CN111426316B - Robot positioning method and device, robot and readable storage medium - Google Patents
Robot positioning method and device, robot and readable storage medium Download PDFInfo
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- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
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- G—PHYSICS
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- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
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Abstract
The application provides a robot positioning method, a device, a robot and a readable storage medium, wherein the method comprises the following steps: acquiring current first position and attitude information obtained in an AMCL mode and current second position and attitude information issued by a multi-source sensor; when the current first position information is invalid, determining a target mapping relation corresponding to the current second position information from a preset mapping relation set; the set of mapping relationships is a set of mapping relationships corresponding to the first posture information and the second posture information at the same time point, which are recorded when the first posture information is valid. And then, carrying out reverse mapping processing on the current second pose information according to the target mapping relation to obtain target first pose information, wherein the target first pose information represents the current actual pose of the robot. Therefore, the application of the pose information of the sensor to the SLAM is realized, and the problem that the pose information of the multi-source sensor cannot be applied to the SLAM at present and the positioning of the robot is not matched is solved.
Description
Technical Field
The application relates to the technical field of robots, in particular to a robot positioning method and device, a robot and a readable storage medium.
Background
The service robot has a complex working environment, the environment changes at any time, and the service robot is influenced and interfered by the outside, so if the navigation task is to be completed in an indoor environment independently, the global position of the robot in the environment needs to be known, namely the robot needs to have the indoor independent positioning capability.
At present, there are many methods for robot positioning, mainly including GNSS (Global Navigation satellite system), laser SLAM (simultaneous localization and mapping, instant positioning and map construction), visual SLAM, odometer, IMU (Inertial Measurement Unit), WIFI, bluetooth, infrared, and the like. However, each method, when taken alone, presents more or less problematic problems.
Therefore, the industry has come to use the multi-sensor complementary feature to overcome the disadvantage of a single sensor, i.e. to apply sensors such as WIFI, GNSS, UWB (Ultra-Wideband) to SLAM. At the moment, the problems of non-uniform position information variance estimation information and non-uniform map among a plurality of sensors (namely, multisource sensors) exist, and the problem of non-matching positioning of the robot is caused because the pose information of the multisource sensors cannot be applied to SLAM.
Disclosure of Invention
An object of the embodiments of the present application is to provide a robot positioning method, an apparatus, a robot, and a readable storage medium, so as to solve the problem that the pose information of the current sensor cannot be applied to SLAM, which results in the positioning of the robot being mismatched.
The embodiment of the application provides a robot positioning method, which comprises the following steps: acquiring current first attitude information obtained in an AMCL (adaptive Monte Carlo Localization) mode and current second attitude information issued by a multi-source sensor; when the current first position information is invalid, determining a target mapping relation corresponding to the current second position information from a preset mapping relation set; the mapping relation set is a set of the mapping relations of the first posture information and the second posture information which are recorded when the first posture information is effective and correspond to the same time point; and according to the target mapping relation, performing reverse mapping processing on the current second pose information to obtain target first pose information obtained by mapping the current second pose information, wherein the target first pose information represents the current actual pose of the robot.
In the implementation process, when the first position and posture information obtained in the AMCL mode is valid, the mapping relation between the first position and posture information corresponding to the same time point is constructed, so that when the AMCL mode is invalid, the corresponding target first position and posture information in the AMCL mode can be reversely estimated based on the current second position and posture information issued by the multi-source sensor, and further the robot is positioned. Therefore, the application of the pose information of the sensor to the SLAM is realized, and the problem that the pose information of the multi-source sensor cannot be applied to the SLAM at present and the positioning of the robot is not matched is solved.
Further, the method further comprises: and when the current first pose information is effective, the current first pose information represents the current actual pose of the robot.
Further, the method further comprises: when the current first position information is effective, calculating the translation amount and the rotation amount between the current first position information and the current second position information; associating the translation amount and the rotation amount with a grid in a map where the current first attitude information is located; and the translation amount and the rotation amount represent the mapping relation between the current first position and attitude information and the current second position and attitude information.
