Point cloud map updating method, device, electronic device and computer readable medium

Abstract

The embodiments of the present disclosure disclose a point cloud map update method, device, electronic device, and computer-readable medium. A specific implementation of the method includes: in the process of moving from a first location to a second location in a target area, obtaining a real-time point cloud set corresponding to the target area; screening at least one real-time point cloud representing scene changes from the real-time point cloud set as a point cloud set to be processed; and updating the point cloud map associated with the target area according to the point cloud set to be processed. This implementation can quickly and efficiently determine the point cloud set to be processed. Furthermore, the point cloud map can be updated to make the point cloud map more accurate.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the field of computer technology, and more particularly to a point cloud map updating method, device, electronic device, and computer-readable medium. Background Art

[0002] Currently, point cloud maps are an indispensable mapping tool for the smooth operation of unmanned delivery vehicles. The process of constructing a point cloud map is often to use a mapping device pre-equipped with high-precision sensors such as lidar and inertial navigation sensors to perform a full-scale scan of the target scene and build a map. When the target scene changes, the point cloud map of the target scene needs to be updated in a timely manner. Otherwise, a point cloud map that is not updated in a timely manner may cause subsequent unmanned delivery vehicles to experience positioning offsets, perception misdetection, and other problems. For updating point cloud maps, the method usually adopted is to determine the areas in the target scene that have changed through manual monitoring. In this way, the mapping device is used to comprehensively detect the areas in the target scene where changes have occurred and update the point cloud map.

[0003] However, when using the above method to update the map, the following technical problems often occur:

[0004] Manual monitoring has a low accuracy rate in determining the transformation area, which can lead to problems such as missed detections and lags. This results in lower accuracy in subsequent point cloud maps. Furthermore, manual monitoring is time-consuming and labor-intensive. Summary of the Invention

[0005] The content of this disclosure is used to briefly introduce concepts that will be described in detail in the detailed description section below. The content of this disclosure is not intended to identify key features or essential features of the claimed technical solution, nor is it intended to limit the scope of the claimed technical solution.

[0006] Some embodiments of the present disclosure provide a point cloud map updating method, apparatus, electronic device, and computer-readable medium to solve one or more of the technical problems mentioned in the above background technology section.

[0007] In a first aspect, some embodiments of the present disclosure provide a point cloud map updating method, including: obtaining a real-time point cloud set corresponding to the target area during movement from a first location to a second location within the target area; screening at least one real-time point cloud representing scene changes from the real-time point cloud set as a point cloud set to be processed; and updating the point cloud map associated with the target area based on the point cloud set to be processed.

[0008] Optionally, the above-mentioned screening of at least one real-time point cloud representing scene changes from the above-mentioned real-time point cloud set as the point cloud set to be processed includes: removing at least one item of the first real-time point cloud subset and the second real-time point cloud subset from the above-mentioned real-time point cloud set to obtain the real-time point cloud set after removal; and determining the real-time point cloud set after removal as the above-mentioned point cloud set to be processed.

[0009] Optionally, the above-mentioned removing at least one item of the first real-time point cloud subset and the second real-time point cloud subset from the above-mentioned real-time point cloud set to obtain the real-time point cloud set after removal includes: determining the point cloud set in the above-mentioned real-time point cloud set that is a static point cloud as the above-mentioned first real-time point cloud subset; in response to detecting the presence of dynamic point cloud in the above-mentioned real-time point cloud set, determining the point cloud set in the above-mentioned real-time point cloud set that is a dynamic point cloud as the above-mentioned second real-time point cloud subset; removing the above-mentioned first real-time point cloud subset and the above-mentioned second real-time point cloud subset from the above-mentioned real-time point cloud set to obtain the above-mentioned real-time point cloud set after removal.

[0010] Optionally, the above-mentioned determination of the point cloud set that is a static point cloud in the above-mentioned real-time point cloud set as the above-mentioned first real-time point cloud subset includes: in response to detecting that there are identical point clouds between the point cloud set corresponding to the above-mentioned point cloud map and the above-mentioned real-time point cloud set, determining at least one identical point cloud between the point cloud set corresponding to the above-mentioned point cloud map and the above-mentioned real-time point cloud set as the target point cloud set; determining the point cloud set associated with the target ground in the point cloud set corresponding to the above-mentioned point cloud map and the above-mentioned target point cloud set as the above-mentioned first real-time point cloud subset.

[0011] Optionally, the above-mentioned updating of the point cloud map associated with the above-mentioned target area based on the above-mentioned point cloud set to be processed includes: obtaining the voxel grid information set corresponding to the above-mentioned target area and the area information corresponding to each voxel grid information in the above-mentioned voxel grid information set; determining the voxel grid information corresponding to each point cloud to be processed in the above-mentioned point cloud set to be processed based on the area information corresponding to each voxel grid information in the above-mentioned voxel grid information set, and obtaining a voxel grid information subset; determining the point cloud change area information in the above-mentioned target area based on the above-mentioned voxel grid information subset; and updating the above-mentioned point cloud map based on the above-mentioned point cloud change area information.

[0012] Optionally, the above-mentioned determination of the point cloud change area in the above-mentioned target area based on the above-mentioned voxel grid information subset includes: obtaining index information corresponding to each voxel grid information in the above-mentioned voxel grid information set; determining the index information corresponding to each voxel grid information in the above-mentioned voxel grid information subset based on the index information corresponding to each voxel grid information in the above-mentioned voxel grid information set, and obtaining an index information set; determining the number of point cloud associations corresponding to each index information in the above-mentioned index information set; in response to determining that the number of point cloud associations corresponding to at least one index information in the above-mentioned index information set is greater than the first target value, determining the index information whose point cloud association number in the above-mentioned at least one index information meets a predetermined condition as the target index information, and obtaining a target index information set; determining the voxel grid information set corresponding to the above-mentioned target index information set as the above-mentioned first target voxel grid information set.

