CN113838162A - Laser mapping method and device and computer readable storage medium - Google Patents
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Abstract
The invention discloses a laser mapping method, a device and a computer readable storage medium. Wherein, the method comprises the following steps: determining a first initial position in a first map, and establishing a second map according to the first initial position; selecting a plurality of first nodes from the first map, selecting a plurality of second nodes corresponding to the first nodes from the second map, and forming relationship nodes by each first node and the corresponding second node; splicing two pieces of laser point clouds corresponding to two nodes in each pair of the relation nodes to obtain a pose change matrix between each pair of the relation nodes; and fusing the first map and the second map according to the pose transformation matrix. The laser mapping scheme with low cost is realized, the large consumption of processing resources is avoided, the requirement on the hardware processing performance is reduced, and the mapping efficiency is improved.
Description
Technical Field
The invention relates to the technical field of robots, in particular to a laser mapping method, laser mapping equipment and a computer readable storage medium.
Background
In the field of existing robot control technology, slam (simultaneous localization and Mapping) is commonly used, which is also called cml (coordinated localization and localization), and may also be called instant localization and Mapping, or concurrent Mapping and localization. The technology enables the mobile robot to collect information of the operation environment through various sensors, so that a map of a site is built autonomously, further, self pose information is calculated according to the map, and a required safety movement function is completed.
It can be understood that the map is a kind of perception of the robot to the environment, and the robot knows the position of the robot and generates the most suitable traveling path, so as to reach the target position to be reached more quickly and accurately. Therefore, a very detailed map needs to be built to enable the robot to move freely accurately and efficiently.
However, the more detailed the map to be created, the larger the range of the map to be created, and the higher the requirements on the hardware performance of the robot. As is known, in the background of some period of technology, the performance of a single piece of hardware cannot completely meet the current task requirement, so in the prior art, when a map is built in a wider range, a higher hardware cost is usually required, and at the same time, the efficiency of the map building operation is low due to the limitation of the hardware performance.
Disclosure of Invention
In order to solve the technical defects in the prior art, the invention provides a laser mapping method, which comprises the following steps:
determining a first initial position in a first map, and establishing a second map according to the first initial position;
selecting a plurality of first nodes from the first map, selecting a plurality of second nodes corresponding to the first nodes from the second map, and forming relationship nodes by each first node and the corresponding second node;
splicing two pieces of laser point clouds corresponding to two nodes in each pair of the relation nodes to obtain a pose change matrix between each pair of the relation nodes;
and fusing the first map and the second map according to the pose transformation matrix.
Optionally, before determining a first initial position in the first map and establishing the second map with the first initial position, the method further includes:
and taking a map created from a first time to a second time as the first map, or reading a stored map at the second time as the first map.
Optionally, the determining a first initial position in a first map and building a second map with the first initial position includes:
and taking the map created from the second time to the third time as the second map.
Optionally, the selecting a plurality of first nodes from the first map, and simultaneously selecting a plurality of second nodes corresponding to the first nodes from the second map, where each first node and the corresponding second node form a relationship node, includes:
selecting the first nodes one by one in the first map;
in the second map, acquiring a distance value between each node and the first node;
and taking the node with the minimum distance value as a second node corresponding to the first node.
Optionally, the selecting a plurality of first nodes from the first map, and simultaneously selecting a plurality of second nodes corresponding to the first nodes from the second map, where each first node and the corresponding second node form a relationship node, further includes:
presetting a distance threshold value with two nodes in a pair relationship;
and if the distance value between the first node and the second node corresponding to the first node is smaller than the distance threshold value, the first node and the second node corresponding to the first node are combined into the relationship node.
Optionally, the stitching two pieces of laser point clouds corresponding to two nodes in each pair of the relationship nodes to obtain a pose change matrix between each pair of the relationship nodes includes:
acquiring a first laser point cloud corresponding to the first node, and acquiring a second laser point cloud corresponding to the second node;
and splicing the first laser point cloud and the second laser point cloud to obtain a pose transformation matrix between the first node and the second node.