In practical application, two different positioning modes often have a certain deviation amount during positioning, and the deviation amount usually includes a translation amount and a rotation amount between positioning positions in two pose information. It should be noted that, in the AMCL method, the map is essentially rasterized into a plurality of meshes, the robot is located by the number of particles in the map mesh, and the location of the AMCL method is essentially the location of the mesh where the robot is most likely to be located. In the implementation process, the grid is taken as a unit, and when the current first position information is valid, the translation amount and the rotation amount between the current first position information and the current second position information are taken as the mapping relationship, so as to construct the mapping relationship between the first position information and the second position information.
Further, the determining a target mapping relationship corresponding to the current second position information from a preset mapping relationship set includes: determining a first target grid corresponding to the current second attitude information in the map; extracting a mapping relation corresponding to the first target grid; and the mapping relation corresponding to the first target grid represents the target mapping relation corresponding to the current second position information.
Further, determining a first target grid corresponding to the second pose information in the map includes: acquiring reference point pose information corresponding to a preset reference point in the map; determining a position deviation of the current second position and posture information and the reference point position and posture information; and determining a first target grid corresponding to the current second position information in the map according to the position deviation and the reference point.
In the implementation process, coordinate systems corresponding to the multi-source sensor and the AMCL are usually different, so that grid determination of the current second posture information in the map can be realized by setting a reference point, and further, the feasibility of the scheme is ensured.
Further, when the mapping relationship corresponding to the first target grid is empty, the method further includes: retrieving a second target grid closest to the first target grid; the second target grid is a grid of which the corresponding mapping relation is not empty; extracting a mapping relation corresponding to the second target grid; and the mapping relation corresponding to the second target grid is a target mapping relation corresponding to the current second position information.
In practical applications, there may be some cases where the grids do not have a mapping relationship. Generally, the actions of the robot are continuous, and therefore, the mapping relationship between adjacent grids often has certain similarity. Therefore, in the embodiment of the present application, the mapping relationship in the second target grid closest to the first target grid may be obtained as the target mapping relationship corresponding to the current second pose information, so that the target first pose information is obtained through reverse mapping processing, and the feasibility of the scheme is ensured.
Further, the first pose information is pose information obtained in a laser map in an AMCL mode; when the mapping relationship corresponding to the first target grid is empty, the method further includes: determining the position of a target laser point corresponding to the target first position information according to the target first position information; matching the position of the target laser point with the position of an actual laser point in the map; and when the proportion of the target laser points matched with the actual laser points is larger than a preset threshold value, associating the mapping relation corresponding to the second target grid with the first target grid.
In the practical application process, when laser SLAM positioning is adopted, corresponding laser point information is usually acquired. The laser spot information is information of a spot scanned by the robot when the laser scanning is performed, and the installation position of the laser spot is set in advance and recorded in a map. When the positioning is carried out through the laser SLAM, the positioning can be realized by utilizing an AMCL algorithm according to the information of the laser spot scanned at present. Similarly, based on the positioning result of the AMCL algorithm, it can be deduced reversely which laser spot is scanned currently. Based on the above, in the embodiment of the present application, after the first position information of the target is obtained, the position of the corresponding target laser point can be obtained by reverse estimation. It should be understood that, since the target first position information is an estimated positioning result obtained by inverse mapping based on the current second position information, the laser point position (i.e. the target laser point position) if the target first position information is to be obtained can be obtained by inverse estimation based on the target first position information. And then the position of the target laser point can be matched with the position of the actual laser point in the map. If the ratio of the target laser points matched with the actual laser points is larger than the preset threshold, the first position information of the target can be considered to be relatively accurate, and the adopted target mapping relation (namely the mapping relation corresponding to the second target grid) is in accordance with the reality, so that the mapping relation corresponding to the second target grid can be associated with the first target grid, and the completeness of the mapping relation is improved.
The embodiment of the present application further provides a robot positioning device, including: the device comprises an acquisition module, a determination module and a processing module; the acquisition module is used for acquiring current first position and attitude information obtained by a self-adaptive Monte Carlo positioning AMCL mode and current second position and attitude information issued by a multi-source sensor; the determining module is configured to determine, from a preset mapping relationship set, a target mapping relationship corresponding to the current second pose information when the current first pose information is invalid; the mapping relation set is a set of the mapping relations of the first posture information and the second posture information which are recorded when the first posture information is effective and correspond to the same time point; the processing module is used for carrying out reverse mapping processing on the current second pose information according to the target mapping relation to obtain target first pose information obtained by mapping the current second pose information, and the target first pose information represents the current actual pose of the robot.