[0013] Optionally, the method further includes: for each index information in the index information set, determining the sum of the number of point cloud associations corresponding to the index information and the second target value as the number of point cloud associations corresponding to the index information.

[0014] Optionally, the above-mentioned determining the point cloud change area in the above-mentioned target area based on the above-mentioned voxel grid information subset includes: determining the number of point cloud associations corresponding to each voxel grid information in the above-mentioned voxel grid information subset; in response to the existence of at least one voxel grid information in the above-mentioned voxel grid information subset whose corresponding point cloud association number is greater than the first target value, determining the voxel grid information in the above-mentioned at least one voxel grid information whose point cloud association number meets a predetermined condition as the first target voxel grid information, and obtaining the first target voxel grid information set.

[0015] Optionally, the above method also includes: for each voxel grid information in the above voxel grid information subset, determining the point cloud association number corresponding to the voxel grid information by adding the second target value as the point cloud association number corresponding to the voxel grid information.

[0016] Optionally, the method further includes: storing the first target voxel grid information set, and determining an area corresponding to the first target voxel grid information set as a point cloud change area in the target area.

[0017] Optionally, the above-mentioned determining the voxel grid information corresponding to each point cloud to be processed in the above-mentioned point cloud to be processed based on the region information corresponding to each voxel grid information in the above-mentioned voxel grid information set to obtain a voxel grid information subset includes: performing coordinate conversion on each point cloud to be processed in the above-mentioned point cloud to be processed to generate corresponding map coordinates to obtain a map coordinate set; determining the voxel grid information corresponding to each point cloud to be processed in the above-mentioned point cloud to be processed based on the above-mentioned map coordinate set and the region information corresponding to each voxel grid information in the above-mentioned voxel grid information set to obtain a voxel grid information subset.

[0018] In a second aspect, some embodiments of the present disclosure provide a point cloud map updating device, including: an acquisition unit, configured to acquire a real-time point cloud set corresponding to the target area during the process of moving from a first location to a second location within the target area; a screening unit, configured to screen at least one real-time point cloud representing scene changes from the real-time point cloud set as a point cloud set to be processed; and an updating unit, configured to update the point cloud map associated with the target area based on the point cloud set to be processed.

[0019] Optionally, the screening unit is further configured to: remove at least one item of the first real-time point cloud subset and the second real-time point cloud subset from the above-mentioned real-time point cloud set to obtain the real-time point cloud set after removal; and determine the real-time point cloud set after removal as the above-mentioned point cloud set to be processed.

[0020] Optionally, the screening unit is further configured to: determine the point cloud set in the above-mentioned real-time point cloud set that is a static point cloud as the above-mentioned first real-time point cloud subset; in response to detecting the presence of a dynamic point cloud in the above-mentioned real-time point cloud set, determine the point cloud set in the above-mentioned real-time point cloud set that is a dynamic point cloud as the above-mentioned second real-time point cloud subset; remove the above-mentioned first real-time point cloud subset and the above-mentioned second real-time point cloud subset in the above-mentioned real-time point cloud set to obtain the above-mentioned real-time point cloud set after removal.

[0021] Optionally, the screening unit is further configured to: in response to detecting that there are identical point clouds between the point cloud set corresponding to the above-mentioned point cloud map and the above-mentioned real-time point cloud set, determine at least one identical point cloud between the point cloud set corresponding to the above-mentioned point cloud map and the above-mentioned real-time point cloud set as a target point cloud set; and determine the point cloud set associated with the target ground in the point cloud set corresponding to the above-mentioned point cloud map and the above-mentioned target point cloud set as the above-mentioned first real-time point cloud subset.

[0022] Optionally, the updating unit is further configured to: obtain the voxel grid information set corresponding to the above-mentioned target area and the area information corresponding to each voxel grid information in the above-mentioned voxel grid information set; determine the voxel grid information corresponding to each point cloud to be processed in the above-mentioned point cloud set according to the area information corresponding to each voxel grid information in the above-mentioned voxel grid information set, and obtain a voxel grid information subset; determine the point cloud change area information in the above-mentioned target area according to the above-mentioned voxel grid information subset; and update the above-mentioned point cloud map according to the above-mentioned point cloud change area information.

[0023] Optionally, the update unit is further configured to: obtain index information corresponding to each voxel grid information in the above-mentioned voxel grid information set; determine the index information corresponding to each voxel grid information in the above-mentioned voxel grid information subset according to the index information corresponding to each voxel grid information in the above-mentioned voxel grid information set, and obtain an index information set; determine the number of point cloud associations corresponding to each index information in the above-mentioned index information set; in response to determining that there is at least one index information in the above-mentioned index information set whose corresponding number of point cloud associations is greater than the first target value, determine the index information in the above-mentioned at least one index information whose point cloud association number meets the predetermined condition as the target index information, and obtain a target index information set; determine the voxel grid information set corresponding to the above-mentioned target index information set as the above-mentioned first target voxel grid information set.

[0024] Optionally, the updating unit is further configured to: for each index information in the above index information set, determine the sum of the number of point cloud associations corresponding to the above index information and the second target value as the number of point cloud associations corresponding to the above index information.

[0025] Optionally, the update unit is further configured to: determine the number of point cloud associations corresponding to each voxel grid information in the above-mentioned voxel grid information subset; in response to the fact that there is at least one voxel grid information in the above-mentioned voxel grid information subset whose corresponding point cloud association number is greater than the target value, determine the voxel grid information in the above-mentioned at least one voxel grid information whose point cloud association number meets the predetermined conditions as the first target voxel grid information, and obtain the first target voxel grid information set.

[0026] Optionally, the updating unit is further configured to: for each voxel grid information in the above voxel grid information subset, determine the sum of the number of point cloud associations corresponding to the above voxel grid information and the target value as the number of point cloud associations corresponding to the voxel grid information.

