CN115437385B - Laser positioning method, device, equipment and medium of mobile robot - Google Patents
Laser positioning method, device, equipment and medium of mobile robot Download PDFInfo
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Abstract
The embodiment of the invention discloses a laser positioning method, a device, equipment and a medium of a mobile robot. The method comprises the following steps: determining laser point cloud data acquired by a mobile robot at a target position in a target area; determining whether a reflector positioning instruction is received at a target position; if yes, determining pose information of the mobile robot at the target position according to positioning reflector laser point cloud data in the laser point cloud data and predetermined reflector calibration information; otherwise, determining pose information of the mobile robot at the target position according to the laser point cloud data and a laser point cloud map of the target area, which is constructed in advance. According to the technical scheme, the laser positioning precision can be effectively improved for scenes with high positioning precision requirements, a laser point cloud matching algorithm is used for scenes with low positioning precision requirements, a reflector is not required to be paved on a large scale, the calculation cost and the economic cost are reduced, the laser positioning efficiency is improved, and therefore the actual requirements are better met.
Description
Technical Field
The present invention relates to the field of laser positioning technologies, and in particular, to a laser positioning method, apparatus, device, and medium for a mobile robot.
Background
The high-precision laser patterning positioning technology is one of the core technologies of mobile robots. The laser composition refers to a process that a mobile robot starts from an unknown place of an unknown environment, the position and the gesture of the mobile robot relative to a starting point are determined through laser point clouds obtained through repeated scanning in the motion process, and a 3D laser map is constructed according to the position and the gesture of the mobile robot relative to the starting point and the scanned laser point clouds. Laser positioning refers to the process of determining the accurate position and posture of a mobile robot in a laser map from a known place in a known environment. Only when the mobile robot knows the position of the mobile robot definitely, the upper control module (such as navigation, planning and the like) can send corresponding instructions to the mobile robot so as to complete related services. Among them, positioning accuracy is one of the most core and key indexes.
In practical applications, the positioning accuracy requirements may be different in different scenarios. For scenes with low positioning precision requirements, general precision positioning can be performed; for scenes with high positioning accuracy requirements, high-accuracy positioning is required. For example, in a warehouse and transport scene, the stacking of goods requires to achieve the precision of +/-2 cm, the positioning precision of the robot requires to reach within +/-1 cm, and the positioning precision in the scene is higher, so that high-precision positioning is required. Therefore, how to automatically select high-precision positioning or general-precision positioning according to the requirements of positioning precision in application scenes so as to adapt to the requirements of laser positioning precision in different scenes, and how to improve the laser positioning precision of a mobile robot in the high-precision positioning scenes while saving cost is a problem to be solved in the current laser positioning technology.
The main scheme at present is that the traditional laser synchronous positioning and map construction (laser SLAM) technology is used for laser composition and positioning. However, due to limitations of factors such as sensor performance, laser positioning algorithm, laser map precision, robot operation scene and the like, the traditional laser SLAM method causes low laser positioning precision, and is difficult to meet actual demands in certain scenes. For the above problems, a reflector is generally introduced for auxiliary positioning. The reflecting plate is a rectangular article made of specific materials and can be fixed on a wall, and the length and the width of the reflecting plate are generally within 50 cm. However, for larger area scenes, a large number of reflectors need to be laid and maintained, resulting in higher positioning costs. In addition, because of the limitation of the laser ranging range and the laser scanning angle, enough reflector point clouds cannot be scanned in some places for calculation, so that the positioning algorithm is abnormal and the positioning accuracy is low.
Disclosure of Invention
The invention provides a laser positioning method, device, equipment and medium for a mobile robot, which can effectively improve the laser positioning precision, reduce the calculation cost and the economic cost and improve the laser positioning efficiency, thereby better meeting the actual demands.
According to an aspect of the present invention, there is provided a laser positioning method of a mobile robot, the method comprising:
determining laser point cloud data acquired by a mobile robot at a target position in a target area;
determining whether a reflector positioning instruction is received at the target position;
if yes, determining pose information of the mobile robot at the target position according to positioning reflector laser point cloud data in the laser point cloud data and predetermined reflector calibration information;
otherwise, determining pose information of the mobile robot at the target position according to the laser point cloud data and a pre-constructed laser point cloud map of the target area.
According to another aspect of the present invention, there is provided a laser positioning device of a mobile robot, including:
the laser point cloud data determining module is used for determining laser point cloud data acquired by the mobile robot at a target position in a target area;
the reflector positioning instruction receiving and determining module is used for determining whether a reflector positioning instruction is received at the target position;
the first pose information determining module is used for determining pose information of the mobile robot at the target position according to the positioning reflector laser point cloud data in the laser point cloud data and the predetermined reflector calibration information if yes;
And the second pose information determining module is used for determining pose information of the mobile robot at the target position according to the laser point cloud data and a pre-constructed laser point cloud map of the target area if not.