An embodiment of the present application further provides a robot, including: a processor, a memory, and a communication bus; the communication bus is used for realizing connection communication between the processor and the memory; the processor is configured to execute one or more programs stored in the memory to implement any of the above-described robot positioning methods.
Also provided in an embodiment of the present application is a readable storage medium storing one or more programs, the one or more programs being executable by one or more processors to implement the robot positioning method of any one of the above.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a schematic flowchart of a robot positioning method according to an embodiment of the present disclosure;
fig. 2 is a schematic diagram of a grid according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a grid search system according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a robot positioning device according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of a robot according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.
The first embodiment is as follows:
the embodiment of the application provides a robot positioning method, and as shown in fig. 1, the method comprises the following steps:
s101: and acquiring current first position and attitude information obtained in an AMCL mode and current second position and attitude information issued by a multi-source sensor.
It should be understood that AMCL is a method that uses particle filtering to locate the position of the robot by scattering a large number of particles. The AMCL is widely applied to various positioning modes, such as WIFI positioning, laser SLAM positioning and the like.
In the embodiment of the application, the robot may obtain, through the multi-source sensor (e.g., one or more sensors of WIFI, GNSS, UWB, IMU, odometer, etc.) set by the robot, second position and orientation information issued by the multi-source sensor, in addition to the first position and orientation information obtained by the AMCL.
Generally, due to different positioning modes, the first pose information and the second pose information are often not described by using the same coordinate system, that is, for a robot at the same time point and the same pose, the pose information description modes corresponding to the robot at the same time point and the same pose often have a certain difference. Therefore, in the embodiment of the present application, a mapping relationship between the first posture information and the second posture information may be established according to the first posture information and the second posture information acquired at the same time point.
In the embodiment of the present application, the mapping relationship between the first and second position information may include the amount of translation and the amount of rotation therebetween.
It should be appreciated that in the robot positioning problem, the transformation between different coordinate systems for the same pose can be generally described by a rotation matrix and a translation vector. And the translation amount (i.e. the translation vector) and the rotation amount (i.e. the rotation matrix) can be effectively calculated by knowing the pose information (i.e. the first pose information and the second pose information) of the two coordinate systems. The mapping relation of the first position and the second position information corresponding to the same pose of the robot at the same time can be represented through the translation amount and the rotation amount.
It should be noted that, when the robot performs AMCL positioning, corresponding confidence data is also output, so that whether the first pose information currently positioned by the robot is valid can be determined according to the confidence data.
In order to ensure the reliability of the mapping relationship, in the embodiment of the present application, the corresponding mapping relationship may be extracted and stored only when the first pose information is valid. When the first posture information is invalid, the following steps in the embodiment of the present application may be performed.
S102: and when the current first position information is invalid, determining a target mapping relation corresponding to the current second position information from a preset mapping relation set.
In the embodiment of the application, when the current first pose information is valid, the current first pose information can be directly used as the actual pose information of the robot for issuing.
Before the positioning is performed by the AMCL method, the map needs to be rasterized into a plurality of meshes, so that the number distribution of particles in the map meshes realizes the positioning of the robot, and the mesh with the most dense particles is used as the position of the robot.
Therefore, in the embodiment of the present application, the mapping relationship may be recorded in units of grids. The mapping relation corresponding to each grid forms a mapping relation set.
In this embodiment of the present application, a corresponding rotation matrix may be set for each grid, and when the current first pose information is valid, the translation amount and the rotation amount between the current first pose information and the current second pose information are extracted and associated with the grid where the current first pose information is located, so as to store the mapping relationship between the current first pose information and the current second pose information.
In this embodiment of the application, when the current first pose information is invalid, a first target grid corresponding to the current second pose information in a map may be determined according to the current second pose information, and then a mapping relationship corresponding to the first target grid is extracted, and the mapping relationship corresponding to the first target grid is used as a target mapping relationship corresponding to the current second pose information.