[0027] Optionally, the updating unit is further configured to: store the first target voxel grid information set, and determine the area corresponding to the first target voxel grid information set as the point cloud change area in the target area.

[0028] Optionally, the update unit is further configured to: perform coordinate conversion on each point cloud to be processed in the above-mentioned point cloud set to generate corresponding map coordinates to obtain a map coordinate set; determine the voxel grid information corresponding to each point cloud to be processed in the above-mentioned point cloud set based on the above-mentioned map coordinate set and the area information corresponding to each voxel grid information in the above-mentioned voxel grid information set to obtain a voxel grid information subset.

[0029] In a third aspect, some embodiments of the present disclosure provide an electronic device comprising: one or more processors; a storage device on which one or more programs are stored, and when the one or more programs are executed by one or more processors, the one or more processors implement the method described in any implementation manner in the first aspect.

[0030] In a fourth aspect, some embodiments of the present disclosure provide a computer-readable medium having a computer program stored thereon, wherein when the program is executed by a processor, the method described in any implementation manner in the first aspect is implemented.

[0031] The above-described embodiments of the present disclosure have the following advantageous effects: The point cloud map updating methods of some embodiments of the present disclosure can quickly and efficiently determine a set of point clouds to be processed. Furthermore, the point cloud map can be updated, making it more accurate. Specifically, the accuracy of determining the changed area through manual monitoring is low, which may lead to problems such as missed detections and lags. This results in lower accuracy of the subsequent point cloud map. Furthermore, manual monitoring is time-consuming and labor-intensive. Based on this, the point cloud map updating methods of some embodiments of the present disclosure can obtain a real-time point cloud set corresponding to the target area while moving from a first location to a second location within the target area. Here, the real-time point cloud set corresponding to the target area is obtained to serve as data support for subsequently determining areas within the point cloud map where scene changes have occurred. Then, at least one real-time point cloud representing the scene change is selected from the real-time point cloud set to serve as the point cloud set to be processed. By determining the point cloud set to be processed, the areas within the point cloud map where scene changes have occurred can be more accurately determined, making subsequent point cloud map updates more targeted and improving the efficiency of point cloud map updates. Finally, based on the above-mentioned point cloud set to be processed, the point cloud map associated with the above-mentioned target area is updated to make the point cloud map more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The above and other features, advantages, and aspects of the various embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that components and elements are not necessarily drawn to scale.

[0033] Figure 1-2is a schematic diagram of an application scenario of a point cloud map updating method according to some embodiments of the present disclosure;

[0034] Figure 3 is a flowchart of some embodiments of the point cloud map updating method according to the present disclosure;

[0035] Figure 4 is a flowchart of other embodiments of the point cloud map updating method according to the present disclosure;

[0036] Figure 5 is a schematic structural diagram of some embodiments of the point cloud map updating device according to the present disclosure;

[0037] Figure 6 is a schematic structural diagram of an electronic device suitable for implementing some embodiments of the present disclosure. DETAILED DESCRIPTION

[0038] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of protection of the present disclosure.

[0039] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present disclosure may be combined with each other.

[0040] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0041] It should be noted that the modifications of "one" and "multiple" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, they should be understood as "one or more".

[0042] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0043] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0044] Figure 1-Figure 2 It is a schematic diagram of an application scenario of the point cloud map updating method according to some embodiments of the present disclosure.

[0045] exist Figure 1-Figure 2 In an application scenario, while moving from a first location 103 to a second location 104 within a target area 102, the electronic device 101 may first obtain a real-time point cloud set 105 corresponding to the target area 102. In this application scenario, the real-time point cloud set 105 may include: a real-time point cloud 1051, a real-time point cloud 1052, a real-time point cloud 1053, a real-time point cloud 1054, and a real-time point cloud 1055. Each real-time point cloud in the real-time point cloud set 105 may be a point cloud corresponding to each object in the scene corresponding to the target area 102. Then, at least one real-time point cloud 106 representing scene changes is selected from the real-time point cloud set 105 to serve as the to-be-processed point cloud set 107. In this application scenario, the real-time point clouds 1052, 1053, and 1054 are selected from the real-time point cloud set 105. Real-time point cloud 1052, real-time point cloud 1053, and real-time point cloud 1054 in the at least one real-time point cloud 106 may be point clouds corresponding to at least one object in the scene that has changed in target area 102. Real-time point cloud 1052 is determined as point cloud to be processed 1071. Real-time point cloud 1053 is determined as point cloud to be processed 1072. Real-time point cloud 1054 is determined as point cloud to be processed 1073. Finally, based on the set of point clouds to be processed 107, the point cloud map 108 associated with the target area 102 is updated to obtain an updated point cloud map 109.

[0046] It should be noted that the electronic device 101 can be hardware or software. When the electronic device is hardware, it can be implemented as a distributed cluster consisting of multiple servers or terminal devices, or it can be implemented as a single server or a single terminal device. When the electronic device is embodied as software, it can be installed in the hardware devices listed above. It can be implemented as multiple software or software modules for providing distributed services, for example, or it can be implemented as a single software or software module. No specific limitation is made here.

[0047] It should be understood that Figure 1-Figure 2 The number of electronic devices in the embodiment is merely illustrative. Any number of electronic devices may be provided according to implementation requirements.

[0048] Continue to refer Figure 3 , shows a process 300 of some embodiments of the point cloud map updating method according to the present disclosure. The point cloud map updating method includes the following steps:

[0049] Step 301 : in the process of moving from a first location to a second location within a target area, obtaining a real-time point cloud set corresponding to the target area.

