CN113470047A - Point cloud processing method and device - Google Patents
Point cloud processing method and device Download PDFInfo
- Publication number
- CN113470047A CN113470047A CN202110726662.7A CN202110726662A CN113470047A CN 113470047 A CN113470047 A CN 113470047A CN 202110726662 A CN202110726662 A CN 202110726662A CN 113470047 A CN113470047 A CN 113470047A
- Authority
- CN
- China
- Prior art keywords
- point cloud
- configuration file
- cloud data
- point
- laser radar
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10028—Range image; Depth image; 3D point clouds
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10032—Satellite or aerial image; Remote sensing
- G06T2207/10044—Radar image
Landscapes
- Engineering & Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Traffic Control Systems (AREA)
- Optical Radar Systems And Details Thereof (AREA)
Abstract
The application discloses a point cloud processing method and device. Wherein, the method comprises the following steps: acquiring a configuration file, wherein a target sub-area in the laser radar point cloud is marked in the configuration file, and the target sub-area is a shielding area; and obtaining second point cloud data in the point cloud data acquired by the laser radar according to the configuration file, wherein the second point cloud data is the point cloud data of the laser radar except the first point cloud data of the corresponding target subarea. The method and the device solve the technical problem that the quality of the point cloud data is low in the related technology.
Description
Technical Field
The application relates to the field of laser radars, in particular to a point cloud processing method and device.
Background
The laser radar comprises a transmitting system, a receiving system and the like, wherein the transmitting system transmits a beam of laser outwards, the laser is reflected after reaching the surface of a target object, the receiving system receives the reflected light, and the distance between the laser radar and the detected object is determined through the time difference between transmitting and receiving.
The data form of the lidar is a point cloud. The point cloud data contains rich characteristic information of the detected object, wherein the information comprises position information, signal intensity, GPS time, echo times and the like. The point cloud data can be used for constructing a three-dimensional model of the detected object, and environment perception, synchronous positioning and mapping are achieved.
The laser radar application environments are different, meanwhile, due to the fact that the receiving angle of the receiving unit is large, partial receiving units are shielded in the working environment difficultly, shielded point clouds are formed, the overall point cloud quality is reduced, and the point cloud data bring inconvenience to subsequent algorithm processing and cause misjudgment.
Disclosure of Invention
The embodiment of the application provides a point cloud processing method and device, and aims to at least solve the technical problem that the quality of point cloud data in the related technology is low.
According to an aspect of an embodiment of the present application, there is provided a method for processing a point cloud, including: acquiring a configuration file, wherein a target sub-area in the laser radar point cloud is marked in the configuration file, and the target sub-area is a shielding area; and obtaining second point cloud data in the point cloud data acquired by the laser radar according to the configuration file, wherein the second point cloud data is the point cloud data of the laser radar except the first point cloud data of the corresponding target subarea.
According to an aspect of the embodiments of the present application, there is also provided a method for processing a point cloud, including: after the laser radar is installed at a specific position of a target carrier, point cloud collected by the laser radar is obtained; determining a target sub-region from the point cloud, wherein the target sub-region is an occlusion region; and generating a configuration file, wherein the configuration file is used for indicating the first point cloud data of the target sub-area and the remaining second point cloud data.
According to another aspect of the embodiments of the present application, there is also provided a processing apparatus for point cloud, including: the device comprises a first acquisition unit, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for acquiring a configuration file, a target sub-area in the laser radar point cloud is marked in the configuration file, and the target sub-area is a shielding area; and the processing unit is used for obtaining second point cloud data in the point cloud data acquired by the laser radar according to the configuration file, wherein the second point cloud data is the point cloud data of the laser radar except the first point cloud data corresponding to the target subarea.
According to another aspect of the embodiments of the present application, there is also provided a processing apparatus for point cloud, including: the second acquisition unit is used for acquiring point cloud collected by the laser radar after the laser radar is installed at a specific position of the target carrier; the determining unit is used for determining a target sub-region from the point cloud, and the target sub-region is an occlusion region; the generating unit is used for generating a configuration file, wherein the configuration file is used for indicating the first point cloud data of the target sub-area and the remaining second point cloud data.
According to another aspect of the embodiments of the present application, there is also provided a storage medium including a stored program which, when executed, performs the above-described method.
According to another aspect of the embodiments of the present application, there is also provided an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the above method through the computer program.