According to another aspect of the present invention, there is provided a laser positioning electronic device of a mobile robot, the electronic device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the laser positioning method of the mobile robot according to any one of the embodiments of the present invention.
According to another aspect of the present invention, there is provided a computer readable storage medium storing computer instructions for causing a processor to execute the laser positioning method of the mobile robot according to any embodiment of the present invention.
According to the technical scheme, laser point cloud data acquired by a mobile robot at a target position in a target area are determined; determining whether a reflector positioning instruction is received at a target position; if yes, determining pose information of the mobile robot at the target position according to positioning reflector laser point cloud data in the laser point cloud data and predetermined reflector calibration information; otherwise, determining pose information of the mobile robot at the target position according to the laser point cloud data and a laser point cloud map of the target area, which is constructed in advance. According to the technical scheme, the laser positioning precision can be effectively improved for scenes with high positioning precision requirements, a laser point cloud matching algorithm is used for scenes with low positioning precision requirements, a reflector is not required to be paved on a large scale, the calculation cost and the economic cost are reduced, the laser positioning efficiency is improved, and therefore the actual requirements are better met.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a laser positioning method of a mobile robot according to a first embodiment of the present invention;
fig. 2 is a flowchart of a laser positioning method of a mobile robot according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of a laser positioning device of a mobile robot according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device for implementing a laser positioning method of a mobile robot according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," "target," and the like in the description and claims of the present invention and in the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
Fig. 1 is a flowchart of a laser positioning method of a mobile robot according to an embodiment of the present invention, where the method may be performed by a laser positioning device of the mobile robot, the laser positioning device of the mobile robot may be implemented in hardware and/or software, and the laser positioning device of the mobile robot may be configured in an electronic device with data processing capability. As shown in fig. 1, the method includes:
s110, determining laser point cloud data acquired by the mobile robot at a target position in a target area.
The target region may be a region waiting for laser positioning. For example, the target area may be a warehouse handling area or the like. The target location may refer to a location in the target area where laser positioning is to be performed. For example, the target location may be a location for picking, identifying, and stacking of goods, etc. The laser point cloud data may refer to point cloud data acquired by scanning an object with a lidar, and may be used to characterize the reflected signal strength of the object. In this embodiment, the laser radar may be mounted at the head position of the mobile robot, and the mobile robot transmits a laser beam to the target position in the target area, so as to receive an echo signal returned from the target position, so as to obtain laser point cloud data at the target position.
S120, determining whether a reflector positioning instruction is received at the target position.
The reflector positioning instruction may be an operation instruction for starting the reflector to perform auxiliary positioning. In this embodiment, it may be determined whether the reflector positioning instruction is received at the target position through various ways. A manager directly issues a reflector positioning instruction corresponding to a target position to a mobile robot through a server according to actual operation scene requirements. When the mobile robot receives the reflector positioning instruction, it may be determined that the reflector positioning instruction is received at the target position. And the other is that the mobile robot scans the number of the reflecting plates around the target position in the target area, and if the number of the scanned reflecting plates is larger than a preset number threshold value, the receiving of the reflecting plate positioning instruction at the target position can be determined. In addition, whether the reflector positioning needs to be started or not can be determined through the map. Specifically, the positioning identification of the reflector can be performed in advance in a certain area on the map, and when the mobile robot enters the area and obtains the positioning identification of the reflector, the mobile robot is considered to receive the positioning instruction of the reflector. When receiving the reflector positioning instruction, the reflector needs to be started for auxiliary positioning.
And S130, if so, determining pose information of the mobile robot at the target position according to the positioning reflector laser point cloud data in the laser point cloud data and the predetermined reflector calibration information.
The positioning reflector laser point cloud data may refer to point cloud data representing reflector positioning information in the laser point cloud data. The reflector calibration information can be used for parameter calibration of the reflector. For example, the reflector calibration information may include the length, width, corner coordinates, rotation angle, etc. of the reflector. The pose information may be used to characterize the position information of the mobile robot. For example, the pose information may include position information, orientation information, angle information, and the like.
In this embodiment, if it is determined that the reflector positioning instruction is received at the target position, it indicates that the reflector positioning needs to be started, and at this time, pose information of the mobile robot at the target position can be determined according to positioning reflector laser point cloud data in the laser point cloud data and predetermined reflector calibration information, so as to achieve accurate positioning of the target position where the mobile robot is located. By way of example, the reflector characteristic information can be extracted according to the locating reflector laser point cloud data, the extracted reflector characteristic information is matched with reflector calibration information which is closer to the locating reflector laser point cloud data in the predetermined reflector calibration information, and then pose information of the mobile robot at the target position is determined according to the matching result. Specifically, if the matching is successful, determining pose information of the mobile robot at the target position according to the matched reflector calibration information; if the matching fails, the pose information of the mobile robot at the target position is determined by using a traditional laser SLAM method.
