示。
A
iX+B
iY+C
iZ+1=0;方程(3)
在方程(3)中,(A
i,B
i,C
i)表示第i次测量时标定板在激光雷达坐标系下映射的平面。i的取值是大于或等于1且小于或等于n。n是测量的次数。依次类推,使用激光雷达对标定板进行n次测量后,会得到(A
1,B
1,C
1)、(A
2,B
2,C
2)、……(A
i,B
i,C
i)、……(A
n,B
n,C
n)这n组数据,这n组数据表示n个第二平面。
S310、外参标定设备根据至少一个第一平面和至少一个第二平面,确定至少一个平面组。
一个平面组包括一个第一平面和一个第二平面。平面组中的第一平面与第二平面对应。例如,平面组中的第一平面和第二平面是同一个标定平面分别映射的两个平面。例如,平面组i包括第一平面i和第二平面i。其中,第一平面i是标定平面i在测量设备的坐标系下映射的平面。第二平面i是标定平面i在第二设备的坐标系下映射的平面。可选地,确定平面组i通过获得平面组i的数据实现,平面组i的数据包括(a
i,b
i,c
i)和p
i、(A
i,B
i,C
i)和P
i、 平面的法向量以及平面中心点。其中,(a
i,b
i,c
i)表示第i次测量得到的第一平面。p
i表示第一设备(如GNSS/IMU设备)坐标系下平面上的一点。(A
i,B
i,C
i)表示第i次测量得到的第二平面。P
i表示p
i对应的第二设备(如激光雷达)坐标系下平面上的一点。其中,平面组i是对至少一个平面组中的一个平面组的举例说明。
在一些实施例中,外参标定设备确定出的平面组的数量是多个。可选地,外参标定设备确定出的平面组的数量和测量标定平面的次数相等。例如,分别使用测量设备和第二设备对标定平面进行n次测量后,外参标定设备会确定出n个平面组。
S311、外参标定设备根据至少一个平面组,确定第二标定参数。
其中,第二标定参数用于表示测量设备与第二设备之间的坐标系转换关系。具体地,第二标定参数包括旋转矩阵或者平移矩阵中的至少一项。该旋转矩阵表示从测量设备的坐标系至第二设备的坐标系的旋转变换关系。该平移矩阵表示从测量设备的坐标系至第二设备的坐标系的平移变换关系。对于测量设备的坐标系中的点A而言,利用第二标定参数中的旋转矩阵对点A进行旋转变换,并利用第二标定参数中的平移矩阵对点A进行平移变换后,能够得到点A在第二设备的坐标系中的同名点。
例如,测量设备是全站仪,第二设备为激光雷达,第二标定参数用于表示全站仪与激光雷达之间的坐标系转换关系,第二标定参数可以通过以下方程(4)中的参数表示。
方程(4)的含义是,C
L中任意一点p
L经过R
LT旋转变换并经过T
LT平移变换后,能够得到p
L在C
T中的同名点p
T。方程(4)中,p
L表示激光雷达的坐标系中的任意一点。R
LT表示全站仪与激光雷达之间的旋转矩阵,T
LT表示全站仪与激光雷达之间的旋转矩阵。p
T表示全站仪的坐标系中的点。C
L表示激光雷达的坐标系。C
T表示全站仪的坐标系。
在一些实施例中,外参标定设备利用平面匹配关系求解第二标定参数。其中,平面匹配关系是指同一个标定平面在测量设备和第二设备的坐标系下分别映射的两个平面之间的匹配关系,即,同一平面组中的第一平面和第二平面组之间的匹配关系。具体地,外参标定设备根据至少一个平面组,平面组中的第一平面和第二平面满足匹配条件,确定第二标定参数。其中,平面组中的第一平面和第二平面满足匹配条件,包括以下条件A和条件B。
条件A、平面组中的第一平面和第二平面之间的法向量夹角最小。例如,第一平面和第二平面平行或者近似平行。
条件B、平面组中的第一平面和第二平面之间的距离最小。例如,第一平面和第二平面之间的距离是0或接近0。换句话说,第一平面和第二平面是重合或近似重合的。
在一些实施例中,当外参标定设备通过平面拟合的方式,分别拟合出标定平面映射的第一平面和标定平面映射的第二平面后,求解使得第一平面和第二平面是同名平面的标定参数,作为第二标定参数。其中,同名平面是指两个坐标系下的同一个平面。第一平面和第二平面是同名平面是对第一平面和第二平面满足匹配条件的举例说明。
本段对利用平面匹配关系求解第二标定参数的效果进行介绍。在利用同名点进行匹配以求解标定参数的方式中,会由于选取的同名点准确性不高,出现影响标定精度的技术问题。例如,在第二设备是激光雷达的情况下,如果通过选取激光雷达中的同名点并利用点对匹配 的方法求解标定参数,会由于激光雷达具有一定的测距误差导致标定精度不够高。而采用以上方式,通过进行平面拟合,并利用平面匹配关系求解激光雷达坐标系与GNSS/IMU设备坐标系间的转换关系,免去了选取激光雷达中的同名点的步骤,从而获得更高的标定精度。