Optionally, the fusing the first map and the second map according to the pose transformation matrix includes:
and obtaining a covariance matrix between each pair of the relationship nodes according to the pose transformation matrix between each pair of the relationship nodes, and fusing and optimizing the first map and the second map according to the covariance matrix to obtain a new first map formed by the first map and the second map.
Optionally, the method further comprises:
and circularly executing the fusion and optimization of the first map and the second map until the map building operation is completed.
Optionally, the present invention further provides a laser mapping apparatus, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and when executed by the processor, the computer program implements the steps of the laser mapping method described above.
Optionally, the present invention further provides a computer-readable storage medium, on which a laser mapping program is stored, which, when executed by a processor, implements the steps of the laser mapping method as described above.
The laser mapping method, the device and the computer readable storage medium of the invention are implemented by determining a first initial position in a first map and establishing a second map by using the first initial position; selecting a plurality of first nodes from the first map, selecting a plurality of second nodes corresponding to the first nodes from the second map, and forming relationship nodes by each first node and the corresponding second node; splicing two pieces of laser point clouds corresponding to two nodes in each pair of the relation nodes to obtain a pose change matrix between each pair of the relation nodes; and fusing the first map and the second map according to the pose transformation matrix. The laser mapping scheme with low cost is realized, the large consumption of processing resources is avoided, the requirement on the hardware processing performance is reduced, and the mapping efficiency is improved.
Drawings
The invention will be further described with reference to the accompanying drawings and examples, in which:
fig. 1 is a first flowchart of a laser mapping method according to an embodiment of the present invention.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In the following description, suffixes such as "module", "component", or "unit" used to denote elements are used only for facilitating the explanation of the present invention, and have no specific meaning in itself. Thus, "module", "component" or "unit" may be used mixedly.
Example one
Fig. 1 is a first flowchart of a laser mapping method according to an embodiment of the present invention. The embodiment provides a laser mapping method, which comprises the following steps:
s1, determining a first initial position in the first map, and establishing a second map according to the first initial position;
s2, selecting a plurality of first nodes from the first map, and simultaneously selecting a plurality of second nodes corresponding to the first nodes from the second map, wherein each first node and the corresponding second node form a relationship node;
s3, splicing two pieces of laser point clouds corresponding to two nodes in each pair of relationship nodes to obtain a pose change matrix between each pair of relationship nodes;
and S4, fusing the first map and the second map according to the pose transformation matrix.
In this embodiment, an initial block map is determined as a first map of this embodiment, and then an initial position is selected from the first map as a first initial position of this embodiment, where the first initial position may be a last position when a new block map is created, or a position obtained by repositioning on the block map. In this embodiment, after the first initial position in the first map is determined, the second map is established with the first initial position as a starting point, and similarly, the second map may be regarded as another block map after the first map is established.
In this embodiment, after the establishment of the first map and the second map is successively completed, a plurality of first nodes are selected in a traversal manner in the node index of the first map, and meanwhile, a plurality of second nodes corresponding to the first nodes are also selected in a traversal manner in the node index of the second map, where the first nodes and the second nodes have a certain association relationship, so that each first node and the corresponding second node form a pair of relationship nodes.
In this embodiment, after all pairs of relationship nodes between the first map and the second map are extracted, two pieces of laser point clouds corresponding to two nodes in each pair of relationship nodes are spliced to obtain a pose change matrix between each pair of relationship nodes. It should be noted that, in the first map and the second map obtained by laser mapping, each first node or second node corresponds to a piece of laser point cloud, which is a set of points returned by a laser sensor scanning a circle of the environment, each pair of relationship nodes obtained in this embodiment includes two nodes, the two nodes correspond to a piece of laser point cloud, and the position and orientation conversion matrix between the relationship nodes can be obtained by performing Iterative Closest Point (ICP) stitching on the two pieces of laser point clouds.
In this embodiment, after the pose transformation matrix of each pair of relationship nodes is obtained, the first map and the second map are fused according to the pose transformation matrix, and further, the fused map is optimized to obtain a complete map composed of the first map and the second map.