And S140, otherwise, determining pose information of the mobile robot at the target position according to the laser point cloud data and a laser point cloud map of the pre-constructed target area.
The laser point cloud map may refer to a three-dimensional laser map distributed in a point cloud form obtained through a laser patterning process. In this embodiment, if it is determined that the reflector positioning instruction is not received at the target position, it indicates that the reflector positioning is not required to be started, and at this time, pose information of the mobile robot at the target position may be determined directly by using a conventional laser SLAM method. In addition, when the contour matching of the positioning reflector and the target reflector is unsuccessful, in order not to influence the normal operation of the mobile robot, the pose information of the mobile robot at the target position is determined by adopting a traditional laser SLAM positioning method.
According to the technical scheme, laser point cloud data acquired by a mobile robot at a target position in a target area are determined; determining whether a reflector positioning instruction is received at a target position; if yes, determining pose information of the mobile robot at the target position according to positioning reflector laser point cloud data in the laser point cloud data and predetermined reflector calibration information; otherwise, determining pose information of the mobile robot at the target position according to the laser point cloud data and a laser point cloud map of the target area, which is constructed in advance. According to the technical scheme, under the condition that the reflector positioning instruction is received, pose information of the mobile robot at the target position can be determined based on the predetermined reflector calibration information; under the condition that a reflector positioning instruction is not received, pose information of the mobile robot at the target position is determined based on a laser point cloud map of a pre-constructed target area, high-precision positioning or general precision positioning can be automatically selected according to the requirements on positioning precision in an application scene, and higher positioning precision is provided for a downstream navigation, planning and control module under the scene with higher positioning precision requirements, such as goods taking, stacking and card entering; under the scene that is not high to the positioning accuracy requirement, like the removal in-process, provide more stable, more general, more economic location, more fit for the demand when mobile robot accomplishes relevant business, therefore effectively promoted laser positioning accuracy, reduced calculation cost and economic cost simultaneously, improved laser positioning efficiency, can adapt to the laser positioning accuracy demand of different scenes to satisfy actual demand better.
Example two
Fig. 2 is a flowchart of a laser positioning method of a mobile robot according to a second embodiment of the present invention, which is optimized based on the above embodiment. The concrete optimization is as follows: before determining the laser point cloud data acquired by the mobile robot at the target position in the target area, the method further comprises: according to sensor data acquired when the mobile robot moves in the target area, constructing a laser point cloud map of the target area; and determining reflector calibration information in the target area according to the calibration reflector laser point cloud data in the sensor data.
As shown in fig. 2, the method of this embodiment specifically includes the following steps:
s210, constructing a laser point cloud map of the target area according to sensor data acquired when the mobile robot moves in the target area.
In this embodiment, first, sensor data of a mobile robot moving in a target area is recorded in real time, wherein the sensor data includes laser point cloud data. And then, pose information of the mobile robot when moving in the target area is obtained by using a laser SLAM algorithm (such as ICP, GICP, LOAM, etc.), so that a laser point cloud map of the target area is constructed by using the obtained pose information, and the constructed laser point cloud map is stored.
S220, determining reflector calibration information in the target area according to the calibration reflector laser point cloud data in the sensor data.
The calibration reflector laser point cloud data may refer to point cloud data representing reflector calibration information in the laser point cloud data. Illustratively, first, calibrated reflector laser point cloud data is extracted from sensor data. Specifically, laser point cloud data with the reflection intensity greater than 225 can be extracted from the sensor data and used as calibration reflector laser point cloud data. And then determining the contour information of the reflector by fitting the laser point cloud data of the calibrated reflector. And then using a laser SLAM algorithm (such as ICP, GICP, LOAM and the like) to obtain the reflector pose information according to the laser point cloud data of the calibrated reflector. And determining the reflector calibration information in the target area according to the reflector profile information and the reflector pose information, and storing the reflector calibration information.
S230, determining laser point cloud data acquired by the mobile robot at a target position in the target area.
S240, determining whether a reflector positioning instruction is received at the target position.
S250, if yes, determining pose information of the mobile robot at the target position according to the positioning reflector laser point cloud data in the laser point cloud data and the predetermined reflector calibration information.
And S260, otherwise, determining pose information of the mobile robot at the target position according to the laser point cloud data and a laser point cloud map of the pre-constructed target area.
The specific implementation of S230 to S260 may be described in detail in S110 to S140, and will not be described here again.
According to the technical scheme, before laser point cloud data acquired by a mobile robot at a target position in a target area are determined, a laser point cloud map of the target area is constructed according to sensor data acquired when the mobile robot moves in the target area; and determining reflector calibration information in the target area according to the calibration reflector laser point cloud data in the sensor data. According to the technical scheme, the laser point cloud map of the target area can be constructed according to the sensor data acquired in the actual application scene, and the calibration information of the reflecting plate in the target area is determined, so that the laser positioning accuracy is further improved, meanwhile, the calculation cost and the economic cost are reduced, the laser positioning efficiency is improved, and the actual requirements are better met.