According to an aspect of the application, a computer program product or computer program is provided, comprising computer instructions, the computer instructions being stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions to cause the computer device to perform the steps of any of the embodiments of the method described above.
In the embodiment of the application, the point cloud data of the shielding part can be removed by adopting a configuration file mode, so that the problem of low quality of the point cloud data in the related technology is solved, and the subsequent perception algorithm can be conveniently used for processing the point cloud.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a flow chart of an alternative method of processing a point cloud in accordance with an embodiment of the present application;
FIG. 2 is a flow chart of an alternative method of point cloud culling according to an embodiment of the application;
FIG. 3 is a flow chart of an alternative point cloud processing method according to an embodiment of the present application;
FIG. 4 is a flow chart of an alternative point cloud processing method according to an embodiment of the present application;
FIG. 5 is a flow chart of an alternative method of point cloud culling according to an embodiment of the application;
and
fig. 6 is a block diagram of a terminal according to an embodiment of the present application.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or 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.
According to an aspect of an embodiment of the present application, a method embodiment of a method for processing a point cloud is provided.
Alternatively, in this embodiment, the above-mentioned point cloud processing method may be applied to an environment including an upper computer and a lower computer, where the upper computer is a computer device (such as a stand-alone computer, a PC, or a computer device integrated on a target vehicle, such as an on-board computer, etc.) for performing point cloud preprocessing, and the lower computer may be a laser radar.
Fig. 1 is a flowchart of an alternative method for processing point clouds, which may be executed in the above environment, where an upper computer and a lower computer respectively execute respective process steps, and as shown in fig. 1, the method may include the following steps:
and step S11, after the laser radar is installed at the specific position of the target carrier, the upper computer acquires the point cloud of the acquisition area of the laser radar. The target vehicle may be a vehicle, an airplane, a robot, etc., and the vehicle will be described as an example.
And step S12, the upper computer determines a target sub-region from the point cloud, wherein the target sub-region is a shielding region.
Determining a target sub-region from the point cloud, wherein the target sub-region is an occlusion region and the method comprises the following three ways:
one is realized by utilizing the point cloud frame selection function of the upper computer:
and S121, visually displaying the point cloud in an interactive interface of the upper computer, wherein a user can select a shielded area by using a frame selection function in the interactive interface.
Step S122, under the condition that the frame selection function is triggered, determining that the sub-area selected by the frame selection function is the target sub-area, wherein when a user uses the frame selection function, the framed area can be one or more, and if the user uses one framed area, directly using the framed area as the target sub-area; and if the number of the regions is multiple, all the framed regions are taken as target sub-regions.
In the scheme of visualizing the point cloud and manually screening, the vehicle position does not need to be changed, and the point cloud can be completely selected manually.
In the first method, the point cloud may be visualized first, and then the occlusion point is selected (for example, manual pointing or automatic selection by a machine according to actual conditions). The distance of a detected object can be seen from a point cloud image, the distance of the blocked part of point cloud is the same as that of the normal part of point cloud, but the distance of the points is relatively short, and the points can not change along with the change of the detected object, namely, the part of point cloud can be obviously distinguished from the part of point cloud which is not blocked according to the characteristics, so that the part of point cloud data can be directly deleted for the convenience of subsequent processing, and the part of point cloud data is reflected on the point cloud image, namely, the blocked part of point cloud does not emit light any more; of course, the part of the point cloud data can be marked as data which does not need to be processed without deleting the point cloud data.
Secondly, the algorithm is utilized to realize automatically: collecting multi-frame point clouds under the condition that the position of a platform (namely a target carrier such as a vehicle and the like) on which a laser radar is arranged is changed in a moving state; and searching a sub-region where the distance-unchanged occlusion point is located in the multi-frame point cloud image as a target sub-region.
Thirdly, the method can also be realized by using an algorithm; in the state that a platform for arranging the laser radar is static or in motion, a sub-region where a shielding point (namely a point with a very small distance) with a distance smaller than a preset threshold value is located is searched in the point cloud to serve as a target sub-region.
In order to avoid errors caused by contingency, the second method and the third method can be combined, a sub-region where the shielding points with the same positions and the distances smaller than a preset threshold value are located is searched in the multi-frame point cloud and is used as a target sub-region, namely, the distance of a certain point in the multi-frame point cloud is small, and the shielding points are considered as shielding points.