In order to facilitate determining the first target grid corresponding to the current second pose information in the map, in the embodiment of the present application, a reference point may be preset in the map, the second pose information corresponding to the reference point is obtained in advance, and the second pose information is used as the reference point pose information corresponding to the reference point. And then, the current second position and attitude information can be brought into the map based on the position deviation between the current second position and attitude information of the reference point, and the position deviation amount is deviated from the reference point in the map, so that the first target grid corresponding to the current second position and attitude information in the map is obtained.
For example, the maximum point position or the minimum point position in the map may be used as the reference point.
It should be understood that in the actual application process, there may be some cases where the grid has not yet been mapped. At this time, if the mapping relationship of the first target grid corresponding to the current second pose information in the map is empty, in order to ensure that effective positioning of the robot can be realized, a second target grid which is closest to the first target grid and is not empty can be searched in the map, and the mapping relationship corresponding to the second target grid is used as the target mapping relationship corresponding to the current second pose information.
For example, as shown in fig. 2, the white grid in fig. 2 is a grid that does not have a mapping relationship at present, and the black grid is a grid that has a mapping relationship. And if the first target grid corresponding to the current second attitude information in the map is a black grid, directly extracting the mapping relation corresponding to the first target grid as the target mapping relation corresponding to the current second attitude information. And if the first target grid corresponding to the second position information in the map is a white grid, searching a black grid closest to the first target grid, and extracting a mapping relation corresponding to the black grid as a target mapping relation corresponding to the current second position information.
In the embodiment of the present application, the search for the second target grid may be implemented by a near-to-far hierarchical search or a cross-shaped ordered search.
Illustratively, referring to fig. 3, the white mesh in fig. 3 is a mesh that does not currently have a mapping relationship, the black mesh is a mesh that has a mapping relationship, and the mesh where the black triangle is located is the first target mesh. In the search, the search may be performed sequentially in the order of the arrow direction in fig. 3. It should be understood that the search sequence in fig. 3 is only one possible search sequence exemplified in the present application, and in the practical application, the search sequence can be freely set by an engineer according to practical needs.
S103: and according to the target mapping relation, carrying out reverse mapping processing on the current second position information to obtain the target first position information obtained by mapping the current second position information.
In the embodiment of the present application, the reverse mapping process refers to a reverse mapping process when mapping from the first posture information to the second posture information.
In the embodiment of the application, after the first pose information of the target is obtained, the first pose information of the target can be used as the current actual pose of the robot.
In the embodiment of the present application, the first position information may be positioning based on a laser SLAM. Namely, a laser map can be constructed by the laser SLAM, and corresponding first attitude information can be obtained in the laser map by the AMCL method.
In the embodiment of the present application, when positioning is implemented based on the laser SLAM, corresponding laser point information is generally collected. The laser spot information is information of a spot scanned by the robot when the laser scanning is performed, and the installation position of the laser spot is set in advance and recorded in a map. When the positioning is carried out through the laser SLAM, the positioning can be realized by utilizing an AMCL algorithm according to the information of the laser spot scanned at present. Similarly, based on the positioning result of the AMCL algorithm, it can be deduced reversely which laser spot is scanned currently.
Therefore, in the embodiment of the present application, if the target first position information is obtained through the mapping relationship corresponding to the second target grid, the position of the target laser point corresponding to the target first position information may be determined according to the target first position information, and then the position of the target laser point may be matched with the position of the actual laser point in the map, and when the proportion of the target laser point matched with the actual laser point is greater than the preset threshold, the mapping relationship corresponding to the second target grid is associated with the first target grid, so as to facilitate subsequent use.
It should be understood that, in the embodiment of the present application, the matching of the target laser point position and the actual laser point position may be that the target laser point position coincides with the actual laser point position. In addition, the matching between the target laser point position and the actual laser point position may be that the position deviation between the target laser point position and the actual laser point position is within a preset deviation range.
In the embodiment of the present application, a specific matching principle between the target laser point position and the actual laser point position may be set by an engineer according to actual needs.