In this embodiment, optionally, determining reflector calibration information in the target area according to the calibration reflector laser point cloud data in the sensor data includes: determining the plane information of the calibration reflector according to the laser point cloud data of the calibration reflector in the sensor data; extracting outline point cloud data of the calibration reflecting plate according to the plane information of the calibration reflecting plate; and determining the calibration information of the reflector according to the outline point cloud data of the calibration reflector and the size information of the reflector.
The calibration reflector plane information may refer to information related to a three-dimensional plane where the reflector for calibration is located. The profile point cloud data of the calibration reflecting plate can be used for representing the profile information of the calibration reflecting plate. The reflector size information may be used to characterize the size of the reflector. For example, the reflector size information may include length information and width information of the reflector.
In this embodiment, after the calibration reflector laser point cloud data is extracted from the sensor data, coordinate transformation and clustering processing are performed on the calibration reflector laser point cloud data. Specifically, if the laser point cloud data of the calibration reflector is recorded as
According to the position and posture information T of the reflector at the current moment, the method is represented by the formula P W ＝T×P m Calibrating laser point cloud data P of reflector m Converted into world coordinate system. Wherein P is W And (5) indicating the laser point cloud data of the calibrated reflector under the world coordinate system. And clustering the laser point cloud data of the calibration reflecting plate under the world coordinate system, so as to determine which calibration reflecting plate laser point cloud data belong to the same reflecting plate.
After coordinate conversion and clustering treatment are carried out on the laser point cloud data of the calibration reflecting plate, the plane information of the calibration reflecting plate can be further determined. Illustratively, assume that the nominal reflector plane is expressed as ax+by+cz+d=0, where A, B, C, D represents the different nominal reflector plane parameters. The nominal reflector plane parameters A, B, C, D can be solved by the following optimization formula:
Wherein argmin represents the value of a variable corresponding to the minimum value of the following expression, and the variable is a constant reflector plane parameter A, B, C, D, (x) i ,y i ,z i ) And (5) representing the coordinates of the laser point cloud data of the ith calibration reflecting plate in the world coordinate system. After the plane parameters A, B, C, D of the calibration reflecting plate are solved through the method, the plane parameters are substituted into the expression of the plane of the calibration reflecting plate, and the plane information of the calibration reflecting plate can be obtained.
After the plane information of the calibration reflecting plate is determined, the outline point cloud data of the calibration reflecting plate can be extracted according to the plane information of the calibration reflecting plate. Optionally, extracting the profile point cloud data of the calibration reflector according to the plane information of the calibration reflector includes: determining projection plane information of the calibration reflector on the target plane; rasterizing the projection plane information of the calibration reflecting plate, and determining the point cloud information of the calibration reflecting plate in the grid; and determining the outline point cloud data of the calibration reflecting plate according to the point cloud information of the calibration reflecting plate in the grid.
Wherein the target plane may be used to indicate to which plane the nominal reflector plane information is projected. Illustratively, the target plane may be a plane selected from the (0, 1) directions. The calibration reflector projection plane information can be used for representing projection plane related information after the calibration reflector plane information is projected to the target plane. The calibration reflector point cloud information can be calibration reflector laser point cloud information in a grid obtained after the calibration reflector projection plane information is rasterized.
Illustratively, the plane in the (0, 1) direction is taken as the target plane, assuming that the normal vector for calibrating the plane information of the reflector is
The normal vector of the target plane is +.>
The rotation angle from the plane of the calibration reflector to the (0, 1) plane can be obtained as follows: />
Meanwhile, the rotation axis can be obtained as follows: />
Wherein P (0), P (1) and P (2) respectively represent a, b and c; q (0), Q (1) and Q (2) represent 0,0 and 1, respectively. Let N respectively x ＝N(0)，N y ＝N(1)，N z N (2), the rotation matrix R can be obtained from the rotation angle and the rotation axis 1 The method comprises the following steps:
the coordinates of the rotating laser point cloud data of the calibrated reflector under the world coordinate system are as follows: p (P) plane ＝R 1 ×P W . And determining the projection plane information of the calibrated reflector on the target plane. It should be noted that, at this time, the projection plane information of the calibration reflector is determined by combining the rotation angle, mainly considering that the paving of the reflector in the actual scene is often angled. Because some wall surfaces are irregular and are not very standard paving modes perpendicular to the ground, the positioning accuracy of the reflecting plate can be further improved by considering the rotation angle.