[0050] In some embodiments, the execution entity of the above point cloud map updating method (for example Figure 1 or Figure 2 The electronic device shown) can obtain a real-time point cloud set corresponding to the above-mentioned target area during the process of moving from a first location to a second location in the target area. The above-mentioned target area may be a predetermined area to be checked whether the scene has changed. The above-mentioned first location may be the starting location of a route in the target area. The above-mentioned second location may be the ending location of a route in the target area. It should be noted that, in the process of moving from the first location to the second location in the target area, it is necessary to obtain a real-time point cloud set corresponding to each moment in a plurality of moments to determine the area in the target area where the scene change occurs. The real-time point cloud set corresponding to a certain moment may reflect the scene layout information of the current scene.

[0051] For example, while moving from a first location to a second location within a target area, the execution entity may receive a real-time point cloud set from a point cloud collection terminal. The point cloud collection terminal may be a mapping device equipped with sensors such as high-precision lidar and inertial navigation sensors, such as an unmanned delivery vehicle or a self-driving car.

[0052] Step 302 : Filter at least one real-time point cloud representing scene changes from the real-time point cloud set as a point cloud set to be processed.

[0053] In some embodiments, the execution entity may select at least one real-time point cloud representing scene changes from the real-time point cloud set as the point cloud set to be processed. Each of the at least one real-time point cloud may be a point cloud representing a scene in a target area of ​​the point cloud map that may have changed.

[0054] As an example, the execution entity may select at least one real-time point cloud representing scene changes from the real-time point cloud set in various ways as the point cloud set to be processed.

[0055] Step 303: Update the point cloud map associated with the target area according to the point cloud set to be processed.

[0056] In some embodiments, the execution entity may update the point cloud map associated with the target area based on the point cloud set to be processed.

[0057] As an example, the execution subject updates the point cloud map associated with the target area according to the to-be-processed point cloud set, which may include the following steps:

[0058] The first step is to determine a set of regions to be processed based on the above set of point clouds to be processed. The region to be processed can be an area with the point cloud to be processed as the center and the target value as the radius.

[0059] In the second step, each of the to-be-processed areas in the to-be-processed area set in the point cloud map is rescanned in real time to update the point cloud map.

[0060] The point cloud map updating methods of some embodiments of the present disclosure can quickly and efficiently determine the set of point clouds to be processed. Furthermore, the point cloud map can be updated to make it more accurate. Specifically, the accuracy of determining the changed area through manual monitoring is low, which may lead to problems such as underreporting and lags. This results in lower accuracy of the subsequent point cloud map. Furthermore, manual monitoring is time-consuming and labor-intensive. Based on this, the point cloud map updating methods of some embodiments of the present disclosure can obtain a real-time point cloud set corresponding to the target area while moving from a first location to a second location within the target area. Here, the real-time point cloud set corresponding to the target area is obtained to serve as data support for the subsequent determination of the area within the point cloud map where the scene has changed. Then, at least one real-time point cloud representing the scene change is selected from the real-time point cloud set to serve as the set of point clouds to be processed. By determining the set of point clouds to be processed, the area within the point cloud map where the scene has changed can be more accurately determined. This makes subsequent point cloud map updates more targeted and improves the efficiency of point cloud map updates. Finally, based on the above-mentioned point cloud set to be processed, the point cloud map associated with the above-mentioned target area is updated to make the point cloud map more accurate.

[0061] Further references Figure 4 , shows a process 400 of another embodiment of the point cloud map updating method according to the present disclosure. The point cloud map updating method includes the following steps:

[0062] Step 401 : in the process of moving from a first location to a second location within a target area, obtaining a real-time point cloud set corresponding to the target area.

[0063] In some embodiments, the specific implementation of step 401 and the technical effects thereof can be referred to in Figure 3 Step 301 in the corresponding embodiment will not be described in detail here.

[0064] Step 402 : Remove at least one of the first real-time point cloud subset, the second real-time point cloud subset, and the third real-time point cloud subset from the real-time point cloud set to obtain a real-time point cloud set after removal.

[0065] In some embodiments, the execution entity (e.g. Figure 1 The electronic device shown) can remove at least one item of the first real-time point cloud subset and the second real-time point cloud subset from the above-mentioned real-time point cloud set to obtain the real-time point cloud set after removal.

[0066] As an example, the execution entity may remove the first real-time point cloud subset from the real-time point cloud set to obtain a real-time point cloud set after removal.

[0067] In some optional implementations of some embodiments, removing at least one item of the first real-time point cloud subset and the second real-time point cloud subset from the real-time point cloud set to obtain the real-time point cloud set after removal may include the following steps:

[0068] In a first step, the execution entity may determine a point cloud set that is a static point cloud in the real-time point cloud set as the first real-time point cloud subset. The static point cloud set in the point cloud map may be a point cloud set corresponding to at least one object in a scene that has not changed within the target area.

[0069] In a second step, in response to detecting the presence of dynamic point clouds in the real-time point cloud set, the execution entity may determine the point cloud set in the real-time point cloud set that is a dynamic point cloud as the second real-time point cloud subset. The point cloud set that is a dynamic point cloud in the point cloud map may be a point cloud set corresponding to at least one object in a scene that undergoes short-term changes in the target area. The execution entity may use a perception module to detect the presence of dynamic point clouds in the real-time point cloud set. For example, the at least one object in the scene that undergoes short-term changes may include a pedestrian or a car.

[0070] In a third step, the execution entity may remove the first real-time point cloud subset and the second real-time point cloud subset from the real-time point cloud set to obtain the real-time point cloud set after removal.

[0071] Optionally, determining the point cloud set that is a static point cloud in the real-time point cloud set as the first real-time point cloud subset may include the following steps:

[0072] In the first step, in response to detecting that there are identical point clouds between the point cloud set corresponding to the above-mentioned point cloud map and the above-mentioned real-time point cloud set, the above-mentioned execution entity can determine at least one identical point cloud between the point cloud set corresponding to the above-mentioned point cloud map and the above-mentioned real-time point cloud set as the target point cloud set.