The method has the advantages that the first initial position is determined in the first map, and the second map is established according to the first initial position; selecting a plurality of first nodes from the first map, selecting a plurality of second nodes corresponding to the first nodes from the second map, and forming relationship nodes by each first node and the corresponding second node; splicing two pieces of laser point clouds corresponding to two nodes in each pair of the relation nodes to obtain a pose change matrix between each pair of the relation nodes; and fusing the first map and the second map according to the pose transformation matrix. The laser mapping scheme with low cost is realized, the large consumption of processing resources is avoided, the requirement on the hardware processing performance is reduced, and the mapping efficiency is improved.
Example two
Based on the above-described embodiment, in order to further determine the respective map blocks, in the present embodiment, the first map and the second map are determined continuously or sequentially. Specifically, the method comprises the following steps:
and taking a map created from a first time to a second time as the first map, or reading a stored map at the second time as the first map.
Optionally, in a new map task, if the establishment of the first map is not completed, taking the map created from the first time to the second time as the first map;
optionally, in a new map task, if the establishment of the first map is completed, the stored map is read as the first map at the second time.
The method has the advantages that the map created from the first moment to the second moment is used as the first map, or the stored map is read at the second moment and used as the first map, so that the determination mode of each map block is more flexible, and the robot can conveniently adjust and fuse each map block in time by combining the current mapping environment and mapping progress when mapping blocks.
EXAMPLE III
Based on the above-described embodiment, in order to further determine the respective map blocks, in the present embodiment, the first map and the second map are determined continuously or sequentially. Specifically, the method comprises the following steps:
and taking the map created from the second time to the third time as the second map.
It should be noted that the process of map building is continuous, and in one map building task, after the first map is built, the block map built subsequently is used as the second map.
Optionally, in a map new task, if the establishment of the second map is not completed, one or more maps created from the second time to the third time are used as the second map;
optionally, in a new map task, if the establishment of a second map is completed, reading one or more map blocks which are stored and different from the first map at the third moment as the second map;
optionally, the block establishment scheme of the first map and the second map is determined according to a mapping strategy such as a movement distance, a duration, a position, a location area, a mapping instruction and the like in the mapping process.
The method has the advantages that the map created from the second moment to the third moment is used as the second map, so that the determination mode of each map block is more flexible, and the robot can timely adjust and fuse each map block by combining the current map creating environment and the map creating progress when building the map in blocks.
Example four
Based on the foregoing embodiment, in order to further determine a fusion manner of the first map and the second map, in this embodiment, the extracting the association point of the first map and the second map specifically includes:
firstly, selecting the first nodes one by one in the first map;
then, in the second map, the distance value between each node and the first node is obtained;
and finally, taking the node with the minimum distance value as a second node corresponding to the first node.
Each node is stored in the first map and the second map in an array or linked list mode, therefore, firstly, each node is selected one by one in the first map in a traversal mode to be used as a first node, and then, when one node is selected in the first map to be used as a first node, in the second map, the distance value between each node in the second map and the first node is obtained in the traversal mode; and finally, judging the size relationship between each node in the second map and the distance value of the first node, taking the node with the minimum distance value with the first node as a second node to be extracted, and taking the node as the second node corresponding to the first node.
Optionally, selecting first nodes one by one, and selecting second nodes corresponding to the first nodes one by one;
optionally, distance values between all the first nodes and all the nodes in the second map are calculated, and the node with the minimum distance value corresponding to each first node is extracted as the corresponding second node.
The method has the advantages that the first nodes are selected one by one in the first map; then, in the second map, the distance value between each node and the first node is obtained; and finally, taking the node with the minimum distance value as a second node corresponding to the first node. Thereby providing an association basis for subsequent fusion of the first map and the second map.
EXAMPLE five
Based on the above embodiment, in order to further determine the association relationship between the first map and the second map association point, in the present embodiment:
firstly, presetting a distance threshold value with two nodes in a pair relationship;
then, judging the magnitude relation between the distance value between the first node and the second node corresponding to the first node and the distance threshold, and if the distance value between the first node and the second node corresponding to the first node is smaller than the distance threshold, combining the first node and the second node corresponding to the first node into the relation node.