And then rasterizing the projection plane information of the calibration reflecting plate, and determining the point cloud information of the calibration reflecting plate in the grid. For example, a grid can be constructed with a size of 2cm x 2cm, and for each calibration reflector laser point cloud data, the grid it falls into is calculated by the following formula:
x＝P plane (0)/0.02；y＝P plance (1)/0.02
Wherein, calibrating laser point cloud data P of the reflector plane Falls within the (x, y) grid.
After the point cloud information of the calibration reflecting plate in the grid is determined, the outline point cloud data of the calibration reflecting plate can be further determined according to the point cloud information of the calibration reflecting plate in the grid. Specifically, traversing all grids, and reserving grids with maximum and minimum y for all grids with consistent x coordinates; for all grids with identical y coordinates, the x maximum and minimum grids are reserved. And determining the outline point cloud data of the calibrated reflector according to the point cloud information in each reserved grid.
According to the scheme, through the arrangement, the projection plane information of the calibration reflecting plate is rasterized, and the outline point cloud data of the calibration reflecting plate can be rapidly and accurately determined according to the point cloud information of the calibration reflecting plate in the grid.
After the outline point cloud data of the calibration reflecting plate are extracted, the calibration information of the reflecting plate can be determined according to the outline point cloud data of the calibration reflecting plate and the size information of the reflecting plate. Optionally, determining the calibration information of the reflector according to the calibration contour point cloud data of the reflector and the size information of the reflector includes: determining reflector calibration information according to the calibration reflector profile point cloud data and reflector size information based on the optimization function f 1; the reflector calibration information comprises position information of an upper left corner point of the reflector and calibration rotation matrix information;
Wherein P is i outline Calibrating contour point cloud data, P, of the reflector for the ith 0 ＝R×P，
L and W are the length and width of the reflector, P is the position information of the left upper corner point of the reflector, R is the information of the calibration rotation matrix, and P 0 Projection position information of upper left corner point position information of reflector on target plane, P 1 Is the projection position information of the upper right corner point position information of the reflector on the target plane, P 2 Is the projection position information of the right lower corner point position information of the reflector on the target plane, P 3 The position information of the left lower corner point of the reflector is projected on the target plane.
Wherein the calibration rotation matrix information R can be used for indicating the rotation from the projection plane of the calibration reflector to the pair of calibration reflectorsCorresponding rotation matrix information, rotation matrix R 1 The method can be used for indicating the rotation matrix information corresponding to the rotation from the plane of the calibration reflecting plate to the projection plane of the calibration reflecting plate. Thus, the rotation matrix information R and the rotation matrix R are calibrated 1 Different, in particular R and R 1 Respectively representing two opposite rotational processes.
According to the scheme, through the arrangement, based on the optimization function f1, the reflector calibration information can be rapidly and accurately determined according to the calibration reflector profile point cloud data and the reflector size information, so that a reference standard is provided for subsequent laser positioning.
In this embodiment, optionally, determining pose information of the mobile robot at the target position according to the positioning reflector laser point cloud data in the laser point cloud data and the predetermined reflector calibration information includes: determining positioning reflector plane information according to positioning reflector laser point cloud data; extracting contour point cloud data of the positioning reflector according to plane information of the positioning reflector; matching the outline point cloud data of the positioning reflector with the reflector calibration information to determine target reflector calibration information; and determining pose information of the mobile robot at the target position according to the positioning reflector contour point cloud data, the target reflector upper left corner point position information and the target calibration rotation matrix information in the target reflector calibration information.
The positioning reflector plane information may refer to information related to a three-dimensional plane in which the reflector for positioning is located. The contour point cloud data of the positioning reflector can be used for representing contour information of the positioning reflector. The target reflector calibration information may refer to successfully matched reflector (i.e., target reflector) calibration information. The upper left corner point position information of the target reflector may refer to upper left corner point position information corresponding to the target reflector. The target calibration rotation matrix information may refer to calibration rotation matrix information corresponding to the target reflector.
In this embodiment, the above-mentioned determination process of the plane information of the calibration reflector and the outline point cloud data of the calibration reflector may be referred to, the plane information of the positioning reflector is determined according to the laser point cloud data of the positioning reflector, and then the outline point cloud data of the positioning reflector is extracted according to the plane information of the positioning reflector. The calculation of the grid profile is different because the number of single-frame point cloud scan points is small. For example, among all grids, the grids with x maximum, x minimum, y maximum or y minimum can be reserved, and laser point cloud data in the grids can be extracted to serve as contour point cloud data of the positioning reflector, so that contour information of the positioning reflector can be determined. And searching the stored calibration information of the reflector, searching the calibration reflector closest to the contour point cloud data of the positioning reflector as a candidate calibration reflector, and judging whether the contour point cloud information of the positioning reflector and the candidate calibration reflector can be successfully matched.