[0073] In a second step, the execution entity may determine the target ground-related point cloud set and the target point cloud set in the point cloud set corresponding to the point cloud map as the first real-time point cloud subset, wherein the target ground-related point cloud set may be a point cloud set representing target ground information.

[0074] Step 403: Determine the real-time point cloud set after the removal as the point cloud set to be processed.

[0075] In some embodiments, the execution entity may determine the real-time point cloud set after the removal as the point cloud set to be processed.

[0076] Step 404 : Acquire the voxel grid information set corresponding to the target area and the area information corresponding to each voxel grid information in the voxel grid information set.

[0077] In some embodiments, the execution entity may obtain a voxel grid information set corresponding to the target region and region information corresponding to each voxel grid information in the voxel grid information set. The target region may be divided into multiple voxel grids. Each voxel grid corresponds to voxel grid information. The voxel grid information may be location information of the voxel grid. For example, the location information may be the coordinates corresponding to the voxel grid. Each voxel grid in the multiple voxel grids may be a three-dimensional region. For example, the voxel grid may be a cube of a fixed size. Thus, each voxel grid corresponds to a cube region. The region information of the voxel grid may be information about the region enclosed by the coordinates corresponding to the voxel grid. As an example, the coordinate set corresponding to the voxel grid may include: (1,1), (1,3), (4,1), (4,3). The region information corresponding to the voxel grid may then be: the horizontal coordinate value is between 1 and 4, and the vertical coordinate value is between 1 and 3.

[0078] It should be noted that the target area can be divided into voxel grids by the following steps:

[0079] The first step is to determine the map coordinate system corresponding to the point cloud map.

[0080] In the second step, a target point is determined from the map coordinate system as a reference center for each voxel grid. For example, the target point can be the center point of the target area during the movement from the first location to the second location.

[0081] The third step is to determine the size of the edges in the voxel grid.

[0082] As an example, the size of the edges in the voxel grid can be set according to the resolution of the reference point cloud map and the real-time point cloud. As an example, the size of the edges of the voxel grid can be between 0.15 and 0.3 meters.

[0083] In the fourth step, the target area is divided into individual voxel grids according to the size of the edges and the reference center of the voxel grid.

[0084] Step 405 , based on the region information corresponding to each voxel grid information in the voxel grid information set, the voxel grid information corresponding to each to-be-processed point cloud in the to-be-processed point cloud set is determined to obtain a voxel grid information subset.

[0085] In some embodiments, the execution entity may determine the voxel grid information corresponding to each point cloud to be processed in the point cloud to be processed set based on the region information corresponding to each voxel grid information in the voxel grid information set to obtain a voxel grid information subset.

[0086] As an example, the execution entity may compare the coordinates of each point cloud to be processed in the point cloud set to be processed with the region information of each voxel grid in the voxel grid set to obtain a voxel grid information subset.

[0087] In some optional implementations of some embodiments, determining the voxel grid information corresponding to each to-be-processed point cloud in the to-be-processed point cloud set based on the region information corresponding to each voxel grid information in the voxel grid information set to obtain the voxel grid information subset includes:

[0088] The first step is to perform coordinate conversion on each point cloud in the above-mentioned pending point cloud set to generate corresponding map coordinates, thus obtaining a map coordinate set. The coordinates of each real-time point cloud in the acquired real-time point cloud set are in the real-time point cloud coordinate system. Therefore, the coordinates of the pending point cloud are also in the real-time point cloud coordinate system. Therefore, the coordinates of the pending point cloud need to be converted to the map coordinate system for the subsequent determination of voxel grid information.

[0089] In the second step, based on the map coordinate set and the region information corresponding to each voxel grid information in the voxel grid information set, the voxel grid information corresponding to each point cloud to be processed in the point cloud set to be processed is determined to obtain a voxel grid information subset.

[0090] As an example, the execution entity may compare each map coordinate in the map coordinate set with the region information of each voxel grid in the voxel grid set to obtain a voxel grid information subset.

[0091] Step 406 : Determine the point cloud change area information in the target area based on the voxel grid information subset.

[0092] In some embodiments, the execution entity may determine the point cloud change area information in the target area based on the voxel grid information subset.

[0093] As an example, the execution entity may first fuse the region information corresponding to each voxel grid in the voxel grid subset to obtain fused region information, and then determine the fused region information as the point cloud change region information in the target region.

[0094] In some optional implementations of some embodiments, determining the point cloud change area in the target area based on the voxel grid information subset may include the following steps:

[0095] The first step is to obtain index information corresponding to each voxel grid information in the voxel grid information set. The index information corresponding to the voxel grid information can be determined based on the coordinates corresponding to the voxel grid. The index information can be an index value.

[0096] As an example, the coordinates corresponding to the voxel grid information are (1,1), (1,3), (4,1), (4,3). Therefore, the index value corresponding to the voxel grid information can be: 2.25.

[0097] In the second step, based on the index information corresponding to each voxel grid information in the voxel grid information set, the index information corresponding to each voxel grid information in the voxel grid information subset is determined to obtain an index information set.

[0098] The third step is to determine the number of point cloud associations corresponding to each index information in the index information set. The number of point cloud associations is the number of times each real-time point cloud in the real-time point cloud set corresponding to at least one moment before the current moment is associated with the point cloud.

[0099] As an example, the execution entity may determine the number of point cloud associations corresponding to each index information in the index information set by querying a table representing the association relationship between index information and point cloud association times.

[0100] It should be noted that to improve the efficiency of lookup and search, voxel grid information can be stored in a hash table. The key in the hash table can be the index information of the voxel grid, and the key value in the hash table can be the number of point cloud associations.

[0101] In a fourth step, in response to determining that at least one index information in the index information set has a point cloud association count greater than a first target value, the index information in the at least one index information whose point cloud association count meets a predetermined condition is determined as the target index information, thereby obtaining a target index information set. For example, the first target value may be "0."