在一些实施例中,第二标定参数通过优化的方法求解。例如,第二标定参数中的旋转矩阵和平移矩阵分别通过两个优化函数确定。优化函数也称代价函数或目标函数。为了区分描述,本实施例将用于确定旋转矩阵的优化函数称为第一优化函数,将用于确定平移矩阵的优化函数称为第二优化函数。
在一些实施例中,外参标定设备会根据至少一个平面组和第一优化函数,确定第二标定参数中的旋转矩阵,该旋转矩阵使得第一优化函数的取值为最小值。
第一优化函数用于根据初始旋转矩阵和至少一个平面组确定第一平面和第二平面之间的法向量夹角。第一优化函数的输入参数包括初始旋转矩阵和至少一个平面组,第一优化函数的取值用于表示平面组中第一平面和第二平面之间的法向量夹角的大小。
例如,第一优化函数的表达式如下所示。
f
1=min(1-R
LT*(A,B,C)*(a,b,c))||min(1-R
LT*((A,B,C)))
其中,f
1表示第一优化函数。f
1的含义为两个匹配平面之间的法向量夹角最小。符号“||”的含义是或者。(1-R
LT*(A,B,C)*(a,b,c))和(1+R
LT*((A,B,C)))均表示平面组中的第一平面和第二平面之间的法向量夹角,具体是指通过(A,B,C)表示的第二平面和通过(a,b,c)表示的第一平面之间的法向量夹角。
如何利用第一优化函数确定旋转矩阵包括多种方式。在一种可能的实现中,第二标定参数中的旋转矩阵是在第一优化函数中的初始旋转矩阵的基础上调整得到的。例如,确定第一优化函数中的初始旋转矩阵;将初始旋转矩阵和至少一个平面组的数据分别带入第一优化函数,确定第一优化函数的取值。在此过程中,对第一优化函数中的初始旋转矩阵进行调整。当第一优化函数的取值达到最小值时,确定第一优化函数中的初始旋转矩阵,作为第二标定参数中的旋转矩阵。
本实施例中,通过构造第一优化函数,利用多次标定数据和第一优化函数,使用优化方法自动地求取旋转矩阵,一方面,旋转矩阵的解算过程能够由外参标定设备自动化完成,而无需人工干预,从而提升标定效率,也避免人工干预带来的误差。另一方面,可以通过多次标定数据,自动地求取旋转矩阵,降低单次标定带来的误差。
在一些实施例中,外参标定设备根据至少一个平面组和第二优化函数,确定平移矩阵,平移矩阵使得第二优化函数的取值为最小值。
第二优化函数用于根据初始平移矩阵和至少一个平面组确定第一平面和第二平面之间的距离。第二优化函数的输入参数包括初始平移矩阵和至少一个平面组,第二优化函数的取值用于表示平面组中第一平面和第二平面之间的距离的大小。
例如,第二优化函数的表达式如下所示。
f
2=min((R
LT*P+T
LT-p)*(a,b,c))
其中,f
2表示第二优化函数。f
2的含义为两个匹配平面之间的距离最小。R
LT表示通过第一优化函数确定的旋转矩阵。T
LT表示初始平移矩阵。(R
LT*P+T
LT-p)*(a,b,c) 表示平面组中的第一平面和第二平面之间的距离,具体是指通过(A,B,C)表示的第二平面和通过(a,b,c)表示的第一平面之间的距离。当f
2的取值接近0时,第一平面和第二平面重合。P表示第一平面上的点。p表示第二平面上的点。
如何利用第二优化函数确定平移矩阵包括多种方式。在一种可能的实现中,第二标定参数中的平移矩阵是在第二优化函数中的初始平移矩阵的基础上调整得到的。例如,确定第二优化函数中的初始平移矩阵;将初始平移矩阵和至少一个平面组的数据分别带入第二优化函数,确定第二优化函数的取值。在此过程中,对第二优化函数中的初始平移矩阵进行调整。当第二优化函数的取值达到最小值时,确定第二优化函数中的初始平移矩阵,作为第二标定参数中的平移矩阵。
本实施例中,通过构造第二优化函数,利用多次标定数据和第二优化函数,使用优化方法自动地求取平移矩阵,一方面,平移矩阵的解算过程能够由外参标定设备自动化完成,而无需人工干预,从而提升标定效率,也避免人工干预带来的误差。另一方面,可以通过多次标定数据,自动地求取平移矩阵,降低单次标定带来的误差。
在一些实施例中,旋转矩阵和平移矩阵是分步求解得到的。具体地,先根据至少一个平面组确定旋转矩阵;然后,根据已确定的旋转矩阵和至少一个平面组,确定平移矩阵。
如何利用已确定的旋转矩阵确定平移矩阵包括多种方式。在一种可能的实现中,外参标定设备使用已确定的旋转矩阵和初始平移矩阵,对第一平面上的点进行旋转变换和平移变换,得到该点的投影点;外参标定设备根据至少一个平面组,确定使得投影点和第二平面之间的距离最小的初始平移矩阵,作为平移矩阵。