Specifically, whether the contour information of the positioning reflector is matched with the contour information of the candidate calibration reflector is judged first, and if the contour information is successfully matched, whether the distance between the contour point cloud data of the positioning reflector and the candidate calibration reflector meets the preset distance threshold condition can be further judged. If the distance is smaller than the preset distance threshold, the positioning reflector profile point cloud data is considered to be successfully matched with the candidate calibration reflectors, the candidate calibration reflectors can be determined to be target reflectors at the moment, and corresponding target reflector calibration information is determined; otherwise, the matching of the contour point cloud data of the positioning reflecting plate and the candidate calibration reflecting plate is considered to be failed, at the moment, the candidate calibration reflecting plate can be tried to be reselected for re-matching, and if the matching is failed for a plurality of times, the pose information of the mobile robot at the target position is determined by using a traditional laser SLAM method. Further, if the number of successful matching is enough, determining pose information of the mobile robot at the target position by using a reflector positioning method; whereas pose information of the mobile robot at the target position is determined using a conventional laser SLAM method.
According to the scheme, through the arrangement, the target reflector calibration information can be rapidly and accurately determined according to the matching result of the positioning reflector profile point cloud data and the reflector calibration information, so that accurate laser positioning can be realized based on the target reflector calibration information.
After the target reflector calibration information is determined, pose information of the mobile robot at the target position can be determined according to the positioning reflector contour point cloud data, the target reflector upper left corner point position information and the target calibration rotation matrix information in the target reflector calibration information. Optionally, determining pose information of the mobile robot at the target position according to the position information of the upper left corner point of the target reflector and the target calibration rotation matrix information in the positioning reflector contour point cloud data and the target reflector calibration information includes: determining the projection position information of the upper left corner of the target reflector on the target plane, the projection position information of the upper right corner of the target, the projection position information of the lower right corner of the target and the projection position information of the lower left corner of the target according to the position information of the corner point of the target reflector in the target reflector calibration information and the target calibration rotation matrix information; based on the optimization function f2, according to the projection position information of the upper left corner of the target reflector on the target plane, the projection position information of the upper right corner of the target, the projection position information of the lower left corner of the target and the contour point cloud data of the positioning reflector, the pose information of the mobile robot at the target position is determined,
Wherein P is i outline The ith positioning reflector profile point cloud data is obtained, T is pose information of the mobile robot at the target position,
projection position information for the upper left corner of the object, +.>
Projection position information for the upper right corner of the object, +.>
Projection position information for the lower right corner of the object, +.>
For projecting position information for the lower left corner of the target, P r R is the angular point position information of the target reflector r And calibrating the rotation matrix information for the target.
According to the scheme, through the arrangement, based on the optimization function f2, pose information of the mobile robot at the target position can be rapidly and accurately determined, and therefore accurate laser positioning is achieved.
Example III
Fig. 3 is a schematic structural diagram of a laser positioning device for a mobile robot according to a third embodiment of the present invention, where the device may execute the laser positioning method for a mobile robot according to any embodiment of the present invention, and the device has functional modules and beneficial effects corresponding to the execution method. As shown in fig. 3, the apparatus includes:
a laser point cloud data determining module 310, configured to determine laser point cloud data acquired by the mobile robot at a target position in a target area;
a reflector positioning instruction receiving determining module 320, configured to determine whether a reflector positioning instruction is received at the target position;
A first pose information determining module 330, configured to determine pose information of the mobile robot at the target position according to the positioning reflector laser point cloud data in the laser point cloud data and predetermined reflector calibration information if yes;
and a second pose information determining module 340, configured to determine pose information of the mobile robot at the target position according to the laser point cloud data and a pre-constructed laser point cloud map of the target area, otherwise.
Optionally, the apparatus further includes:
the laser point cloud map construction module is used for constructing a laser point cloud map of a target area according to sensor data acquired when the mobile robot moves in the target area before determining the laser point cloud data acquired by the mobile robot at the target position in the target area;
and the reflector calibration information determining module is used for determining reflector calibration information in the target area according to the calibrated reflector laser point cloud data in the sensor data.
Optionally, the reflector calibration information determining module includes:
the calibration reflector plane information determining unit is used for determining calibration reflector plane information according to the calibration reflector laser point cloud data in the sensor data;
The calibration reflector profile point cloud data extraction unit is used for extracting calibration reflector profile point cloud data according to the calibration reflector plane information;
and the reflector calibration information determining unit is used for determining the reflector calibration information according to the calibration reflector contour point cloud data and the reflector size information.
Optionally, the calibration reflector profile point cloud data extraction unit is configured to:
determining the projection plane information of the calibration reflector on the target plane;
rasterizing the projection plane information of the calibration reflecting plate, and determining the point cloud information of the calibration reflecting plate in the grid;
and determining the outline point cloud data of the calibrated reflector according to the point cloud information of the calibrated reflector in the grid.