Step S13, the upper computer generates a configuration file, where the configuration file is used to indicate the first point cloud data of the target sub-region and the remaining second point cloud data, the configuration file may specifically include address bits and identification information, and the identification information indicates whether a point corresponding to each address bit is an occlusion point.
Optionally, an address index may be created for each acquisition point of the lidar, each address index may uniquely correspond to one acquisition point; saving the address index and the corresponding enabling identification of each acquisition point to a configuration file, wherein the enabling identification with a first numerical value (such as '1') is used for indicating that the point corresponding to the address index is located in the target sub-area, and the enabling identification with a second numerical value (such as '0') is used for indicating that the point corresponding to the address index is located outside the target sub-area.
And step S14, the lower computer acquires the configuration file from the upper computer.
After the upper computer generates the configuration file, when the laser radar requests the configuration file, the upper computer sends the configuration file to the laser radar, and the laser radar stores the configuration file by using the storage and reads the configuration file from the storage after restarting and electrifying.
Step S15, in the point cloud collected by the laser radar, the lower computer eliminates (the elimination may be direct deletion, or may identify the part of point cloud data so that the part of point cloud data does not need to be processed subsequently) the first point cloud data located in the target sub-area, and obtains second point cloud data to be processed by the target vehicle.
Optionally, after the configuration file is generated according to step S13, the configuration file may be issued to the lower computer, the lower computer processes the point cloud data according to the configuration file (as described in step S14 and step S15), or the point cloud data is processed directly on the upper computer according to the configuration file, and at this time, the lower computer transmits the collected point cloud data to the upper computer for processing.
In order to improve the quality of the point cloud, the method for invalidating the occluded point cloud according to different installation environments is provided. The user can select a non-luminous point cloud area according to the formed point cloud (the step can be automatically realized by a machine), generate a configuration file and download the configuration file into the laser radar. After restarting the radar, the previously configured non-light emitting area is free of point cloud data.
The preprocessing method can remove the occluded point cloud and improve the quality of the point cloud. When the method is applied to automatic driving, the problems of automatic driving blockage, parking and the like caused by the point cloud quality can be further solved. Because if the point cloud of the invalid area is included in the point cloud, the algorithm may be caused to falsely report the obstacle when identifying the travelable area and the obstacle, or the space which can be used is falsely identified as impassable. In addition, the shielding area can be regarded as an invalid area, so that an invalid detection area which is not concerned by a user is removed, the subsequent data processing amount can be reduced, and the subsequent data processing efficiency is improved.
As an alternative embodiment, the steps of implementing the point cloud occlusion rejection function are shown in fig. 2:
and step S21, the laser radar is started after being installed at a specific position, and a point cloud image of the laser radar is obtained.
And step S22, the user judges which points are the shielded points, selects the points to be eliminated by using the upper computer, and then generates a new configuration file.
The steps are realized by matching the upper computer and the lower computer, and the functions to be realized by the upper computer end are shown in fig. 3. The upper computer generally refers to a computer, a PC and the like, and the lower computer is the laser radar.
Step S221, a point cloud framing function, and a user can frame the point cloud data to be selected according to needs.
In step S222, the selected point cloud is converted into a configuration file.
Step S223, a point cloud configuration file downloading function.
In step S224, the device may read the configuration file from the FLASH after being powered on.
And step S225, the upper computer sends the configuration message to the lower computer through the communication interface with the lower computer.
In the scheme, a point cloud frame selection function of the upper computer is provided, and a user can select a shielded area according to data of the initial point cloud and export a configuration file. The method can visually reflect the position of the laser radar which is shielded, and the frame selection function provides a convenient means for a user to select the shielding points which need to be removed.
The point cloud configuration file comprises parameters of whether all points of the point cloud are luminous or not after being framed and selected by a user, and the lower computer can determine whether each point of the point cloud is luminous or not according to the configuration file. Whether each point emits light or not is not that the actual light-emitting time of the laser corresponding to the shielding point does not emit light, but the laser emits light normally, and only the point cloud of the shielding area does not emit light on the final point cloud image, wherein the light emission means that the light-emitting point on the point cloud image emits light, and the light-emitting point does not emit light, namely, the data detected by the area is deleted. The method has the final effect that the information of covering part of the point cloud is not sent to an algorithm any more, and the point cloud visualization shows that the part of the point cloud is black, and is referred to as whether the point cloud shines or not.