可选地,利用已确定的旋转矩阵确定平移矩阵通过以上介绍的优化函数实现。例如,第二优化函数的取值是第一平面上的点的投影点和第二平面之间的距离。第二优化函数的输入参数包括旋转矩阵。在通过第一优化函数确定旋转矩阵后,将通过第一优化函数确定的旋转矩阵和初始平移矩阵带入至第二优化函数中。在通过第二优化函数进行运算的过程中,会在第一平面上取一点P;通过第一优化函数确定的旋转矩阵对点P进行旋转变换,通过初始平移矩阵,对点P进行平移变换,得到点P的投影点P’。计算投影点P’和第二平面之间的距离。当投影点P’和第二平面之间的距离的取值达到最小值时,确定第二优化函数中的初始旋转矩阵,作为第二标定参数中的旋转矩阵。
通过利用已确定的旋转矩阵确定平移矩阵,达到的效果包括:考虑到即使第一平面和第二平面之间的法向量夹角最小,也可能出现第一平面和第二平面并非完全平行,而是第一平面和第二平面之间相交的情况,导致难以直接计算出第一平面和第二平面之间的距离,进而导致难以根据平面之间的距离确定平移矩阵。而通过上述方式,将两个面之间的距离计算转换为点和平面之间的距离计算,由于第一平面和第二平面平行或非平行的情况下,投影点和第二平面之间的距离都是容易求解的,从而保证确定平移矩阵的方法的应用范围更广泛,提升了实用性。
其中,如何确定初始旋转矩阵和初始平移矩阵包括多种方式。在一种可能的实现中,对于一个平面组,获取第一平面上的第一点和第二平面上的第二点,根据第一点和第二点,通过矩阵分解的方式确定初始旋转矩阵和初始平移矩阵。可选地,第一点是第一平面上的任意一个点,第二点是第二平面上的任意一个点。本实施例中,并不要求第一点和第二点是同名点。可选地,第一点是第一平面的中心点。第二点是第二平面的中心点。
例如,第一设备是GNSS/IMU设备,第二设备为激光雷达,对于平面组i,取GNSS/IMU设备的坐标系下的平面上的一点p与对应的激光点云中平面内一点P,通过以下方程(5),通过矩阵分解求得初始R
LT与初始T
LT。其中,初始R
LT是对初始旋转矩阵的举例说明,初始T
LT是对初始平移矩阵的举例说明。
p*R
LT+T
LT=P;方程(5)
S312、外参标定设备根据第一标定参数和第二标定参数,获取第二设备与第一设备之间的外参。
本实施例中,由于通过测量设备分别测量了第一设备和标定平面,通过第二设备测量了标定平面,测量设备的坐标系可以充当第一设备的坐标系和第二设备的坐标系之间的中继。根据步骤S307得到的第一标定参数和步骤S311得到的第二标定参数,能够确定第二设备与第一设备之间的外参。其中,第二设备与第一设备之间的外参包括第二设备与第一设备之间的旋转矩阵以及第二设备与第一设备之间的平移矩阵。在一种可能的实现中,联合方程(1)和方程(4),得到以下方程(6)。
方程(6)的含义是C
T中任意一点p
T分别经过R
LT和R
TI进行旋转变换,并分别经过T
LT和T
TI进行平移变换后,能够得到C
I中的同名点p
I。在方程(6)中,p
L表示激光雷达的坐标系下的一点。R
LT表示全站仪与激光雷达之间的旋转矩阵。T
LT表示全站仪与激光雷达之间的旋转矩阵。R
TI表示从全站仪至GNSS/IMU设备的旋转矩阵。T
TI表示从全站仪至GNSS/IMU设备的平移矩阵。p
I表示GNSS/IMU设备的坐标系中的点。C
T表示全站仪的坐标系,C
I表示GNSS/IMU设备的坐标系。C
L表示激光雷达的坐标系。
在一些实施例中,在获得第二设备与第一设备之间的外参后,外参标定设备根据第一设备在世界坐标系下的位置和姿态、第二设备与第一设备之间的外参,获取第三标定参数,该第三标定参数用于表示第二设备与世界坐标系之间的坐标系转换关系。该第三标定参数包括第二设备的坐标系与世界坐标系之间的旋转矩阵以及第二设备的坐标系与世界坐标系之间的平移矩阵。
例如,第一设备是GNSS/IMU设备,第二设备为激光雷达,在GNSS/IMU设备工作过程中,能够获取GNSS/IMU设备的坐标原点在世界坐标系下的绝对位置和姿态。基于方程(6),通过以下方程(7)确定激光雷达与世界坐标系之间的坐标系转换关系。
方程(7)的含义是,C
L中任意一点p
L经过R
IW旋转变换并经过T
IW平移变换后,能够得到p
L在C
W中的同名点p
W。C
L表示激光雷达的坐标系,C
W表示世界坐标系。在方程(7)中,p
L表示激光雷达的坐标系C
L下的一点,T