[0102] As an example, in response to determining that there is at least one index information in the above-mentioned index information set whose corresponding point cloud association times are greater than the first target value, the above-mentioned execution entity can determine the index information in the above-mentioned at least one index information whose point cloud association times are greater than a predetermined threshold as the target index information, and obtain the target index information set.

[0103] In the fifth step, the voxel grid information set corresponding to the target index information set is determined as the first target voxel grid information set.

[0104] Optionally, the above step further includes: for each index information in the above index information set, the above execution entity may determine the point cloud association count corresponding to the index information by adding the result of the number of point cloud associations corresponding to the index information and a second target value. As an example, the second target value may be 1.

[0105] In some optional implementations of some embodiments, determining the point cloud change area in the target area based on the voxel grid information subset may include the following steps:

[0106] The first step is to determine the number of point cloud associations corresponding to each voxel grid information in the voxel grid information subset.

[0107] As an example, the execution entity may determine the number of point cloud associations corresponding to each voxel grid information in the voxel grid information subset by querying a pre-built table representing the association relationship between voxel grid information and point cloud association times.

[0108] In the second step, in response to the fact that there is at least one voxel grid information in the above voxel grid information subset whose corresponding point cloud association times are greater than the first target value, the voxel grid information whose point cloud association times in the above at least one voxel grid information meet the predetermined conditions is determined as the first target voxel grid information, and the first target voxel grid information set is obtained.

[0109] As an example, in response to the fact that there is at least one voxel grid information in the above-mentioned voxel grid information subset whose corresponding point cloud association times are greater than the first target value, the above-mentioned execution entity can determine the voxel grid information in the above-mentioned at least one voxel grid information whose point cloud association times are greater than a predetermined threshold as the first target voxel grid information, and obtain the first target voxel grid information set.

[0110] Optionally, the steps further include: for each voxel grid information in the voxel grid information subset, the execution entity may determine the point cloud association count corresponding to the voxel grid information by adding a second target value to the point cloud association count corresponding to the voxel grid information. As an example, the second target value may be "1."

[0111] Optionally, the above steps further include: the execution entity may store the first target voxel grid information set, and determine the area corresponding to the first target voxel grid information set as the point cloud change area in the target area.

[0112] As an example, the execution entity may store the first target voxel grid information set in a cache area.

[0113] Step 407: Update the point cloud map according to the point cloud change area information.

[0114] In some embodiments, the execution entity may update the point cloud map based on the point cloud change area information.

[0115] As an example, the execution entity may perform point cloud update on the point cloud changed area corresponding to the point cloud changed area information in the point cloud map.

[0116] from Figure 4 It can be seen that Figure 3 Compared with the description of some corresponding embodiments, Figure 4 The point cloud map update method process 400 in some corresponding embodiments further highlights the specific steps of determining the point cloud set to be processed and determining the point cloud change area information. As a result, the solutions described in these embodiments can more accurately and efficiently determine the point cloud set to be processed, and based on the point cloud set to be processed, more accurately determine the point cloud change area information in the target area. Thus, based on the point cloud change area information, the point cloud map is updated to make the point cloud map more accurate.

[0117] Further references Figure 5 As an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of a point cloud map updating device. These device embodiments are similar to Figure 3 Corresponding to the method embodiments shown, the device can be specifically applied to various electronic devices.

[0118] like Figure 5 As shown, a point cloud map updating device 500 includes: an acquisition unit 501, a screening unit 502, and an updating unit 503. The acquisition unit 501 is configured to acquire a real-time point cloud set corresponding to a target area during movement from a first location to a second location within the target area; the screening unit 502 is configured to screen at least one real-time point cloud representing scene changes from the real-time point cloud set as a to-be-processed point cloud set; and the updating unit 503 is configured to update the point cloud map associated with the target area based on the to-be-processed point cloud set.

[0119] In some optional implementations of some embodiments, the screening unit 502 in the point cloud map updating device 500 is further configured to: remove at least one item of the first real-time point cloud subset and the second real-time point cloud subset from the above-mentioned real-time point cloud set to obtain the real-time point cloud set after removal; and determine the real-time point cloud set after removal as the above-mentioned point cloud set to be processed.

[0120] In some optional implementations of some embodiments, the screening unit 502 in the point cloud map updating device 500 is further configured to: determine the point cloud set in the above-mentioned real-time point cloud set that is a static point cloud as the above-mentioned first real-time point cloud subset; in response to detecting the presence of dynamic point clouds in the above-mentioned real-time point cloud set, determine the point cloud set in the above-mentioned real-time point cloud set that is a dynamic point cloud as the above-mentioned second real-time point cloud subset; remove the above-mentioned first real-time point cloud subset and the above-mentioned second real-time point cloud subset in the above-mentioned real-time point cloud set to obtain the above-mentioned real-time point cloud set after removal.

[0121] In some optional implementations of some embodiments, the screening unit 502 in the point cloud map updating device 500 is further configured to: in response to detecting that there are identical point clouds between the point cloud set corresponding to the above-mentioned point cloud map and the above-mentioned real-time point cloud set, determine at least one identical point cloud between the point cloud set corresponding to the above-mentioned point cloud map and the above-mentioned real-time point cloud set as a target point cloud set; determine the point cloud set associated with the target ground in the point cloud set corresponding to the above-mentioned point cloud map and the above-mentioned target point cloud set as the above-mentioned first real-time point cloud subset.

[0122] In some optional implementations of some embodiments, the update unit 503 in the point cloud map updating device 500 is further configured to: obtain the voxel grid information set corresponding to the above-mentioned target area and the area information corresponding to each voxel grid information in the above-mentioned voxel grid information set; determine the voxel grid information corresponding to each point cloud to be processed in the above-mentioned point cloud set according to the area information corresponding to each voxel grid information in the above-mentioned voxel grid information set, and obtain a voxel grid information subset; determine the point cloud change area information in the above-mentioned target area according to the above-mentioned voxel grid information subset; and update the above-mentioned point cloud map according to the above-mentioned point cloud change area information.