In addition, in the embodiment of the present application, the preset threshold of the ratio of the target laser point to the actual laser point may also be set by an engineer according to actual needs.
According to the robot positioning method provided by the embodiment of the application, when the first attitude information obtained in the AMCL mode is valid, the mapping relation between the first attitude information and the second attitude information corresponding to the same time point is constructed, so that when the AMCL mode is invalid, the corresponding target first attitude information in the AMCL mode can be reversely estimated based on the current second attitude information issued by the multi-source sensor, and the robot is positioned. Therefore, the application of the pose information of the sensor to the SLAM is realized, and the problem that the pose information of the multi-source sensor cannot be applied to the SLAM at present and the positioning of the robot is not matched is solved.
Example two:
the present embodiment illustrates the scheme of the present application in a case of being applied to a laser SLAM on the basis of the first embodiment.
First, the Robot runs an ROS (Robot Operating System) environment, and constructs a laser map by SLAM.
And grid division is carried out on the laser map, and the minimum value of the map is obtained through map.
Next, AMCL position information AMCL _ position (i.e. first position information, hereinafter referred to as AMCL _ position in this embodiment) of the moving area of the robot in the laser map and second position information issued by the multi-source sensor are recorded.
And then, time synchronization is carried out on the recorded amcl _ position and the second position information, and if the amcl _ position and the second position information are both reliable at the synchronization time point, mapping is carried out on the amcl _ position and the second position information, the translation amount and the rotation amount of the amcl _ position and the second position information are calculated, and the translation amount and the rotation amount are related to the grid where the amcl _ position is located.
And acquiring and storing second attitude information of the robot at the minimum point of the map.
After the corresponding translation amount and rotation amount are associated with the partial grids, the method can be applied to actual navigation of the robot.
The actual navigation process is as follows:
when the amcl _ position is effective, the actual pose of the robot is the amcl _ position; when amcl _ position fails, the following logic is followed:
a. and determining a first target grid corresponding to the current second position information in the laser map according to the known minimum position in the laser map and the second position information corresponding to the minimum position in the laser map.
b. If there is a corresponding amount of translation and rotation for the first target grid. The translation amount and the rotation amount are read, and the target amcl _ position (namely the target first position and attitude information) is reversely calculated for the current second position information based on the translation amount and the rotation amount, so that the robot is repositioned.
c. If the translation amount and the rotation amount corresponding to the first target grid are null, the hierarchy or cross from the near to the far is searched in order (for example, as shown in fig. 3). And when the distance between the second target grid and the first target grid obtained by searching does not exceed a preset distance threshold, performing reverse calculation on the current second position information by using the translation amount and the rotation amount corresponding to the second target grid to obtain a target amcl _ position, and realizing robot relocation.
Optionally, in this embodiment of the application, when the translation amount and the rotation amount corresponding to the first target grid are null, after the second target grid is retrieved and converted to the target amcl _ position, the position of the target laser point corresponding to the target amcl _ position may be determined according to the target amcl _ position, and then the position of the target laser point may be matched with the position of the actual laser point in the laser map. And when the ratio of the target laser points matched with the actual laser points is larger than a preset threshold value, correlating the translation amount and the rotation amount corresponding to the second target grid with the first target grid so as to facilitate subsequent use.
Example three:
based on the same inventive concept, the embodiment of the application also provides a robot positioning device. Referring to fig. 4, fig. 4 shows a robot positioning device 100 corresponding to the method according to the first embodiment. It should be understood that the specific functions of the robot positioning device 100 can be referred to the above description, and the detailed description is omitted here as appropriate to avoid redundancy. The robotic positioning device 100 includes at least one software functional module that can be stored in memory in the form of software or firmware or solidified in the operating system of the robotic positioning device 100. Specifically, the method comprises the following steps:
referring to fig. 4, the robot positioning device 100 includes: an acquisition module 101, a determination module 102 and a processing module 103. Wherein:
the obtaining module 101 is configured to obtain current first position and orientation information obtained in an adaptive monte carlo positioning AMCL manner and current second position and orientation information issued by a multi-source sensor.