IW表示GNSS/IMU设备的坐标原点在世界坐标系下的位置,R
IW表示GNSS/IMU设备在世界坐标系的姿态。p
W表示世界坐标系中 的点。
应理解,本实施例对S307、S308和S309这三个步骤之间的时序不做限定。在一些实施例中,S307、S308和S309顺序执行。例如,先执行S307,再执行S308,再执行S309;又如,先执行S308,再执行S309,再执行S307;又如,先执行S308,再执行S307,再执行S309。在另一些实施例中,S307、S308和S309中的至少两项并行执行,即,同时执行S307、S308和S309中的至少两项。
应理解,本实施例对S301与S303的时序不做限定。在一些实施例中,S301与S303可以顺序执行。例如,可以先执行S301,再执行S303;也可以先执行S303,再执行S301。在另一些实施例中,S301与S303也可以并行执行,即,可以同时执行S301以及S303。
应理解,本实施例对S305与S303的时序不做限定。在一些实施例中,S305与S303可以顺序执行。例如,可以先执行S305,再执行S303;也可以先执行S303,再执行S305。在另一些实施例中,S305与S303也可以并行执行,即,可以同时执行S305以及S303。
应理解,本实施例仅是以同一个外参标定设备执行上述S307至S312为例进行说明,在一些实施例中,上述S307至S312可以由多台外参标定设备协作执行。
本实施例提供的方法,通过使用测量设备对第一设备进行测量,确定出测量设备与第一设备之间的坐标系转换关系,并通过使用测量设备和第二设备分别至少一个标定平面进行测量,确定出至少一个标定平面在测量设备和第二设备的坐标系下分别映射的至少一个平面组,利用至少一个平面组确定测量设备与第二设备之间的坐标系转换关系。这样,能够利用测量设备的坐标系,作为第一设备的坐标系与第二设备的坐标系之间的中继,找到第一设备与第二设备之间的外参。由于外参是通过确定出的平面组获得的,而不需要从点云数据中提取同名点,从而避免了同名点的提取过程对标定精度的影响,因此提高了标定精度。此外,该方法能够固化为计算机自动化执行的流程,避免了人工计算标定参数会带来的费时费力的问题,因此提高了标定效率。
以下通过方法400,对方法300进行举例说明。在方法400,测量设备为全站仪,标定平面为标定板,第一设备为GNSS/IMU设备,第二设备为激光雷达,外参标定设备为PC。换句话说,方法400描述的方法流程关于PC上如何利用全站仪和激光雷达对标定板的测量数据,确定激光雷达与GNSS/IMU设备之间的外参。
参见附图7,附图7为本申请实施例提供的一种激光雷达的外参标定方法400的流程图。示例性地,方法400包括S401至S404。
S401、全站仪观测标定板上的标志点。
S402、PC将全站仪的观测结果转换至GNSS/IMU设备的坐标系。
S403、激光雷达扫描标定板,得到点云数据。
S404、PC根据全站仪的观测结果和点云数据,进行平面提取与平面拟合。
S405、PC根据拟合的平面解算出外参,从而完成外参标定,将确定的外参保存至外参文件。
以上介绍了本申请实施例的方法300或方法400,以下介绍本申请实施例的外参标定装置,应理解,该外参标定装置具有上述方法300或方法400中外参标定设备的任意功能。
附图8是本申请实施例提供的一种外参标定装置500的结构示意图,如附图8所示,装置500包括:获取模块501,用于执行S307和S312;确定模块502,用于执行S308、S309、S310和S311。
应理解,装置500对应于上述方法实施例中的外参标定设备,装置500中的各模块和上述其他操作和/或功能分别为了实现方法300或方法400中的外参标定设备所实施的各种步骤和方法,具体细节可参见上述方法300或方法400,为了简洁,在此不再赘述。
应理解,装置500在标定外参时,仅以上述各功能模块的划分进行举例说明,实际应用中,可以根据需要而将上述功能分配由不同的功能模块完成,即将装置500的内部结构划分成不同的功能模块,以完成以上描述的全部或者部分功能。另外,上述实施例提供的装置500与上述方法300或方法400属于同一构思,其具体实现过程详见方法300或方法400,这里不再赘述。
与本申请提供的方法实施例以及虚拟装置实施例相对应,本申请实施例还提供了一种外参标定设备,下面对外参标定设备的硬件结构进行介绍。