Step S23, the new configuration file is downloaded into the laser radar.
The functions to be realized by the lower computer are shown in fig. 4:
and S231, storing the file configured by the upper computer in a storage medium.
In step S232, the address index of each point of the point cloud is used to read the enabling state of the point from the storage medium.
And step S233, determining whether the point cloud parameters of the point are uploaded to an upper computer or not by reading the enabling state of the point.
The lower computer designs a storage structure matched with data transmitted by the upper computer and used for storing point cloud configuration files, each address in the storage structure and the light emitting state of each point of the point cloud have a one-to-one correspondence relationship, the storage structure has a nonvolatile characteristic, and a user only needs to configure each machine installed at a specific position once.
And step S24, the point cloud of the shielding position can be closed by restarting the laser radar.
Optionally, when the point cloud occlusion rejection is implemented, the point cloud occlusion rejection can be automatically completed by a computer without setting by a user, and the principle of the scheme is as shown in fig. 5:
step S51, the lidar is placed in a working position.
Step S52, ensure that the laser radar places an object with a fixed distance in front of the object, which is about the largest area that the radar can detect at the field angle of the radar at that location, and the distance should be greater than the distance of the position of the blocking object.
And step S53, turning on the laser radar, and continuously acquiring point cloud images of a plurality of frames.
And step S54, processing the point cloud data by using a software algorithm, judging points with distances smaller than the placement positions of the detection objects in the frames, judging the points as shielding points, generating a point cloud configuration file, and sending the point cloud configuration file to a lower computer for shielding point elimination.
The above method is performed while the platform on which the lidar is mounted remains stationary.
Similarly, the point cloud may be collected in a moving state, but the situation is more complicated than a static state, and multiple frames of point clouds in the moving state may be compared to find out a point with a constant distance, and the point with the constant distance is excluded from the points where the lidar and the detected object are kept relatively static, for example, a vehicle equipped with the lidar and the detected vehicle travel on a highway at the same speed, and in this case, it is necessary to further determine whether the point is a blocking object, and then perform the exclusion.
In contrast, in a static state, the shielded points are easier to distinguish, and the detection object in the case is easier to search, such as one wall.
The point cloud data obtained by the method of removing the shielding part points is convenient for the subsequent algorithm to process the point cloud, and the problem of automatic driving blockage or even parking caused by shielding is effectively solved in the aspect of automatic driving.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present application.
According to another aspect of the embodiment of the application, a processing device for point cloud for implementing the processing method for point cloud is also provided. The apparatus may include:
the device comprises a first acquisition unit, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for acquiring a configuration file, a target sub-area in the laser radar point cloud is marked in the configuration file, and the target sub-area is a sheltering area (namely, a sub-area where a point where point cloud data does not change is located under the condition that the position of a target carrier for fixedly mounting the laser radar is changed);
and the processing unit is used for obtaining second point cloud data in the point cloud data acquired by the laser radar according to the configuration file, wherein the second point cloud data is the point cloud data of the laser radar except the first point cloud data corresponding to the target subarea.
The processing unit is further configured to: acquiring an enabling identifier of each point in the point cloud data from the configuration file; and taking the point cloud data of all the points with the enabling identification value of the first numerical value as first point cloud data, and taking the point cloud data of all the points with the enabling identification value of the second numerical value as second point cloud data.
According to another aspect of the embodiment of the application, a processing device for point cloud for implementing the processing method for point cloud is also provided. The apparatus may include:
and the second acquisition unit is used for acquiring the point cloud acquired by the laser radar after the laser radar is installed at the specific position of the target carrier.
And the determining unit is used for determining a target sub-area from the point cloud, and the target sub-area is an occlusion area.
The generating unit is used for generating a configuration file, wherein the configuration file is used for indicating the first point cloud data of the target sub-area and the remaining second point cloud data.
Optionally, the apparatus of the present application may further comprise: and the transmission unit is used for sending the configuration file to the laser radar when the laser radar requests the configuration file after generating the configuration file, wherein the laser radar is used for saving the configuration file by using the memory and reading the configuration file from the memory after restarting power-on.