Optionally, the reflector calibration information determining unit is configured to:
determining the reflector calibration information according to the calibration reflector profile point cloud data and the reflector size information based on an optimization function f 1; the reflector calibration information comprises reflector upper left corner point position information and calibration rotation matrix information;
wherein P is i outline Calibrating contour point cloud data, P, of the reflector for the ith 0 ＝R×P，
L and W are the length and width of the reflector, P is the position information of the left upper corner point of the reflector, R is the information of the calibration rotation matrix, and P 0 Projection position information of the upper left corner point position information of the reflector on the target plane is the upper left corner, P 1 Projection position information of the right upper corner point position information of the reflector on the target plane is the right upper corner projection position information, P 2 The projection position information of the right lower corner point position information of the reflector on the target plane is the right lower corner projection position information, P 3 And projecting position information for the left lower corner of the reflector on the target plane. />
Optionally, the first pose information determining module 330 includes:
the positioning reflector plane information determining unit is used for determining positioning reflector plane information according to the positioning reflector laser point cloud data;
the locating reflector profile point cloud data extraction unit is used for extracting locating reflector profile point cloud data according to the locating reflector plane information;
the target reflector calibration information determining unit is used for determining target reflector calibration information according to the contour point cloud data of the positioning reflector and the reflector calibration information;
and the pose information determining unit is used for determining pose information of the mobile robot at the target position according to the contour point cloud data of the positioning reflector, the position information of the left upper corner point of the target reflector in the target reflector calibration information and the target calibration rotation matrix information.
Optionally, the pose information determining unit is configured to:
determining the projection position information of the target reflector at the upper left corner of the target on the target plane, the projection position information of the target upper right corner, the projection position information of the target lower right corner and the projection position information of the target lower left corner according to the position information of the corner point of the target reflector in the target reflector calibration information and the target calibration rotation matrix information;
based on the optimization function f2, according to the projection position information of the upper left corner of the target reflector on the target plane, the projection position information of the upper right corner of the target, the projection position information of the lower left corner of the target and the contour point cloud data of the positioning reflector, the pose information of the mobile robot at the target position is determined,
wherein,,
the ith positioning reflector profile point cloud data is obtained, T is pose information of the mobile robot at the target position, and +.>
Projection position information for the upper left corner of the object, +.>
Projection position information for the upper right corner of the object, +.>
Projection position information for the lower right corner of the object, +.>
For projecting position information for the lower left corner of the target, P r R is the angular point position information of the target reflector r And calibrating the rotation matrix information for the target.
The laser positioning device of the mobile robot provided by the embodiment of the invention can execute the laser positioning method of the mobile robot provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
Example IV
Fig. 4 shows a schematic diagram of the structure of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 4, the electronic device 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as a laser positioning method of a mobile robot.
In some embodiments, the laser positioning method of the mobile robot may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the laser positioning method of the mobile robot described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the laser positioning method of the mobile robot in any other suitable way (e.g. by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (7)
1. A method of laser positioning of a mobile robot, the method comprising:
determining laser point cloud data acquired by a mobile robot at a target position in a target area;
determining whether a reflector positioning instruction is received at the target position;
if yes, determining pose information of the mobile robot at the target position according to positioning reflector laser point cloud data in the laser point cloud data and predetermined reflector calibration information;
Otherwise, determining pose information of the mobile robot at the target position according to the laser point cloud data and a pre-constructed laser point cloud map of the target area;
wherein, before determining laser point cloud data acquired by the mobile robot at a target location in the target area, the method further comprises:
constructing a laser point cloud map of a target area according to sensor data acquired when a mobile robot moves in the target area;
determining reflector calibration information in the target area according to the calibration reflector laser point cloud data in the sensor data;
determining reflector calibration information in the target area according to the calibration reflector laser point cloud data in the sensor data, including:
determining the plane information of the calibration reflector according to the laser point cloud data of the calibration reflector in the sensor data;
extracting outline point cloud data of the calibration reflecting plate according to the plane information of the calibration reflecting plate;
determining the reflector calibration information according to the calibration reflector profile point cloud data and the reflector size information based on an optimization function f 1; the reflector calibration information comprises reflector upper left corner point position information and calibration rotation matrix information;
Wherein,,
calibrating contour point cloud data, P, of the reflector for the ith 0 R×P，
L and W are the length and width of the reflector, P is the position information of the left upper corner point of the reflector, R is the information of the calibration rotation matrix, and P 0 Projection position information of upper left corner point position information of reflector on target plane, P 1 Is the projection position information of the upper right corner point position information of the reflector on the target plane, P 2 Is the projection position information of the right lower corner point position information of the reflector on the target plane, P 3 And projecting position information for the left lower corner of the reflector on a target plane, wherein the target plane is a preset projection plane for calibrating the reflector plane information.