外参标定设备600对应于上述方法300或方法400中的外参标定设备或PC,外参标定设备600中的各硬件、模块和上述其他操作和/或功能分别为了实现方法实施例中外参标定设备或PC所实施的各种步骤和方法,关于外参标定设备600如何标定外参的详细流程,具体细节可参见上述方法300或方法400,为了简洁,在此不再赘述。其中,方法300或方法400的各步骤通过外参标定设备600处理器中的硬件的集成逻辑电路或者软件形式的指令完成。结合本申请实施例所公开的方法的步骤可以直接体现为硬件处理器执行完成,或者用处理器中的硬件及软件模块组合执行完成。软件模块可以位于随机存储器,闪存、只读存储器,可编程只读存储器或者电可擦写可编程存储器、寄存器等本领域成熟的存储介质中。该存储介质位于存储器,处理器读取存储器中的信息,结合其硬件完成上述方法的步骤,为避免重复,这里不再详细描述。
外参标定设备600对应于上述外参标定装置500,装置500中的每个功能模块采用外参标定设备600的软件实现。换句话说,装置500包括的功能模块为外参标定设备600的处理器读取存储器中存储的程序代码后生成的。
参见附图9,附图9示出了本申请一个示例性实施例提供的外参标定设备600的结构示意图,例如,该外参标定设备600可以是主机、服务器或个人计算机等。该外参标定设备600可以由一般性的总线体系结构来实现。
外参标定设备600包括至少一个处理器601、通信总线602、存储器603以及至少一个通信接口604。
处理器601可以是一个通用中央处理器(central processing unit,CPU)、网络处理器(network processer,NP)、微处理器、或者可以是一个或多个用于实现本申请方案的集成电路,例如,专用集成电路(application-specific integrated circuit,ASIC),可编程逻辑器件(programmable logic device,PLD)或其组合。上述PLD可以是复杂可编程逻辑器件(complex programmable logic device,CPLD),现场可编程逻辑门阵列(field-programmable gate array,FPGA),通用阵列逻辑(generic array logic,GAL)或其任意组合。
通信总线602用于在上述组件之间传送信息。通信总线602可以分为地址总线、数据总 线、控制总线等。为便于表示,附图9中仅用一条粗线表示,但并不表示仅有一根总线或一种类型的总线。
存储器603可以是只读存储器(read-only memory,ROM)或可存储静态信息和指令的其它类型的静态存储设备,也可以是随机存取存储器(random access memory,RAM)或者可存储信息和指令的其它类型的动态存储设备,也可以是电可擦可编程只读存储器(electrically erasable programmable read-only Memory,EEPROM)、只读光盘(compact disc read-only memory,CD-ROM)或其它光盘存储、光碟存储(包括压缩光碟、激光碟、光碟、数字通用光碟、蓝光光碟等)、磁盘存储介质或者其它磁存储设备,或者是能够用于携带或存储具有指令或数据结构形式的期望的程序代码并能够由计算机存取的任何其它介质,但不限于此。存储器603可以是独立存在,并通过通信总线602与处理器601相连接。存储器603也可以和处理器601集成在一起。
通信接口604使用任何收发器一类的装置,用于与其它设备或通信网络通信。通信接口604包括有线通信接口,还可以包括无线通信接口。其中,有线通信接口例如可以为以太网接口。以太网接口可以是光接口,电接口或其组合。无线通信接口可以为无线局域网(wireless local area networks,WLAN)接口,蜂窝网络通信接口或其组合等。
在具体实现中,作为一种实施例,处理器601可以包括一个或多个CPU,如附图9中所示的CPU0和CPU1。
在具体实现中,作为一种实施例,外参标定设备600可以包括多个处理器,如附图9中所示的处理器601和处理器605。这些处理器中的每一个可以是一个单核处理器(single-CPU),也可以是一个多核处理器(multi-CPU)。这里的处理器可以指一个或多个设备、电路、和/或用于处理数据(如计算机程序指令)的处理核。