Optionally, the generating unit is further configured to: creating an address index for each point of the point cloud of the laser radar; and saving the address index and the corresponding enable identification of each point to a configuration file, wherein the enable identification of the first numerical value is used for indicating that the point corresponding to the address index is positioned in the target sub-area, and the enable identification of the second numerical value is used for indicating that the point corresponding to the address index is positioned outside the target sub-area.
Optionally, the determining unit is further configured to: visually displaying the point cloud image in an interactive interface, wherein a point cloud frame selection function is provided on the interactive interface; and under the condition that the frame selection function is triggered, determining the sub-region selected by the frame selection function as a target sub-region.
Optionally, the determining unit is further configured to: acquiring multi-frame point clouds under the condition that the position of a target carrier is changed, and searching a sub-region where a shielding point with a constant distance is located from the multi-frame point clouds to serve as the target sub-region.
Optionally, the determining unit is further configured to: and searching a sub-region where the shielding point with the distance smaller than a preset threshold value is located in the point cloud to serve as a target sub-region.
It should be noted here that the modules described above are the same as the examples and application scenarios implemented by the corresponding steps, but are not limited to the disclosure of the above embodiments. It should be noted that the modules described above as a part of the apparatus may operate in a corresponding hardware environment, and may be implemented by software or hardware.
According to another aspect of the embodiment of the application, a server or a terminal for implementing the point cloud processing method is also provided.
Fig. 6 is a block diagram of a terminal according to an embodiment of the present application, and as shown in fig. 6, the terminal may include: one or more processors 601 (only one of which is shown in fig. 6), a memory 603, and a transmitting device 605, as shown in fig. 6, the terminal may further include an input-output device 607.
The memory 603 may be configured to store software programs and modules, such as program instructions/modules corresponding to the method and apparatus for processing a point cloud in the embodiment of the present application, and the processor 601 executes various functional applications and data processing by running the software programs and modules stored in the memory 603, that is, implements the above-mentioned method for processing a point cloud. The memory 603 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 603 may further include memory located remotely from the processor 601, which may be connected to the terminal through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The above-mentioned transmission device 605 is used for receiving or sending data via a network, and may also be used for data transmission between a processor and a memory. Examples of the network may include a wired network and a wireless network. In one example, the transmission device 605 includes a Network adapter (NIC) that can be connected to a router via a Network cable and other Network devices to communicate with the internet or a local area Network. In one example, the transmission device 605 is a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.
Among them, the memory 603 is used to store an application program, in particular.
The processor 601 may call the application stored in the memory 603 through the transmission device 605 to perform the following steps:
acquiring a configuration file, wherein a target sub-area in a laser radar point cloud is marked in the configuration file, and the target sub-area is a shielding area;
and obtaining second point cloud data in the point cloud data acquired by the laser radar according to the configuration file, wherein the second point cloud data is the point cloud data of the laser radar except the first point cloud data corresponding to the target subarea.
Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments, and this embodiment is not described herein again.
It can be understood by those skilled in the art that the structure shown in fig. 6 is only an illustration, and the terminal may be a terminal device such as a smart phone (e.g., an Android phone, an iOS phone, etc.), a tablet computer, a palm computer, and a Mobile Internet Device (MID), a PAD, etc. Fig. 6 is a diagram illustrating a structure of the electronic device. For example, the terminal may also include more or fewer components (e.g., network interfaces, display devices, etc.) than shown in FIG. 6, or have a different configuration than shown in FIG. 6.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by a program instructing hardware associated with the terminal device, where the program may be stored in a computer-readable storage medium, and the storage medium may include: flash disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
Embodiments of the present application also provide a storage medium. Alternatively, in the present embodiment, the storage medium may be used for a program code for executing a processing method of a point cloud.
Optionally, in this embodiment, the storage medium may be located on at least one of a plurality of network devices in a network shown in the above embodiment.
Acquiring a configuration file, wherein a target sub-area in a laser radar point cloud is marked in the configuration file, and the target sub-area is a shielding area;
and obtaining second point cloud data in the point cloud data acquired by the laser radar according to the configuration file, wherein the second point cloud data is the point cloud data of the laser radar except the first point cloud data corresponding to the target subarea.
Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments, and this embodiment is not described herein again.
Optionally, in this embodiment, the storage medium may include, but is not limited to: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.
The integrated unit in the above embodiments, if implemented in the form of a software functional unit and sold or used as a separate product, may be stored in the above computer-readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a storage medium, and including instructions for causing one or more computer devices (which may be personal computers, servers, network devices, or the like) to execute all or part of the steps of the method described in the embodiments of the present application.