[0123] In some optional implementations of some embodiments, the update unit 503 in the point cloud map updating device 500 is further configured to: obtain index information corresponding to each voxel grid information in the above-mentioned voxel grid information set; determine the index information corresponding to each voxel grid information in the above-mentioned voxel grid information subset according to the index information corresponding to each voxel grid information in the above-mentioned voxel grid information set, and obtain an index information set; determine the number of point cloud associations corresponding to each index information in the above-mentioned index information set; in response to determining that there is at least one index information in the above-mentioned index information set whose corresponding number of point cloud associations is greater than the first target value, determine the index information in the above-mentioned at least one index information whose point cloud association number meets the predetermined condition as the target index information, and obtain the target index information set; determine the voxel grid information set corresponding to the above-mentioned target index information set as the above-mentioned first target voxel grid information set.

[0124] In some optional implementations of some embodiments, the point cloud map updating apparatus 500 further includes: a first determining unit (not shown). The first determining unit may be configured to: for each index information in the index information set, add the number of point cloud associations corresponding to the index information and the second target value to determine the number of point cloud associations corresponding to the index information.

[0125] In some optional implementations of some embodiments, the update unit 503 in the point cloud map updating device 500 is further configured to: determine the number of point cloud associations corresponding to each voxel grid information in the above-mentioned voxel grid information subset; in response to the existence of at least one voxel grid information in the above-mentioned voxel grid information subset whose corresponding point cloud association number is greater than the first target value, determine the voxel grid information in the above-mentioned at least one voxel grid information whose point cloud association number meets the predetermined condition as the first target voxel grid information, and obtain the first target voxel grid information set.

[0126] In some optional implementations of some embodiments, the point cloud map updating apparatus 500 further includes: a second determining unit (not shown). The second determining unit may be configured to: for each voxel grid information in the voxel grid information subset, add the number of point cloud associations corresponding to the voxel grid information and the second target value to determine the number of point cloud associations corresponding to the voxel grid information.

[0127] In some optional implementations of some embodiments, the point cloud map updating apparatus 500 further includes a storage determination unit (not shown). The storage determination unit may be configured to store the first target voxel grid information set and determine the area corresponding to the first target voxel grid information set as the point cloud change area in the target area.

[0128] In some optional implementations of some embodiments, the update unit 503 in the point cloud map updating device 500 is further configured to: perform coordinate conversion on each point cloud to be processed in the above-mentioned point cloud set to generate corresponding map coordinates to obtain a map coordinate set; determine the voxel grid information corresponding to each point cloud to be processed in the above-mentioned point cloud set based on the above-mentioned map coordinate set and the area information corresponding to each voxel grid information in the above-mentioned voxel grid information set to obtain a voxel grid information subset.

[0129] It is understood that the units described in the device 500 are similar to those in the reference Figure 3 Therefore, the operations, features and beneficial effects described above for the method are also applicable to the device 500 and the units included therein, and will not be repeated here.

[0130] Reference below Figure 6 , which shows an electronic device (eg, Figure 1 Schematic diagram of the structure of the electronic device 600. Figure 6 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0131] like Figure 6 As shown, the electronic device 600 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage device 608 into a random access memory (RAM) 603. Various programs and data required for the operation of the electronic device 600 are also stored in the RAM 603. The processing device 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0132] Typically, the following devices may be connected to the I / O interface 605: an input device 606 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 607 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 608 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 609. The communication device 609 may allow the electronic device 600 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 6 The electronic device 600 is shown with various devices, but it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed instead. Figure 6 Each block shown in the figure may represent one device, or may represent multiple devices as needed.

[0133] In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In some such embodiments, the computer program can be downloaded and installed from a network via the communication device 609, or installed from the storage device 608, or installed from the ROM 602. When the computer program is executed by the processing device 601, the above-mentioned functions defined in the method of some embodiments of the present disclosure are performed.

[0134] It should be noted that in some embodiments of the present disclosure, the computer-readable medium mentioned above may be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In some embodiments of the present disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, device, or device. In some embodiments of the present disclosure, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to wires, optical cables, RF (radio frequency), etc., or any suitable combination thereof.

[0135] In some embodiments, the client and server can communicate using any currently known or future developed network protocol, such as HTTP (HyperText Transfer Protocol), and can be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0136] The computer-readable medium may be included in the electronic device, or may exist independently and not be incorporated into the electronic device. The computer-readable medium carries one or more programs. When executed by the electronic device, the electronic device: obtains a real-time point cloud set corresponding to the target area during movement from a first location to a second location within the target area; selects at least one real-time point cloud representing scene changes from the real-time point cloud set as a point cloud set to be processed; and updates a point cloud map associated with the target area based on the point cloud set to be processed.

[0137] Computer program code for performing the operations of some embodiments of the present disclosure may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0138] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the module, program segment, or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0139] The units described in some embodiments of the present disclosure may be implemented by software or by hardware. The described units may also be provided in a processor, for example, they may be described as: a processor comprising an acquisition unit, a screening unit, and an update unit. The names of these units do not, in some cases, constitute a limitation on the units themselves, for example, the acquisition unit may also be described as "a unit for acquiring a real-time point cloud corresponding to the target area in the process of moving from a first location to a second location within the target area".

[0140] The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, and without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chip (SOCs), complex programmable logic devices (CPLDs), and the like.

[0141] The above description is only an illustration of some preferred embodiments of the present disclosure and the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalent features without departing from the above-mentioned inventive concept. For example, the above-mentioned features are replaced with (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure.