在具体实现中,作为一种实施例,外参标定设备600还可以包括输出设备和输入设备。输出设备和处理器601通信,可以以多种方式来显示信息。例如,输出设备可以是液晶显示器(liquid crystal display,LCD)、发光二级管(light emitting diode,LED)显示设备、阴极射线管(cathode ray tube,CRT)显示设备或投影仪(projector)等。输入设备和处理器601通信,可以以多种方式接收用户的输入。例如,输入设备可以是鼠标、键盘、触摸屏设备或传感设备等。
在一些实施例中,存储器603用于存储执行本申请方案的程序代码610,处理器601可以执行存储器603中存储的程序代码610。也即是,外参标定设备600可以通过处理器601以及存储器603中的程序代码610,来实现方法实施例提供的外参标定方法。
本申请实施例的外参标定设备600可对应于上述各个方法实施例中的外参标定设备,并且,该外参标定设备600中的处理器601、通信接口604等可以实现上述各个方法实施例中的外参标定设备所具有的功能和/或所实施的各种步骤和方法。为了简洁,在此不再赘述。
应理解,装置500中的获取模块501、确定模块502相当于外参标定设备600中的处理器601或处理器605。
应理解,上述各种产品形态的外参标定设备,分别具有上述方法实施例中外参标定设备的任意功能,此处不再赘述。
本领域普通技术人员可以意识到,结合本文中所公开的实施例中描述的各方法步骤和单 元,能够以电子硬件、计算机软件或者二者的结合来实现,为了清楚地说明硬件和软件的可互换性,在上述说明中已经按照功能一般性地描述了各实施例的步骤及组成。这些功能究竟以硬件还是软件方式来执行,取决于技术方案的特定应用和设计约束条件。本领域普通技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能,但是这种实现不应认为超出本申请的范围。
所属领域的技术人员可以清楚地了解到,为了描述的方便和简洁,上述描述的***、装置和模块的具体工作过程,可以参见前述方法实施例中的对应过程,在此不再赘述。
在本申请所提供的几个实施例中,应该理解到,所揭露的***、装置和方法,可以通过其它的方式实现。例如,以上所描述的装置实施例仅仅是示意性的,例如,该模块的划分,仅仅为一种逻辑功能划分,实际实现时可以有另外的划分方式,例如多个模块或组件可以结合或者可以集成到另一个***,或一些特征可以忽略,或不执行。另外,所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口、装置或模块的间接耦合或通信连接,也可以是电的,机械的或其它的形式连接。
该作为分离部件说明的模块可以是或者也可以不是物理上分开的,作为模块显示的部件可以是或者也可以不是物理模块,即可以位于一个地方,或者也可以分布到多个网络模块上。可以根据实际的需要选择其中的部分或者全部模块来实现本申请实施例方案的目的。
另外,在本申请各个实施例中的各功能模块可以集成在一个处理模块中,也可以是各个模块单独物理存在,也可以是两个或两个以上模块集成在一个模块中。上述集成的模块既可以采用硬件的形式实现,也可以采用软件功能模块的形式实现。
该集成的模块如果以软件功能模块的形式实现并作为独立的产品销售或使用时,可以存储在一个计算机可读存储介质中。基于这样的理解,本申请的技术方案本质上或者说对现有技术做出贡献的部分,或者该技术方案的全部或部分可以以软件产品的形式体现出来,该计算机软件产品存储在一个存储介质中,包括若干指令用以使得一台计算机设备(可以是个人计算机,服务器,或者网络设备等)执行本申请各个实施例中方法的全部或部分步骤。而前述的存储介质包括:U盘、移动硬盘、只读存储器(read-only memory,ROM)、随机存取存储器(random access memory,RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
本申请中术语“第一”“第二”等字样用于对作用和功能基本相同的相同项或相似项进行区分,应理解,“第一”、“第二”之间不具有逻辑或时序上的依赖关系,也不对数量和执行顺序进行限定。还应理解,尽管以下描述使用术语第一、第二等来描述各种元素,但这些元素不应受术语的限制。这些术语只是用于将一元素与另一元素区别分开。例如,在不脱离各种所述示例的范围的情况下,第一标定参数可以被称为第二标定参数,并且类似地,第二标定参数可以被称为第一标定参数。第一标定参数和第二标定参数都可以是标定参数,并且在某些情况下,可以是单独且不同的标定参数。