Optionally, the distance threshold is determined according to an experimental value or an empirical value;
optionally, if the distance value between one first node and a plurality of second nodes is smaller than the distance threshold, a relationship node formed by the second nodes smaller than the distance threshold and the first node is determined;
optionally, if the distance value between one first node and the plurality of second nodes is smaller than the distance threshold, the second node with the smallest distance value and the first node form a relationship node.
The method has the advantages that the distance threshold value with the paired relation of the two nodes is preset; then, judging the magnitude relation between the distance value between the first node and the second node corresponding to the first node and the distance threshold, and if the distance value between the first node and the second node corresponding to the first node is smaller than the distance threshold, combining the first node and the second node corresponding to the first node into the relation node. Therefore, clearer and more accurate relationship nodes are provided for the subsequent fusion of the first map and the second map.
EXAMPLE six
Based on the above embodiment, after each pair of relationship nodes is determined, two pieces of laser point clouds corresponding to two nodes in each pair of relationship nodes are spliced to obtain a pose change matrix between each pair of relationship nodes, which specifically includes:
firstly, acquiring a first laser point cloud corresponding to a first node, and simultaneously acquiring a second laser point cloud corresponding to a second node;
and then, splicing the first laser point cloud and the second laser point cloud to obtain a pose transformation matrix between the first node and the second node.
Optionally, first determining all the relationship nodes, and then stitching two pieces of laser point clouds corresponding to two nodes in each pair of the relationship nodes.
The method has the advantages that the first laser point cloud corresponding to the first node is obtained, and meanwhile, the second laser point cloud corresponding to the second node is obtained; and then, splicing the first laser point cloud and the second laser point cloud to obtain a pose transformation matrix between the first node and the second node. The method and the device realize the associated splicing of the first map and the second map, thereby avoiding the excessive consumption of processing resources and hardware resources caused by the single establishment of large-scale maps.
EXAMPLE seven
Based on the above embodiment, after the first map and the second map are fused according to the pose transformation matrix, the fused map is optimized, specifically:
and obtaining a covariance matrix between each pair of the relationship nodes according to the pose transformation matrix between each pair of the relationship nodes, and fusing and optimizing the first map and the second map according to the covariance matrix to obtain a new first map formed by the first map and the second map.
Optionally, optimizing the fused map by using a light beam adjustment method;
optionally, if in a mapping task, the second map is the last map block in the area range, generating a final map of the mapping task;
optionally, if the second map is not the last map segment in the area in one mapping task, the map formed by the first map and the second map is used as a new first map, so as to continue to perform the subsequent segment map building and fusing steps.
The method has the advantages that the covariance matrix between each pair of the relationship nodes is obtained through the pose transformation matrix between each pair of the relationship nodes, and the first map and the second map are fused and optimized according to the covariance matrix to obtain the new first map formed by the first map and the second map. Therefore, the associated splicing of each block map in the map building task is realized, and the excessive consumption of processing resources and hardware resources caused by the single building of a large-scale map is avoided.
Example eight
Based on the embodiment, in one mapping task, one mapping robot circularly executes the fusion and optimization of the first map and the second map until the mapping operation is completed;
optionally, in the same mapping task, each mapping robot circularly executes the fusion and optimization of the corresponding first map and second map until the mapping operation is completed;
optionally, in a primary mapping task, a map partition is selected and read as a first map for an area in which mapping has been completed, then an initial position is obtained after relocation, a new second map is established on the basis, and finally the second map is fused with the first map, so that the completed map area can be removed or changed.
The method has the advantages that the fusion and optimization of the first map and the second map are executed in a circulating mode until the mapping operation is completed, the associated splicing of each block map in the mapping task is achieved successively, the flexibility of map building or map modification is higher, the excessive consumption of processing resources and hardware resources caused by single map building or map modification in a specific area is avoided, and the operation efficiency and accuracy of map building or map modification are improved.