The determining module 102 is configured to determine, from a preset mapping relationship set, a target mapping relationship corresponding to the current second pose information when the current first pose information is invalid; the set of mapping relationships is a set of mapping relationships between the first pose information and the second pose information recorded when the first pose information is valid and corresponding to the same time point.
And the processing module 103 is configured to perform reverse mapping processing on the current second pose information according to the target mapping relationship to obtain target first pose information obtained by mapping the current second pose information, where the target first pose information represents a current actual pose of the robot.
In this embodiment of the application, the processing module 103 is further configured to, when the current first pose information is valid, characterize the current actual pose of the robot by the current first pose information.
In this embodiment of the application, the processing module 103 is further configured to calculate a translation amount and a rotation amount between the current first position information and the current second position information when the current first position information is valid; associating the translation amount and the rotation amount with a grid where the current first attitude information is located in the map; and the translation amount and the rotation amount represent the mapping relation between the current first position and attitude information and the current second position and attitude information.
In this embodiment of the application, the determining module 102 is specifically configured to determine a first target grid corresponding to the current second pose information in the map; extracting a mapping relation corresponding to the first target grid; and the mapping relation corresponding to the first target grid represents the target mapping relation corresponding to the current second position and posture information.
In a feasible implementation manner of the embodiment of the present application, the determining module 102 is specifically configured to acquire reference point pose information corresponding to a preset reference point in a map; determining the position deviation of the current second position and orientation information of the reference point; and determining a first target grid corresponding to the current second attitude information in the map according to the position deviation and the reference point.
In this embodiment of the application, when the mapping relationship corresponding to the first target grid is null, the determining module 102 is further configured to retrieve a second target grid closest to the first target grid; the second target grid is a grid of which the corresponding mapping relation is not empty; extracting a mapping relation corresponding to the second target grid; the mapping relation corresponding to the second target grid is a target mapping relation corresponding to the current second position information.
In a feasible implementation manner of the embodiment of the application, the first pose information is pose information obtained in a laser map in an AMCL manner; when the mapping relation corresponding to the first target grid is null, the processing module 103 is further configured to determine, according to the target first position information, a target laser point position corresponding to the target first position information; matching the position of the target laser point with the position of an actual laser point in a map; and when the ratio of the target laser points matched with the actual laser points is larger than a preset threshold value, associating the mapping relation corresponding to the second target grid with the first target grid.
It should be understood that, for the sake of brevity, the contents described in some embodiments are not repeated in this embodiment.
Example four:
the present embodiment provides a robot, as shown in fig. 5, which includes a processor 501, a memory 502, and a communication bus 503. Wherein:
the communication bus 503 is used to realize connection communication between the processor 501 and the memory 502.
The processor 501 is configured to execute one or more programs stored in the memory 502 to implement the robot positioning method according to the first embodiment or the second embodiment.
It will be appreciated that the arrangement shown in figure 5 is merely illustrative and that the robot may also comprise more or fewer components than shown in figure 5 or have a different configuration than that shown in figure 5, for example there may also be components such as a display screen, a keyboard and the like.
The present embodiment also provides a readable storage medium, such as a floppy disk, an optical disk, a hard disk, a flash Memory, a usb (secure digital Card), an MMC (Multimedia Card), etc., in which one or more programs for implementing the above steps are stored, and the one or more programs can be executed by one or more processors to implement the robot positioning method in the first embodiment. And will not be described in detail herein.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
In addition, units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
Furthermore, the functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
In this context, a plurality means two or more.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (7)
1. A robot positioning method, comprising:
acquiring current first position information obtained by a self-adaptive Monte Carlo positioning AMCL mode and current second position information issued by a multi-source sensor;
when the current first position information is invalid, determining a target mapping relation corresponding to the current second position information from a preset mapping relation set; the mapping relation set is a set of the mapping relations of the first posture information and the second posture information which are recorded when the first posture information is effective and correspond to the same time point;
according to the target mapping relation, performing reverse mapping processing on the current second pose information to obtain target first pose information obtained by mapping the current second pose information, wherein the target first pose information represents the current actual pose of the robot;
the determining, from a preset mapping relationship set, a target mapping relationship corresponding to the current second position information includes:
determining a first target grid corresponding to the current second attitude information in a map;
extracting a mapping relation corresponding to the first target grid; the mapping relation corresponding to the first target grid represents a target mapping relation corresponding to the current second position and posture information;
when the mapping relationship corresponding to the first target grid is empty, the method further includes:
retrieving a second target grid closest to the first target grid; the second target grid is a grid of which the corresponding mapping relation is not empty;
extracting a mapping relation corresponding to the second target grid; the mapping relation corresponding to the second target grid is a target mapping relation corresponding to the current second position and posture information;
the first position and posture information is position and posture information obtained in a laser map in an AMCL mode;
when the mapping relationship corresponding to the first target grid is empty, the method further includes:
determining the position of a target laser point corresponding to the target first position information according to the target first position information;
matching the position of the target laser point with the position of an actual laser point in the map;
and when the proportion of the target laser points matched with the actual laser points is larger than a preset threshold value, associating the mapping relation corresponding to the second target grid with the first target grid.