2. The method of claim 1, wherein extracting nominal reflector profile point cloud data from the nominal reflector plane information comprises:
determining the projection plane information of the calibration reflector on the target plane;
rasterizing the projection plane information of the calibration reflecting plate, and determining the point cloud information of the calibration reflecting plate in the grid;
and determining the outline point cloud data of the calibrated reflector according to the point cloud information of the calibrated reflector in the grid.
3. The method of claim 1, wherein determining pose information of the mobile robot at the target location based on locating reflector laser point cloud data and predetermined reflector calibration information in the laser point cloud data comprises:
determining positioning reflector plane information according to the positioning reflector laser point cloud data;
extracting contour point cloud data of the positioning reflector according to the plane information of the positioning reflector;
matching the outline point cloud data of the positioning reflector with the reflector calibration information to determine target reflector calibration information;
and determining pose information of the mobile robot at the target position according to the outline point cloud data of the positioning reflector, the position information of the left upper corner point of the target reflector in the target reflector calibration information and the target calibration rotation matrix information.
4. A method according to claim 3, wherein determining pose information of the mobile robot at the target position based on the target reflector upper left corner point position information and target calibration rotation matrix information in the positioning reflector profile point cloud data and the target reflector calibration information comprises:
Determining the projection position information of the target reflector at the upper left corner of the target on the target plane, the projection position information of the target upper right corner, the projection position information of the target lower right corner and the projection position information of the target lower left corner according to the position information of the corner point of the target reflector in the target reflector calibration information and the target calibration rotation matrix information;
based on the optimization function f2, according to the projection position information of the upper left corner of the target reflector on the target plane, the projection position information of the upper right corner of the target, the projection position information of the lower left corner of the target and the contour point cloud data of the positioning reflector, the pose information of the mobile robot at the target position is determined,
wherein,,
the ith positioning reflector profile point cloud data is obtained, T is pose information of the mobile robot at the target position, and +.>
Projection position information for the upper left corner of the object, +.>
Projection position information for the upper right corner of the object, +.>
Projection position information for the lower right corner of the object, +.>
For projecting position information for the lower left corner of the target, P r R is the angular point position information of the target reflector r And calibrating the rotation matrix information for the target.
5. A laser positioning device for a mobile robot, the device comprising:
The laser point cloud data determining module is used for determining laser point cloud data acquired by the mobile robot at a target position in a target area;
the reflector positioning instruction receiving and determining module is used for determining whether a reflector positioning instruction is received at the target position;
the first pose information determining module is used for determining pose information of the mobile robot at the target position according to the positioning reflector laser point cloud data in the laser point cloud data and the predetermined reflector calibration information if yes;
the second pose information determining module is used for determining pose information of the mobile robot at the target position according to the laser point cloud data and a pre-constructed laser point cloud map of the target area;
wherein the apparatus further comprises:
the laser point cloud map construction module is used for constructing a laser point cloud map of a target area according to sensor data acquired when the mobile robot moves in the target area before determining the laser point cloud data acquired by the mobile robot at the target position in the target area;
the reflector calibration information determining module is used for determining reflector calibration information in the target area according to the calibrated reflector laser point cloud data in the sensor data;
The reflector calibration information determining module comprises:
the calibration reflector plane information determining unit is used for determining calibration reflector plane information according to the calibration reflector laser point cloud data in the sensor data;
the calibration reflector profile point cloud data extraction unit is used for extracting calibration reflector profile point cloud data according to the calibration reflector plane information;
the reflector calibration information determining unit is used for determining the reflector calibration information according to the calibration reflector profile point cloud data and the reflector size information based on an optimization function f 1; the reflector calibration information comprises reflector upper left corner point position information and calibration rotation matrix information;
wherein,,
calibrating contour point cloud data, P, of the reflector for the ith 0 R×P，
L and W are the length and width of the reflector, P is the position information of the left upper corner point of the reflector, R is the information of the calibration rotation matrix, and P 0 Projection position information of upper left corner point position information of reflector on target plane, P 1 Is the projection position information of the upper right corner point position information of the reflector on the target plane, P 2 Is the projection position information of the right lower corner point position information of the reflector on the target plane, P 3 And projecting position information for the left lower corner of the reflector on a target plane, wherein the target plane is a preset projection plane for calibrating the reflector plane information.
6. A laser positioning electronic device of a mobile robot, the electronic device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the laser positioning method of the mobile robot of any one of claims 1-4.
7. A computer readable storage medium, characterized in that the computer readable storage medium stores computer instructions for causing a processor to execute the laser positioning method of the mobile robot according to any one of claims 1-4.
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Application publication date: 20221206 Assignee: Muyi (Huzhou) Technology Development Co.,Ltd. Assignor: SHANGHAI MOOE-ROBOT TECHNOLOGY Co.,Ltd. Contract record no.: X2024980007103 Denomination of invention: Laser positioning methods, devices, equipment, and media for mobile robots Granted publication date: 20230623 License type: Common License Record date: 20240613 |