Example nine
Based on the foregoing embodiments, the present invention further provides a laser mapping apparatus, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the computer program, when executed by the processor, implements the steps of the laser mapping method described above.
It should be noted that the device embodiment and the method embodiment belong to the same concept, and specific implementation processes thereof are detailed in the method embodiment, and technical features in the method embodiment are correspondingly applicable in the device embodiment, which is not described herein again.
Example ten
Based on the above embodiment, the present invention further provides a computer-readable storage medium, on which a laser mapping program is stored, and the laser mapping program, when executed by a processor, implements the steps of the laser mapping method described above.
It should be noted that the media embodiment and the method embodiment belong to the same concept, and specific implementation processes thereof are detailed in the method embodiment, and technical features in the method embodiment are correspondingly applicable in the media embodiment, which is not described herein again.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (10)
1. A method of laser mapping, the method comprising:
determining a first initial position in a first map, and establishing a second map according to the first initial position;
selecting a plurality of first nodes from the first map, selecting a plurality of second nodes corresponding to the first nodes from the second map, and forming relationship nodes by each first node and the corresponding second node;
splicing two pieces of laser point clouds corresponding to two nodes in each pair of the relation nodes to obtain a pose change matrix between each pair of the relation nodes;
and fusing the first map and the second map according to the pose transformation matrix.
2. The laser mapping method of claim 1, wherein before determining a first initial position in a first map and building a second map with the first initial position, the method further comprises:
and taking a map created from a first time to a second time as the first map, or reading a stored map at the second time as the first map.
3. The laser mapping method of claim 2, wherein determining a first initial position in a first map and building a second map with the first initial position comprises:
and taking the map created from the second time to the third time as the second map.
4. The laser mapping method according to claim 1, wherein the selecting a plurality of first nodes in the first map and a plurality of second nodes corresponding to the first nodes in the second map, and the forming a relationship node by each first node and its corresponding second node comprises:
selecting the first nodes one by one in the first map;
in the second map, acquiring a distance value between each node and the first node;
and taking the node with the minimum distance value as a second node corresponding to the first node.
5. The laser mapping method according to claim 4, wherein the selecting a plurality of first nodes in the first map and a plurality of second nodes corresponding to the first nodes in the second map, and a relationship node is formed by each first node and the corresponding second node, further comprises:
presetting a distance threshold value with two nodes in a pair relationship;
and if the distance value between the first node and the second node corresponding to the first node is smaller than the distance threshold value, the first node and the second node corresponding to the first node are combined into the relationship node.
6. The laser mapping method according to claim 1, wherein the stitching two pieces of laser point clouds corresponding to two nodes in each pair of the relationship nodes to obtain a pose change matrix between each pair of the relationship nodes includes:
acquiring a first laser point cloud corresponding to the first node, and acquiring a second laser point cloud corresponding to the second node;
and splicing the first laser point cloud and the second laser point cloud to obtain a pose transformation matrix between the first node and the second node.
7. The laser mapping method of claim 6, wherein the fusing the first map and the second map according to the pose transformation matrix comprises:
and obtaining a covariance matrix between each pair of the relationship nodes according to the pose transformation matrix between each pair of the relationship nodes, and fusing and optimizing the first map and the second map according to the covariance matrix to obtain a new first map formed by the first map and the second map.
8. The laser mapping method of claim 7, further comprising:
and circularly executing the fusion and optimization of the first map and the second map until the map building operation is completed.
9. Laser mapping apparatus, characterized in that the apparatus comprises a memory, a processor and a computer program stored on the memory and executable on the processor, which computer program, when executed by the processor, implements the steps of the laser mapping method according to any of claims 1 to 8.
10. A computer-readable storage medium, having stored thereon a laser mapping program which, when executed by a processor, implements the steps of the laser mapping method according to any one of claims 1 to 8.
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| CN107796397A (en) * | 2017-09-14 | 2018-03-13 | 杭州迦智科技有限公司 | A kind of Robot Binocular Vision localization method, device and storage medium |
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