2. The robot positioning method of claim 1, further comprising:
and when the current first pose information is effective, the current first pose information represents the current actual pose of the robot.
3. The robot positioning method of claim 2, further comprising:
when the current first position information is effective, calculating the translation amount and the rotation amount between the current first position information and the current second position information;
associating the translation amount and the rotation amount with a grid in a map where the current first attitude information is located; and the translation amount and the rotation amount represent the mapping relation between the current first position and attitude information and the current second position and attitude information.
4. The robot positioning method of claim 1, wherein determining the first target grid to which the current second pose information corresponds in the map comprises:
acquiring reference point pose information corresponding to a preset reference point in the map;
determining a position deviation of the current second position and posture information and the reference point position and posture information;
and determining a first target grid corresponding to the current second position information in the map according to the position deviation and the reference point.
5. A robot positioning device, comprising: the device comprises an acquisition module, a determination module and a processing module;
the acquisition module is used for acquiring current first position and attitude information obtained by a self-adaptive Monte Carlo positioning AMCL mode and current second position and attitude information issued by a multi-source sensor;
the determining module is configured to determine, from a preset mapping relationship set, a target mapping relationship corresponding to the current second pose information when the current first pose information is invalid; the mapping relation set is a set of the mapping relations of the first posture information and the second posture information which are recorded when the first posture information is effective and correspond to the same time point;
the processing module is used for carrying out reverse mapping processing on the current second pose information according to the target mapping relation to obtain target first pose information obtained by mapping the current second pose information, and the target first pose information represents the current actual pose of the robot;
the determining, from a preset mapping relationship set, a target mapping relationship corresponding to the current second position information includes:
determining a first target grid corresponding to the current second attitude information in a map;
extracting a mapping relation corresponding to the first target grid; the mapping relation corresponding to the first target grid represents a target mapping relation corresponding to the current second position and posture information;
when the mapping relationship corresponding to the first target grid is null, the determining module is further configured to:
retrieving a second target grid closest to the first target grid; the second target grid is a grid of which the corresponding mapping relation is not empty;
extracting a mapping relation corresponding to the second target grid; the mapping relation corresponding to the second target grid is a target mapping relation corresponding to the current second position and posture information;
the first position and posture information is position and posture information obtained in a laser map in an AMCL mode;
when the mapping relationship corresponding to the first target grid is null, the processing module is further configured to:
determining the position of a target laser point corresponding to the target first position information according to the target first position information;
matching the position of the target laser point with the position of an actual laser point in the map;
and when the proportion of the target laser points matched with the actual laser points is larger than a preset threshold value, associating the mapping relation corresponding to the second target grid with the first target grid.
6. A robot, comprising: a processor, a memory, and a communication bus;
the communication bus is used for realizing connection communication between the processor and the memory;
the processor is configured to execute one or more programs stored in the memory to implement the robot positioning method of any of claims 1 to 4.
7. A readable storage medium storing one or more programs, the one or more programs being executable by one or more processors to implement the robot positioning method according to any one of claims 1 to 4.
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| CN112819891B (en) * | 2021-02-01 | 2023-12-22 | 深圳万拓科技创新有限公司 | Pose repositioning method, device, equipment and medium of laser sweeper |
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