In the above embodiments of the present application, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed client may be implemented in other manners. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one type of division of logical functions, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The foregoing is only a preferred embodiment of the present application and it should be noted that those skilled in the art can make several improvements and modifications without departing from the principle of the present application, and these improvements and modifications should also be considered as the protection scope of the present application.
Claims (10)
1. A method for processing point clouds, comprising:
acquiring a configuration file, wherein a target sub-area in a laser radar point cloud is marked in the configuration file, and the target sub-area is a shielding area;
and obtaining second point cloud data in the point cloud data acquired by the laser radar according to the configuration file, wherein the second point cloud data is the point cloud data of the laser radar except the first point cloud data corresponding to the target subarea.
2. The method of claim 1, wherein obtaining second point cloud data from the configuration file in the point cloud data collected by the lidar comprises:
acquiring an enabling identifier of each point in the point cloud data from the configuration file;
and taking the point cloud data of all points with the enabling identification value of a first numerical value as the first point cloud data, and taking the point cloud data of all points with the enabling identification value of a second numerical value as the second point cloud data.
3. A method for processing point clouds, comprising:
after a laser radar is installed at a specific position of a target carrier, point cloud collected by the laser radar is obtained;
determining a target sub-region from the point cloud, wherein the target sub-region is an occlusion region;
generating a configuration file, wherein the configuration file is used for indicating the first point cloud data and the remaining second point cloud data of the target sub-area.
4. The method of claim 3, wherein after generating the configuration file, the method further comprises:
and when the laser radar requests the configuration file, sending the configuration file to the laser radar, wherein the laser radar is used for saving the configuration file by using a memory and reading the configuration file from the memory after restarting and powering on.
5. The method of claim 3, wherein generating a configuration file comprises:
creating an address index for each point of the point cloud of the lidar;
and saving the address index and the corresponding enabling identification of each point to the configuration file, wherein the enabling identification of the first numerical value is used for indicating that the point corresponding to the address index is positioned in the target sub-area, and the enabling identification of the second numerical value is used for indicating that the point corresponding to the address index is positioned outside the target sub-area.
6. The method of any of claims 3 to 5, wherein determining a target sub-region from the point cloud comprises:
visually displaying the point cloud image in an interactive interface, wherein a point cloud frame selection function is provided on the interactive interface;
and under the condition that the frame selection function is triggered, determining the sub-region selected by the frame selection function as the target sub-region.
7. The method of any of claims 3 to 5, wherein determining a target sub-region from the point cloud comprises:
acquiring multi-frame point clouds under the condition that the position of a target carrier is changed, and searching a sub-region where a shielding point with a constant distance is located from the multi-frame point clouds to serve as the target sub-region.
8. The method of any of claims 3 to 5, wherein determining a target sub-region from the point cloud comprises:
and searching a sub-region where the shielding point with the distance smaller than a preset threshold value is located in the point cloud to serve as the target sub-region.
9. A point cloud processing device, comprising:
the device comprises a first acquisition unit, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for acquiring a configuration file, a target sub-area in the laser radar point cloud is marked in the configuration file, and the target sub-area is a shielding area;
and the processing unit is used for obtaining second point cloud data in the point cloud data acquired by the laser radar according to the configuration file, wherein the second point cloud data is the point cloud data of the laser radar except the first point cloud data corresponding to the target subarea.