本申请中术语“至少一个”的含义是指一个或多个,本申请中术语“多个”的含义是指两个或两个以上,例如,多个标定平面是指两个或两个以上的标定平面。
还应理解,术语“如果”可被解释为意指“当...时”(“when”或“upon”)或“响应于确定”或“响应于检测到”。类似地,根据上下文,短语“如果确定...”或“如果检测到[所陈述的条件或事件]”可被解释为意指“在确定...时”或“响应于确定...”或“在检测到[所陈述的条件或事件]时”或“响应于检测到[所陈述的条件或事件]”。
以上描述,仅为本申请的具体实施方式,但本申请的保护范围并不局限于此,任何熟悉本技术领域的技术人员在本申请揭露的技术范围内,可轻易想到各种等效的修改或替换,这些修改或替换都应涵盖在本申请的保护范围之内。因此,本申请的保护范围应以权利要求的保护范围为准。
在上述实施例中,可以全部或部分地通过软件、硬件、固件或者其任意组合来实现。当使用软件实现时,可以全部或部分地以计算机程序产品的形式实现。该计算机程序产品包括一个或多个计算机程序指令。在计算机上加载和执行该计算机程序指令时,全部或部分地产生按照本申请实施例中的流程或功能。该计算机可以是通用计算机、专用计算机、计算机网络、或者其他可编程装置。该计算机指令可以存储在计算机可读存储介质中,或者从一个计算机可读存储介质向另一个计算机可读存储介质传输,例如,该计算机程序指令可以从一个网站站点、计算机、服务器或数据中心通过有线或无线方式向另一个网站站点、计算机、服务器或数据中心进行传输。该计算机可读存储介质可以是计算机能够存取的任何可用介质或者是包含一个或多个可用介质集成的服务器、数据中心等数据存储设备。该可用介质可以是磁性介质(例如软盘、硬盘、磁带)、光介质(例如,数字视频光盘(digital video disc,DVD)、或者半导体介质(例如固态硬盘)等。
本领域普通技术人员可以理解实现上述实施例的全部或部分步骤可以通过硬件来完成,也可以通过程序来指令相关的硬件完成,该程序可以存储于一种计算机可读存储介质中,上述提到的存储介质可以是只读存储器,磁盘或光盘等。
以上描述仅为本申请的可选实施例,并不用以限制本申请,凡在本申请的精神和原则之内,所作的任何修改、等同替换、改进等,均应包含在本申请的保护范围之内。
Claims (20)
- 一种外参标定方法,其特征在于,所述方法包括:根据测量设备对第一设备的测量数据,获取第一标定参数,所述第一标定参数用于表示所述测量设备与所述第一设备之间的坐标系转换关系;根据所述测量设备对至少一个标定平面的测量数据,确定所述至少一个标定平面在所述测量设备的坐标系下映射的至少一个第一平面;根据第二设备对所述至少一个标定平面的测量数据,确定所述至少一个标定平面在所述第二设备的坐标系下映射的至少一个第二平面;根据所述至少一个第一平面和所述至少一个第二平面,确定至少一个平面组,所述平面组包括第一平面和第二平面,所述平面组中的第一平面与第二平面对应;根据所述至少一个平面组,确定第二标定参数,所述第二标定参数用于表示所述测量设备与所述第二设备之间的坐标系转换关系;根据所述第一标定参数和所述第二标定参数,获取所述第二设备与所述第一设备之间的外参。
- 根据权利要求1所述的方法,其特征在于,所述根据所述至少一个平面组,确定第二标定参数,包括:根据所述至少一个平面组,所述平面组中的第一平面和第二平面满足匹配条件,确定第二标定参数。
- 根据权利要求2所述的方法,其特征在于,所述平面组中的第一平面和第二平面满足匹配条件,包括:所述平面组中的第一平面和第二平面之间的法向量夹角最小。
- 根据权利要求3所述的方法,其特征在于,所述第二标定参数包括旋转矩阵,所述根据所述至少一个平面组,所述平面组中的第一平面和第二平面之间的法向量夹角最小,确定第二标定参数,包括:根据所述至少一个平面组和第一优化函数,确定所述旋转矩阵,所述旋转矩阵使得所述第一优化函数的取值为最小值。
- 根据权利要求1-4任一项所述的方法,其特征在于,所述平面组中的第一平面和第二平面满足匹配条件,包括:所述平面组中的第一平面和第二平面之间的距离最小。
- 根据权利要求5所述的方法,其特征在于,所述第二标定参数包括平移矩阵,所述根据所述至少一个平面组,所述平面组中的第一平面和第二平面之间的距离最小,确定第二标定参数,包括:根据所述至少一个平面组和第二优化函数,确定所述平移矩阵,所述平移矩阵使得所述第二优化函数的取值为最小值。
- 根据权利要求1至6中任一项所述的方法,其特征在于,所述第二标定参数包括平移矩阵,所述根据所述至少一个平面组,确定第二标定参数,包括:使用所述旋转矩阵和初始平移矩阵,对第一平面上的点进行旋转变换和平移变换,得到所述点的投影点;根据所述至少一个平面组,确定使得所述投影点和所述第二平面之间的距离最小的初始平移矩阵,作为所述平移矩阵。
- 根据权利要求1所述的方法,其特征在于,所述根据测量设备对第一设备的测量数据,获取第一标定参数,包括:根据所述第一设备上的标志点在所述第一设备的坐标系下的坐标值和所述测量设备测量得到的所述标志点在所述测量设备的坐标系下的坐标值,获取所述第一标定参数。
- 根据权利要求1所述的方法,其特征在于,所述测量设备为全站仪、激光扫描仪或摄影测量***,所述标定平面为标定板或墙,所述第一设备为惯导设备、车辆或第一激光雷达,所述第二设备为第二激光雷达、毫米波或相机。
- 一种外参标定装置,其特征在于,所述装置包括:获取模块,用于根据测量设备对第一设备的测量数据,获取第一标定参数,所述第一标定参数用于表示所述测量设备与所述第一设备之间的坐标系转换关系;确定模块,用于根据所述测量设备对至少一个标定平面的测量数据,确定所述至少一个标定平面在所述测量设备的坐标系下映射的至少一个第一平面;确定模块,用于根据第二设备对所述至少一个标定平面的测量数据,确定所述至少一个标定平面在所述第二设备的坐标系下映射的至少一个第二平面;确定模块,用于根据所述至少一个第一平面和所述至少一个第二平面,确定至少一个平面组,所述平面组包括第一平面和第二平面,所述平面组中的第一平面与第二平面对应;确定模块,用于根据所述至少一个平面组,确定第二标定参数,所述第二标定参数用于表示所述测量设备与所述第二设备之间的坐标系转换关系;所述获取模块,还用于根据所述第一标定参数和所述第二标定参数,获取所述第二设备与所述第一设备之间的外参。
- 根据权利要求10所述的装置,其特征在于,所述确定模块,用于根据所述至少一个平面组,所述平面组中的第一平面和第二平面满足匹配条件,确定第二标定参数。
- 根据权利要求11所述的装置,其特征在于,所述平面组中的第一平面和第二平面满足匹配条件,包括:所述平面组中的第一平面和第二平面之间的法向量夹角最小。
- 根据权利要求12所述的装置,其特征在于,所述第二标定参数包括旋转矩阵,所述确定模块,用于根据所述至少一个平面组和第一优化函数,确定所述旋转矩阵,所述旋转矩阵使得所述第一优化函数的取值为最小值。
- 根据权利要求10-13任一项所述的装置,其特征在于,所述平面组中的第一平面和第二平面满足匹配条件,包括:所述平面组中的第一平面和第二平面之间的距离最小。
- 根据权利要求14所述的装置,其特征在于,所述第二标定参数包括平移矩阵,所述确定模块,用于根据所述至少一个平面组和第二优化函数,确定所述平移矩阵,所述平移矩阵使得所述第二优化函数的取值为最小值。
- 根据权利要求10至15中任一项所述的装置,其特征在于,所述第二标定参数包括平移矩阵,所述确定模块,用于使用所述旋转矩阵和初始平移矩阵,对第一平面上的点进行旋转变换和平移变换,得到所述点的投影点;根据所述至少一个平面组,确定使得所述投影点和所述第二平面之间的距离最小的初始平移矩阵,作为所述平移矩阵。
- 根据权利要求10所述的装置,其特征在于,所述获取模块,用于根据所述第一设备上的标志点在所述第一设备的坐标系下的坐标值和所述测量设备测量得到的所述标志点在所述测量设备的坐标系下的坐标值,获取所述第一标定参数。
- 根据权利要求10所述的装置,其特征在于,所述测量设备为全站仪、激光扫描仪或摄影测量***,所述标定平面为标定板或墙,所述第一设备为惯导设备、车辆或第一激光雷达,所述第二设备为第二激光雷达、毫米波或相机。
- 一种外参标定设备,其特征在于,所述外参标定设备包括处理器,所述处理器用于执行指令,使得所述外参标定设备执行如权利要求1至权利要求9中任一项所述的方法。
- 一种计算机可读存储介质,其特征在于,所述存储介质中存储有至少一条指令,所述指令由处理器读取以使外参标定设备执行如权利要求1至权利要求9中任一项所述的方法。
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CN118068358A (zh) * | 2024-04-19 | 2024-05-24 | 临沂大学 | 一种激光雷达与惯性测量单元外参标定的无奇异方法 |
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