Claims

1. A point cloud map updating method, comprising: In the process of moving from a first location to a second location within a target area, obtaining a real-time point cloud set corresponding to the target area; Selecting at least one real-time point cloud representing scene changes from the real-time point cloud set as a point cloud set to be processed; Acquire a voxel grid information set corresponding to the target area and area information corresponding to each voxel grid information in the voxel grid information set; Determine the voxel grid information corresponding to each to-be-processed point cloud in the to-be-processed point cloud set according to the region information corresponding to each voxel grid information in the voxel grid information set, and obtain a voxel grid information subset; According to the voxel grid information subset, point cloud change area information in the target area is determined, wherein the point cloud change area information in the target area is determined according to the voxel grid information subset, including: determining the number of point cloud associations corresponding to each voxel grid information in the voxel grid information subset; in response to the existence of at least one voxel grid information in the voxel grid information subset whose point cloud association number corresponding to the voxel grid information is greater than a first target value, determining the voxel grid information in the at least one voxel grid information whose point cloud association number meets a predetermined condition as the first target voxel grid information, and obtaining the first target voxel grid information set; The point cloud map is updated according to the point cloud change area information.

2. The method according to claim 1, wherein: The step of selecting at least one real-time point cloud representing scene changes from the real-time point cloud set as the point cloud set to be processed includes: Removing at least one item in the first real-time point cloud subset and the second real-time point cloud subset from the real-time point cloud set to obtain a real-time point cloud set after removal; The removed real-time point cloud set is determined as the to-be-processed point cloud set.

3. The method according to claim 2, wherein: The removing at least one item of the first real-time point cloud subset and the second real-time point cloud subset from the real-time point cloud set to obtain the real-time point cloud set after the removal includes: Determine a point cloud set that is a static point cloud in the real-time point cloud set as the first real-time point cloud subset; In response to detecting that there is a dynamic point cloud in the real-time point cloud set, determining a point cloud set in the real-time point cloud set that is a dynamic point cloud as the second real-time point cloud subset; The first real-time point cloud subset and the second real-time point cloud subset in the real-time point cloud set are removed to obtain the real-time point cloud set after the removal.

4. The method according to claim 3, wherein: The step of determining the point cloud set of the real-time point cloud set as a static point cloud as the first real-time point cloud subset comprises: In response to detecting that there are identical point clouds between the point cloud set corresponding to the point cloud map and the real-time point cloud set, determining at least one identical point cloud between the point cloud set corresponding to the point cloud map and the real-time point cloud set as a target point cloud set; The point cloud set associated with the target ground in the point cloud set corresponding to the point cloud map and the target point cloud set are determined as the first real-time point cloud subset.

5. The method according to claim 1, wherein: The step of determining the point cloud change area in the target area according to the voxel grid information subset includes: Obtaining index information corresponding to each voxel grid information in the voxel grid information set; According to the index information corresponding to each voxel grid information in the voxel grid information set, the index information corresponding to each voxel grid information in the voxel grid information subset is determined to obtain an index information set; Determine the number of point cloud associations corresponding to each index information in the index information set; In response to determining that the number of point cloud associations corresponding to at least one index information in the index information set is greater than a first target value, determining the index information whose point cloud association number in the at least one index information meets a predetermined condition as target index information, to obtain a target index information set; The voxel grid information set corresponding to the target index information set is determined as the first target voxel grid information set.

6. The method according to claim 5, wherein: The method further comprises: For each index information in the index information set, a sum of the number of point cloud associations corresponding to the index information and the second target value is determined as the number of point cloud associations corresponding to the index information.

7. The method according to claim 1, wherein: The method further comprises: For each voxel grid information in the voxel grid information subset, a sum of the number of point cloud associations corresponding to the voxel grid information and the second target value is determined as the number of point cloud associations corresponding to the voxel grid information.

8. The method according to claim 1, wherein: The method further comprises: The first target voxel grid information set is stored, and an area corresponding to the first target voxel grid information set is determined as a point cloud change area in the target area.

9. The method according to claim 1, wherein: The step of determining the voxel grid information corresponding to each to-be-processed point cloud in the to-be-processed point cloud set according to the region information corresponding to each voxel grid information in the voxel grid information set, and obtaining the voxel grid information subset, comprises: Performing coordinate transformation on each point cloud to be processed in the point cloud set to be processed to generate corresponding map coordinates to obtain a map coordinate set; According to the map coordinate set and the area information corresponding to each voxel grid information in the voxel grid information set, the voxel grid information corresponding to each to-be-processed point cloud in the to-be-processed point cloud set is determined to obtain a voxel grid information subset.

10. A point cloud map updating device, comprising: An acquisition unit is configured to acquire a real-time point cloud set corresponding to the target area during movement from a first location to a second location in the target area; A screening unit, configured to screen at least one real-time point cloud representing scene changes from the real-time point cloud set as a point cloud set to be processed; An updating unit is configured to obtain a voxel grid information set corresponding to the target area and region information corresponding to each voxel grid information in the voxel grid information set; determine the voxel grid information corresponding to each to-be-processed point cloud in the to-be-processed point cloud set according to the region information corresponding to each voxel grid information in the voxel grid information set, and obtain a voxel grid information subset; According to the voxel grid information subset, point cloud change area information in the target area is determined, wherein the point cloud change area information in the target area is determined according to the voxel grid information subset, including: determining the number of point cloud associations corresponding to each voxel grid information in the voxel grid information subset; in response to the existence of at least one voxel grid information in the voxel grid information subset whose corresponding point cloud association number is greater than a first target value, determining the voxel grid information whose point cloud association number in the at least one voxel grid information meets a predetermined condition as the first target voxel grid information, and obtaining a first target voxel grid information set; according to the point cloud change area information, the point cloud map is updated.

11. An electronic device, comprising: one or more processors; a storage device having one or more programs stored thereon, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 9.

12. A computer readable medium having a computer program stored thereon, wherein: When the program is executed by a processor, the method according to any one of claims 1 to 9 is implemented.

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