10. A point cloud processing device, comprising:
the second acquisition unit is used for acquiring point cloud collected by the laser radar after the laser radar is installed at a specific position of a target carrier;
the determining unit is used for determining a target sub-region from the point cloud, wherein the target sub-region is an occlusion region;
the generating unit is used for generating a configuration file, wherein the configuration file is used for indicating the first point cloud data of the target sub-area and the remaining second point cloud data.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110726662.7A CN113470047A (en) | 2021-06-29 | 2021-06-29 | Point cloud processing method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110726662.7A CN113470047A (en) | 2021-06-29 | 2021-06-29 | Point cloud processing method and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113470047A true CN113470047A (en) | 2021-10-01 |
Family
ID=77873682
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110726662.7A Pending CN113470047A (en) | 2021-06-29 | 2021-06-29 | Point cloud processing method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113470047A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115079128A (en) * | 2022-08-23 | 2022-09-20 | 深圳市欢创科技有限公司 | Method and device for distortion removal of laser radar point cloud data and robot |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20190323843A1 (en) * | 2018-07-04 | 2019-10-24 | Baidu Online Network Technology (Beijing) Co., Ltd. | Method for generating a high precision map, apparatus and storage medium |
| CN111273314A (en) * | 2018-11-16 | 2020-06-12 | 北京四维图新科技股份有限公司 | Point cloud data processing method and device and storage medium |
| CN111402160A (en) * | 2020-03-13 | 2020-07-10 | 北京百度网讯科技有限公司 | Point cloud data denoising method, device, equipment and storage medium |
| CN112700455A (en) * | 2020-12-28 | 2021-04-23 | 北京超星未来科技有限公司 | Laser point cloud data generation method, device, equipment and medium |
| CN112949366A (en) * | 2020-04-01 | 2021-06-11 | 北京京东乾石科技有限公司 | Obstacle identification method and device |
-
2021
- 2021-06-29 CN CN202110726662.7A patent/CN113470047A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20190323843A1 (en) * | 2018-07-04 | 2019-10-24 | Baidu Online Network Technology (Beijing) Co., Ltd. | Method for generating a high precision map, apparatus and storage medium |
| CN111273314A (en) * | 2018-11-16 | 2020-06-12 | 北京四维图新科技股份有限公司 | Point cloud data processing method and device and storage medium |
| CN111402160A (en) * | 2020-03-13 | 2020-07-10 | 北京百度网讯科技有限公司 | Point cloud data denoising method, device, equipment and storage medium |
| CN112949366A (en) * | 2020-04-01 | 2021-06-11 | 北京京东乾石科技有限公司 | Obstacle identification method and device |
| CN112700455A (en) * | 2020-12-28 | 2021-04-23 | 北京超星未来科技有限公司 | Laser point cloud data generation method, device, equipment and medium |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115079128A (en) * | 2022-08-23 | 2022-09-20 | 深圳市欢创科技有限公司 | Method and device for distortion removal of laser radar point cloud data and robot |
| CN115079128B (en) * | 2022-08-23 | 2022-12-09 | 深圳市欢创科技有限公司 | Method and device for distortion removal of laser radar point cloud data and robot |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106951847B (en) | Obstacle detection method, apparatus, device and storage medium | |
| US11455511B2 (en) | Ground environment detection method and apparatus | |
| CN109191553B (en) | Point cloud rendering method, device, terminal and storage medium | |
| CN109377694B (en) | Monitoring method and system for community vehicles | |
| US20200201513A1 (en) | Systems and methods for rfid tag locationing in augmented reality display | |
| CN113127583A (en) | Data transmission method and device | |
| CN110245567B (en) | Obstacle avoidance method and device, storage medium and electronic equipment | |
| CN113470047A (en) | Point cloud processing method and device | |
| EP4345773A1 (en) | Lane line extraction method and apparatus, vehicle and storage medium | |
| CN115294544A (en) | Driving scene classification method, device, equipment and storage medium | |
| CN114460598A (en) | Target identification method, device, equipment and storage medium | |
| CN111540027A (en) | Detection method, detection device, electronic equipment and storage medium | |
| CN114296716A (en) | Function configuration method and device for intelligent operation of engineering machinery and electronic equipment | |
| CN112529335B (en) | Model detection method, device, equipment and storage medium | |
| CN108369270B (en) | Radar detector with multi-band directional display and enhanced false alarm detection | |
| CN113345101B (en) | Three-dimensional point cloud labeling method, device, equipment and storage medium | |
| CN113076830A (en) | Environment passing area detection method and device, vehicle-mounted terminal and storage medium | |
| WO2019111168A1 (en) | Location calibration based on movement path and map objects | |
| CN110892449A (en) | Image processing method and device and mobile device | |
| CN114690783A (en) | Path planning method of mower and related device | |
| CN114359599A (en) | Image processing method, storage medium and computer terminal | |
| CN111435511B (en) | Order processing method, device, equipment, system and readable storage medium | |
| KR102146613B1 (en) | Method for monitoring material location using low-power infrared beacon and speed camera and system using the same | |
| CN112579103A (en) | BMS program flashing device | |
| CN110839131A (en) | Synchronization control method, synchronization control device, electronic equipment and computer readable medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |