CN113031006B

CN113031006B - Method, device and equipment for determining positioning information

Info

Publication number: CN113031006B
Application number: CN202110221211.8A
Authority: CN
Inventors: 魏青铜; 秦野; 刘佳
Original assignee: Hangzhou Hikrobot Co Ltd
Current assignee: Hangzhou Hikrobot Co Ltd
Priority date: 2021-02-26
Filing date: 2021-02-26
Publication date: 2023-06-27
Anticipated expiration: 2041-02-26
Also published as: CN113031006A

Abstract

The application provides a method, a device and equipment for determining positioning information, wherein the method comprises the following steps: acquiring a grid map of the robot, wherein the grid map comprises an occupied area and an idle area, and the idle area comprises a traveling area and a non-traveling area; transmitting a plurality of laser signals through a radar of the robot in the advancing process of the robot, and receiving echo signals returned after the laser signals detect a target object aiming at each laser signal; if the target object is located in the traveling area, determining the echo signal as an invalid echo signal; if the target object is located in the occupied area or the non-traveling area, determining the echo signal as an effective echo signal; and determining the matching degree of the laser signals and the grid map based on the first quantity of the effective echo signals corresponding to the laser signals, and determining the positioning information of the robot based on the matching degree. Through the technical scheme of the application, the interference laser signals in the traveling area of the robot can be removed, and the matching degree of the laser signals and the grid map is improved.

Description

Method, device and equipment for determining positioning information

Technical Field

The present disclosure relates to the field of robots, and in particular, to a method, an apparatus, and a device for determining positioning information.

Background

In recent years, various types of robots (robots), which are machine devices for automatically performing work and which are machines for realizing various functions by means of their own power and control capabilities, have been rapidly developed in technical and market aspects. The robot can accept human command, can run a pre-programmed program and can act according to strategies formulated by artificial intelligence. For example, the user uses the manual remote controller to control the robot to execute related operations, for example, the user uses the manual remote controller to send an operation command to the robot in a wireless mode, and the robot executes the operation specified by the operation command after receiving the operation command, thereby completing related functions.

AGVs (Automatic Guided Vehicle), automated guided vehicles) are currently in widespread use as one type of robot. When the AGV starts to move from an unknown position in an unknown environment, the AGV can position itself in the moving process and construct an incremental map based on the self-positioning.

To position the AGV, the following may be used: the AGV determines the degree of matching of the laser signal with the grid map and positions the AGV based on the degree of matching. For example, the higher the matching degree is, the higher the positioning reliability is, and the lower the matching degree is, the lower the positioning reliability is. In summary, it is desirable to determine the degree of matching and evaluate the reliability of the AGV's positioning results based on the degree of matching.

However, during the movement of the AGV, shielding of the laser signal is unavoidable, which may result in a reduced degree of matching and a reduced reliability of the positioning result. For example, in a scenario of multiple AGVs, the laser signals between the multiple AGVs are blocked from each other, resulting in a reduced degree of matching. If an unknown obstacle exists in the travel route of the AGV, the laser signal is blocked by the obstacle, and the matching degree is reduced.

Disclosure of Invention

In a first aspect, the present application provides a method for determining positioning information, the method including:

acquiring a grid map of the robot, wherein the grid map comprises an occupied area and an idle area, and the idle area comprises a traveling area and a non-traveling area; wherein the occupied area represents an area where a known obstacle exists, the free area represents an area where no known obstacle exists, the traveling area represents an area where the robot passes during traveling in the free area, and the non-traveling area represents an area where the robot does not pass during traveling in the free area;

transmitting a plurality of laser signals through a radar of the robot in the advancing process of the robot, and receiving echo signals returned after the laser signals detect a target object aiming at each laser signal; if the target object is located in the travelling area, determining the echo signal as an invalid echo signal; if the target object is located in the occupied area or the non-traveling area, determining the echo signal as a valid echo signal;

And determining the matching degree of the laser signals and the grid map based on the first quantity of the effective echo signals corresponding to the laser signals, and determining the positioning information of the robot based on the matching degree.

Illustratively, after receiving an echo signal returned after the laser signal detects the target object, the method further includes: counting a second number of echo signals located in the occupied area;

the determining the matching degree of the laser signals and the grid map based on the first quantity of the effective echo signals corresponding to the laser signals comprises the following steps: the degree of matching is determined based on the first number and a second number of echo signals located in the occupied area.

In one possible implementation, determining the matching degree based on the first number and a second number of echo signals located in the occupied area includes:

the degree of matching is determined based on a quotient of the second number and the first number.

In one possible implementation manner, before the acquiring the grid map of the robot, the method further includes: when a travel task of the robot is obtained, determining a travel route indicated by the travel task, and determining a travel area of the robot based on the travel route;

The acquiring the grid map of the robot includes: marking the advancing area on the original topological map of the robot to obtain a target topological map of the robot; wherein the target topology map includes an occupied area and a free area, and the free area includes a traveling area and a non-traveling area;

acquiring a grid map based on the target topological map; the occupied area of the target topological map is mapped to the occupied area of the grid map, the idle area of the target topological map is mapped to the idle area of the grid map, the traveling area of the target topological map is mapped to the traveling area of the grid map, and the non-traveling area of the target topological map is mapped to the non-traveling area of the grid map.

In one possible embodiment, the determining the travel area of the robot based on the travel route includes: determining a target size M, N, M representing the number of longitudinal pixels, N representing the number of transverse pixels in the running process of the robot, expanding M pixels for the longitudinal running route of the running route, and expanding N pixels for the transverse running route of the running route to obtain an initial area;

And performing expansion processing on the initial area to obtain the advancing area of the robot.

In one possible embodiment, the target size is a preconfigured size; or, the target size is the size of the robot; alternatively, in a scenario where there are at least two robots, the target size is a maximum size determined based on the sizes of all robots.

In one possible implementation manner, after the receiving the echo signal returned after the laser signal detects the target object, the method further includes:

determining a distance between the target object and the radar based on the echo signals;

determining a target grid where the target object is located based on the emitting direction of the laser signal and the distance, wherein the target grid is matched to one of a plurality of grids of the grid map;

determining a position of the target object based on the target grid; if the target grid is matched with the grid of the travelling area, the target object is positioned in the travelling area; if the target grid is matched with the grid of the occupied area, the target object is positioned in the occupied area; and if the target grid is matched with the grid of the non-travelling area, the target object is positioned in the non-travelling area.

In one possible embodiment, the robot specifically includes an automated guided vehicle AGV.

In a second aspect, the present application proposes a device for determining positioning information, the device comprising:

the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring a grid map of the robot, the grid map comprises an occupied area and an idle area, and the idle area comprises a traveling area and a non-traveling area; wherein the occupied area represents an area where a known obstacle exists, the free area represents an area where no known obstacle exists, the traveling area represents an area where the robot passes during traveling in the free area, and the non-traveling area represents an area where the robot does not pass during traveling in the free area;

the determining module is used for transmitting a plurality of laser signals through the radar of the robot in the advancing process of the robot, and receiving echo signals returned after the laser signals detect a target object aiming at each laser signal; if the target object is located in the travelling area, determining the echo signal as an invalid echo signal; if the target object is located in the occupied area or the non-traveling area, determining the echo signal as a valid echo signal;

And the positioning module is used for determining the matching degree of the laser signals and the grid map based on the first quantity of the effective echo signals corresponding to the plurality of laser signals and determining the positioning information of the robot based on the matching degree.

In a possible implementation manner, the determining module is further configured to count a second number of echo signals located in the occupied area;

the positioning module is specifically configured to, when determining the matching degree between the laser signals and the grid map based on the first number of effective echo signals corresponding to the plurality of laser signals: determining the degree of matching based on the first number and a second number of echo signals located in the occupied area;

the positioning module is specifically configured to determine the matching degree based on the first number and the second number of echo signals located in the occupied area: determining the degree of matching based on a quotient of the second number and the first number;

the determining module is further used for determining a travel route indicated by the travel task when the travel task of the robot is obtained, and determining a travel area of the robot based on the travel route;

The acquisition module is specifically used for acquiring the grid map of the robot when: marking the advancing area on the original topological map of the robot to obtain a target topological map of the robot; wherein the target topology map includes an occupied area and a free area, and the free area includes a traveling area and a non-traveling area; acquiring a grid map based on the target topological map; the occupied area of the target topological map is mapped to the occupied area of the grid map, the idle area of the target topological map is mapped to the idle area of the grid map, the traveling area of the target topological map is mapped to the traveling area of the grid map, and the non-traveling area of the target topological map is mapped to the non-traveling area of the grid map;

the determining module is specifically configured to, when determining the travel area of the robot based on the travel route: determining a target size M, N, M representing the number of longitudinal pixels, N representing the number of transverse pixels in the running process of the robot, expanding M pixels for the longitudinal running route of the running route, and expanding N pixels for the transverse running route of the running route to obtain an initial area; and performing expansion processing on the initial area to obtain the advancing area of the robot.

In a third aspect, the present application proposes a robot comprising: a processor and a machine-readable storage medium storing machine-executable instructions executable by the processor;

the processor is configured to execute machine-executable instructions to perform the steps of:

As can be seen from the above technical solutions, in the embodiments of the present application, after receiving an echo signal returned after a laser signal detects a target object, if the target object is located in a traveling area of a robot, the echo signal is determined to be an invalid echo signal, and if the target object is not located in the traveling area, the echo signal is determined to be a valid echo signal. And determining the matching degree of the laser signals and the grid map based on the number of the effective echo signals, and determining the positioning information of the robot based on the matching degree. In the above manner, if the target object is located in the traveling area of the robot, the echo signal is determined to be an invalid echo signal, so that the interference laser signal in the traveling area of the robot is removed, the matching degree of the laser signal and the grid map is improved, the accuracy of the matching degree in representing the positioning effect is improved, and accurate positioning information is obtained. In the motion process of the robot, even if shielding for laser signals exists, the matching degree is not reduced, and the reliability of a positioning result is improved.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following description will briefly describe the drawings that are required to be used in the embodiments of the present application or the description in the prior art, and it is obvious that the drawings in the following description are only some embodiments described in the present application, and other drawings may also be obtained according to these drawings of the embodiments of the present application for a person having ordinary skill in the art.

FIGS. 1A and 1B are schematic diagrams of a topological map and a grid map in one embodiment of the present application;

FIGS. 2A and 2B are schematic diagrams of a topological map and a grid map in one embodiment of the present application;

3A-3C are schematic diagrams of a topological map and a grid map in one embodiment of the present application;

FIG. 4 is a flow chart of a method of determining positioning information in one embodiment of the present application;

5A-5D are schematic diagrams of topological and grid maps in one embodiment of the present application;

FIGS. 6A and 6B are schematic diagrams of a topological map and a grid map in one embodiment of the present application;

FIG. 7 is a schematic structural diagram of a positioning information determining device in an embodiment of the present application;

Fig. 8 is a hardware configuration diagram of a robot according to an embodiment of the present application.

Detailed Description

The terminology used in the embodiments of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this application and the claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to any or all possible combinations including one or more of the associated listed items.

It should be understood that although the terms first, second, third, etc. may be used in embodiments of the present application to describe various information, these information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, a first message may also be referred to as a second message, and similarly, a second message may also be referred to as a first message, without departing from the scope of the present application. Depending on the context, furthermore, the word "if" used may be interpreted as "at … …" or "at … …" or "in response to a determination".

Before the technical scheme of the application is introduced, technical terms related to the application are introduced:

SLAM (Simultaneous Localization and Mapping), synchronous localization and mapping technique: the robot starts to move from an unknown position in an unknown environment, and can perform self-positioning according to the position estimation and the map in the moving process, and meanwhile, an incremental map is built on the basis of self-positioning.

Laser SLAM technology: the robot uses radar (e.g., lidar, etc.) as an external sensor to effect positioning, where SLAMs are laser SLAMs, i.e., laser SLAMs are employed to effect positioning.

Topology map (topologic map): the laser SLAM technology relates to a topological map, wherein the topological map is a statistical map in the cartography, and is an abstract map which keeps the correct relative position relation between points and lines, but does not necessarily keep the correct shape, area, distance and direction of a graph. The topological map may be composed of nodes and edges, the nodes representing important location points in the environment, the edges representing connection relationships between the nodes.

The topological map allows effective path planning, has low space complexity, does not need accurate position information of the robot, can realize effective man-machine interaction and is connected with reality.

Grid map (Grid based map): in the laser SLAM technique, a raster map is a raster image (also referred to as a raster image), and the raster map is divided into individual lattices, which are referred to as grids. Some grids are occupied by obstacles, and the robot needs to avoid the grids when navigating. Each grid in the grid map is given a possible value representing the probability that the grid is occupied by an obstacle.

The grid map is easy to construct, express and store, the position is unique, and the short-path planning is more convenient. The path planning efficiency of the grid map is low, space is wasted (the grid resolution is independent of environmental complexity), accurate robot position estimation is needed, and the effect on man-machine interaction problem of object recognition is poor.

When positioning a robot by using a laser SLAM technique, it is necessary to use a topology map and a grid map, for example, to give a travel route of the robot in the topology map, map the topology map to the grid map, position the robot based on the grid map, and navigate the robot based on the grid map.

Degree of matching of laser signal to grid map: i.e. the degree of matching of the occupied area echo signal with the effective echo signal, herein abbreviated as the degree of matching. For example, the grid map may be divided into an occupied area that represents an area where a known obstacle exists (i.e., the robot has recognized that the area has an obstacle), and an unoccupied area that represents an area where the known obstacle does not exist (i.e., the robot has not recognized that the area has an obstacle, but over time, the unoccupied area may or may not appear as an obstacle). The occupied area echo signal is an echo signal returned by a pointer to a target object of the occupied area, and the effective echo signal is an echo signal returned by the pointer to the target objects of the occupied area and the free area.

In the laser SLAM technique, the robot may be positioned based on the degree of matching. For example, the higher the degree of matching, the higher the positioning reliability, and the lower the degree of matching, the lower the positioning reliability.

Laser interference: laser interference refers to a decrease in the degree of matching of laser signals to a grid map due to environmental changes or occlusion, which in turn results in a decrease in the reliability of the positioning results. For example, in a scene of a plurality of robots, mutual occlusion of laser signals between the plurality of robots results in a decrease in the degree of matching. If an obstacle exists in the travel route of the robot, the obstacle shields the laser signal, and the matching degree is also reduced.

The following describes a laser interference process in connection with a specific application scenario.

The topological map may include an occupied area representing an area that has been occupied by a known obstacle, that is, an area where the known obstacle exists, and an unoccupied area that is an area where the known obstacle does not exist, but as the environment changes, an unknown obstacle or other robot (other robot is also an obstacle as an unoccupied area, and is subsequently noted as an unknown obstacle) may exist in the unoccupied area. The user may configure the travel route of the robot in the topological map, i.e. the robot moves based on the travel route.

On the basis of this topological map, it is also possible to map the topological map as a grid map, which also comprises occupied areas and free areas. The footprint of the topological map may be mapped to the footprint of the grid map, i.e. the footprint of the grid map may comprise a plurality of grids of a first type having a first attribute (e.g. representing the grids by a first value that they have a first attribute) representing that the grids of the first type belong to the footprint. And, the free area of the topological map may be mapped to the free area of the grid map, i.e. the free area of the grid map may comprise a plurality of grids of a second type having a second attribute (e.g. representing the grids as having the second attribute by a second value), the second attribute representing that the grids of the second type belong to the free area. To this end, the topology map can be mapped to a grid map.

Assuming that no unknown obstacle exists in the free area of the topological map, reference may be made to fig. 1A and 1B for the degree of matching of the laser signal to the grid map. Referring to fig. 1A, a schematic diagram of a topological map is shown, a black area is an occupied area, a white area is an idle area, and a robot walks along a travel route (dotted line) drawn in advance, and the travel route is located in the idle area. Referring to fig. 1B, a schematic diagram of a grid map is shown, where a gray grid is a first type of grid (i.e., a grid with a first attribute) occupying an area, different attributes can be distinguished by different colors, and different attributes can be distinguished by different values, and a white grid is a second type of grid (i.e., a grid with a second attribute) occupying an idle area.

When the robot emits a laser signal by radar, the laser signal returns an echo signal after contacting a target object (i.e., an obstacle or other robot). Referring to fig. 1A, only the occupied area has a known obstacle, and the free area does not have an obstacle or other robots, and thus, in fig. 1B, only the occupied area has a target object, and the free area does not have a target object. Obviously, the occupied area echo signal is identical to the effective echo signal, and the matching degree of the occupied area echo signal and the effective echo signal is 100%.

Assuming that there are unknown obstacles and other robots in the free area of the topological map, reference can be made to fig. 2A and 2B for the degree of matching of the laser signal to the grid map. Referring to fig. 2A, a schematic diagram of a topological map is shown, a black area is an occupied area, a white area is an idle area, and unknown obstacles and other robots are present in the idle area (in an actual topological map, the unknown obstacles and other robots are not drawn, and fig. 2A shows the unknown obstacles and other robots in the idle area for convenience of illustration only, and are not present in the actual topological map). Referring to fig. 2B, a schematic diagram of a grid map is shown, where gray grids are first-class grids of occupied areas and white grids are second-class grids of free areas.

Referring to fig. 2A, there are known obstacles in the occupied area and unknown obstacles and other robots in the free area, so in fig. 2B, there are target objects in the occupied area as well as in the free area (black circles in fig. 2B indicate target objects in the free area, which also return echo signals, in an actual grid map, these black circles are not drawn, and fig. 2B shows black circles indicating target objects in the free area, which are not present in the actual grid map, for convenience of illustration only). Assuming that the target object of the occupied area returns 80 echo signals and the target object of the free area returns 20 echo signals, the number of occupied area echo signals is 80, the number of effective echo signals is 100 (80+20), and the matching degree between the occupied area echo signals and the effective echo signals is 80%.

Obviously, because unknown obstacles and other robots exist in the idle area, the matching degree of the echo signals of the occupied area and the effective echo signals is reduced, namely, the laser interference phenomenon is caused, the mutual shielding of multiple robots and/or the shielding of the unknown obstacles reduce the matching degree, and the reliability of the positioning result is reduced.

In one possible implementation, the matching degree may not accurately characterize the positioning result, i.e., a case with a better matching degree characterizes a wrong positioning result, a case with a worse matching degree characterizes a correct positioning result, and this phenomenon is called a matching degree trap. The cause of this matching degree trap is: when the robot is positioned at certain specific positions, if the key positioning features are blocked by obstacles (i.e. obstacles in the idle area) appearing in the environment, and the echo signals of the obstacles are similar to those of the obstacles in the occupied area, whether the echo signals in the idle area or the echo signals in the occupied area cannot be accurately identified, so that the positioning result cannot be accurately represented by the matching degree, and the problems of trap of the matching degree and the like appear.

Referring to fig. 3A, a schematic diagram of a topological map is shown, a black area is an occupied area, a white area is an idle area, and an unknown obstacle exists in the idle area (in an actual topological map, the unknown obstacle is not drawn, and fig. 3A is merely for convenience of illustration). Referring to fig. 3B and 3C, there is shown a schematic diagram of a grid map, in which gray grids are first-type grids of occupied areas and white grids are second-type grids of free areas.

In fig. 3B, the occupied area has target objects, the unoccupied area also has target objects (black circles indicate target objects in the unoccupied area, in an actual grid map, these black circles are not drawn, fig. 3B is for convenience of illustration only), and an obstacle on the upper side of the grid map is recognized as a target object of the unoccupied area (in actuality, an obstacle on the lower side of the grid map is a target object of the unoccupied area, that is, this is an erroneous recognition case), in which case, assuming that the target object of the occupied area returns 90 echo signals, and the target object of the unoccupied area returns 10 echo signals, the degree of matching is 90%.

In fig. 3C, the occupied area has target objects, the unoccupied area also has target objects (black circles indicate target objects in the unoccupied area, in an actual grid map, these black circles are not drawn, fig. 3C is for convenience of illustration only), and an obstacle on the lower side of the grid map is recognized as a target object of the unoccupied area (in actuality, an obstacle on the lower side of the grid map is a target object of the unoccupied area, that is, this is a correct recognition case), in which case, assuming that the target object of the occupied area returns 80 echo signals, and the target object of the unoccupied area returns 20 echo signals, the degree of matching is 80%.

As can be seen from the above, since the matching degree of fig. 3B is 90% and the matching degree of fig. 3C is 80%, the positioning result of fig. 3B is taken as the final positioning result (when the matching degree is higher, the positioning reliability is higher), and it is obvious that this is an erroneous positioning result, i.e. the problem of the matching degree trap occurs.

The root cause of the occurrence of the matching degree trap is: under the condition that the target objects detected by the laser signals cannot be distinguished, the accuracy of the matching degree on the laser SLAM positioning effect characterization can be directly affected by the interference data, so that the problems of reduced matching degree, trapped matching degree and the like of the laser SLAM can be caused for local environment changes and laser signal shielding phenomena caused by the operation of multiple robots.

Aiming at the finding, the embodiment of the application provides a method for determining positioning information, which marks the advancing area of the robot in the grid map and determines the echo signal of the advancing area as an invalid echo signal, so that the interference laser signal in the advancing area is removed, the blocked laser signal can be effectively removed, the matching degree of the laser signal and the grid map is improved, the accuracy of the matching degree for positioning effect characterization is improved, accurate positioning information is obtained, and meanwhile, the probability of occurrence of a matching degree trap is reduced.

The method for determining positioning information provided by the embodiment of the application can be applied to robots, namely, each robot can process by adopting the method for determining positioning information provided by the embodiment of the application. The robot may include, but is not limited to, an AGV (Automatic Guided Vehicle, automated guided vehicle) or the like, although the AGV is merely an example and the type of robot is not limited as long as the laser SLAM technique is supported.

Referring to fig. 4, a flowchart of a method for determining positioning information, the method may be applied to any robot (i.e. any robot supporting positioning by SLAM technology), and the method may include:

step 401, a grid map of a robot is acquired, the grid map may include an occupied area and a free area, and the free area may include a traveling area and a non-traveling area. Illustratively, the occupied area represents an area where a known obstacle exists, the free area represents an area where no known obstacle exists, the traveling area represents an area where the robot passes during traveling in the free area, and the non-traveling area represents an area where the robot does not pass during traveling in the free area.

For example, for the grid map, a traveling area and a non-traveling area are added on the basis of the occupied area and the free area, namely, the free area is divided into the traveling area and the non-traveling area, so that the traveling area and the non-traveling area are marked in the grid map of the robot, the traveling area represents an area which is passed by the robot in the traveling process, and the non-traveling area represents an area which is not passed by the robot in the traveling process. In summary, the grid map may include an occupied area, a traveling area, and a non-traveling area.

For example, the occupancy zone of the grid map may include a plurality of first-type grids having a first attribute that indicates that the first-type grids belong to the occupancy zone. The non-travel area of the grid map may include a plurality of second-type grids having a second attribute that indicates that the second-type grids belong to the non-travel area. The travel area of the grid map may include a plurality of third class grids having third attributes indicating that the third class grids belong to the travel area.

For example, different attributes of the grids may be distinguished by different colors, for example, a first type of grid is a first color, a grid having the first color belongs to an occupied area, a second type of grid is a second color, a grid having the second color belongs to a non-traveling area, a third type of grid is a third color, and a grid having the third color belongs to a traveling area. Or, different attributes of the grids can be distinguished through different values, for example, a first type of grid is a first value, a grid with the first value belongs to an occupied area, a second type of grid is a second value, a grid with the second value belongs to a non-travelling area, a third type of grid is a third value, and a grid with the third value belongs to a travelling area. Of course, the foregoing is merely exemplary.

In one possible embodiment, when a travel task of the robot is obtained, a travel route indicated by the travel task may be determined, and a travel area of the robot may be determined based on the travel route. For example, the travel task is used for indicating a travel route on which the robot travels, so that after the robot obtains the travel task, the travel route indicated by the travel task can be determined, and a travel area of the robot can be determined based on the travel route, for example, an initial area can be determined based on the travel route and a target size of the robot, and expansion processing can be performed on the initial area to obtain the travel area of the robot.

Further, after obtaining the traveling area of the robot, step 401 and subsequent steps may be performed, and in step 401, the robot may acquire a grid map of the robot in the following manner:

in step 4011, the travel region is marked on an original topology map of the robot to obtain a target topology map of the robot, which may include, for example, an occupied region and an unoccupied region, and the unoccupied region may include a travel region and a non-travel region. As can be seen, the target topology map of the robot may include an occupied area, a traveling area, and a non-traveling area.

For example, an original topology map and a travel route (a preset route or a manually drawn route) of the robot may be imported, and as shown in fig. 1A, 2A, and 3A, are schematic diagrams of the original topology map (for convenience of distinction, these topology maps are referred to as an original topology map), which may include an occupied area (black area) and an unoccupied area (white area), and the unoccupied area includes the travel route of the robot. On the basis of an original topological map, an initial area can be determined based on a travel route and a target size of a robot, and assuming that the target size in the travelling process of the robot is M×N, M represents the number of longitudinal pixels and N represents the number of transverse pixels, M pixels are extended for the longitudinal travel route of the travel route and N pixels are extended for the transverse travel route of the travel route, so that the initial area is obtained.

For example, M pixels are extended on both sides of the longitudinal travel route (e.g., M/2 pixels each side, or M/3 on one side and 2M/3 on the other side, without limitation), or M pixels on one side of the longitudinal travel route. And extending N pixels on both sides of the lateral travel route (e.g., N/2 pixels on each side, or N/3 on one side and 2N/3 on the other side, without limitation), or N pixels on one side of the lateral travel route.

For the original topological map shown in fig. 1A, the initial region may be as shown in fig. 5A.

Then, the initial region is subjected to expansion processing to obtain a traveling region of the robot, for example, the initial region is subjected to expansion processing according to a preset ratio K, and the region after expansion processing can be used as the traveling region of the robot. If the preset ratio K is 1, the traveling area after the expansion processing is the same as the initial area, if the preset ratio K is greater than 1, the traveling area after the expansion processing is greater than the initial area, and if the preset ratio K is less than 1, the traveling area after the expansion processing (i.e., the contraction processing) is less than the initial area.

For convenience of description, in this embodiment, taking the preset ratio K as an example, after the initial area is inflated according to the preset ratio K, as shown in fig. 5A, since the longitudinal travel route of the initial area is M pixels and the transverse travel route is N pixels, the longitudinal travel route of the travel area is m×k pixels and the transverse travel route is n×k pixels, as shown in fig. 5B, which is a schematic diagram of the travel area.

The travel area may then be marked on the original topology map, the topology map marked with the travel area being referred to as the target topology map, as shown in fig. 5C. It is to be noted that, after marking the travel area, other areas than the travel area in the free area may be noted as non-travel areas, that is, the free area is divided into the travel area and the non-travel area. In summary, the target topology map may include an occupied area (black area), a non-traveling area (white area), and a traveling area (gray area), and the traveling area includes a traveling route of the robot. Obviously, the non-traveling area of the target topological map is the remaining area except the traveling area in the free area of the original topological map. For example, the non-travel region may also have an unknown obstacle, and the travel region may also have an unknown obstacle.

In the above embodiment, the target size may be a preconfigured size, that is, the target size is empirically configured, and the configuration manner of the target size is not limited. Alternatively, the target size may be the size of the present robot, for example, the target size may be determined based on the size of the present robot, that is, the width of the present robot is set as M in the target size and the height of the present robot is set as N in the target size for the processing procedure of the present robot. Alternatively, in a scenario where at least two robots are present (i.e. where there are at least two robots in the area where the topological map is located), the target size is the maximum size determined based on the sizes of all robots, e.g. the maximum width is selected based on the widths of all robots, the maximum height is selected based on the heights of all robots, and the maximum width and the maximum height constitute the maximum size. The width of the maximum dimension (i.e., the maximum width) is taken as M in the target dimension, and the height of the maximum dimension (i.e., the maximum height) is taken as N in the target dimension. Of course, the above manner is merely a few examples, and the manner of determining the target size is not limited thereto.

Step 4012, obtaining a grid map based on a target topology map, wherein an occupied area of the target topology map is mapped to an occupied area of the grid map, an unoccupied area of the target topology map is mapped to an unoccupied area of the grid map, a traveling area of the target topology map is mapped to a traveling area of the grid map, and a non-traveling area of the target topology map is mapped to a non-traveling area of the grid map. To this end, a grid map including an occupied area and an unoccupied area, and an unoccupied area including a traveling area and a non-traveling area, that is, the grid map including an occupied area, a traveling area, and a non-traveling area, can be obtained.

Referring to fig. 5D, a schematic view of the grid map is shown, in which the light gray grid is a first type of grid occupying the area, the white grid is a second type of grid not traveling in the area, and the dark gray grid is a third type of grid traveling in the area. In summary, in the grid map, except for the occupied area, the idle area may be divided into a traveling area and a non-traveling area, where the traveling area indicates an area that the robot may pass through in the traveling process, that is, the robot moves in the traveling area, and the non-traveling area indicates an area that the robot may not pass through in the traveling process.

Step 402, transmitting a plurality of laser signals by a radar of the robot during the traveling process of the robot, and receiving echo signals returned after the laser signals detect the target object for each laser signal.

For example, if the target object is located in the travel zone, the echo signal may be determined to be an invalid echo signal; if the target object is located in the occupied area or the non-traveling area, the echo signal may be determined to be a valid echo signal. And if the target object is located in the traveling region or the non-traveling region, determining the echo signal as a non-occupied region echo signal; if the target object is located in the occupied area, the echo signal may be determined as an occupied area echo signal.

For example, in the running process of the robot, a plurality of laser signals can be periodically transmitted through the radar of the robot, that is, in each period, a plurality of laser signals can be transmitted, and each time a plurality of laser signals are transmitted, steps 402-404 can be executed to determine the positioning information of the robot, so that in each period, the positioning information of the robot can be determined, and the robot can be positioned in real time.

Step 403, determining a degree of matching between the laser signals and the grid map based on a first number of effective echo signals corresponding to the plurality of laser signals. For example, a second number of echo signals located in the occupied area (i.e., the number of echo signals in the occupied area) may be counted, and a degree of matching between the laser signals and the grid map may be determined based on the first number of effective echo signals corresponding to the plurality of laser signals and the second number of echo signals located in the occupied area. For example, the matching degree is determined based on the quotient of the second number and the first number, for example, the quotient of the second number and the first number is taken as the matching degree, and the matching degree may be simply referred to as the matching degree, and the calculation formula of the matching degree is as follows: match = second number/first number.

For example, assuming that the target object of the occupied area returns 80 echo signals, the target object of the non-traveling area returns 20 echo signals, and the target object of the traveling area returns 50 echo signals, the 50 echo signals returned by the target object of the traveling area are invalid echo signals, and the 100 echo signals returned by the target objects of the occupied area and the non-traveling area are valid echo signals, the first number of valid echo signals is 100 instead of 150. The 80 echo signals returned by the target object of the occupied zone are occupied zone echo signals, and the 70 echo signals returned by the target objects of the traveling zone and the non-traveling zone are non-occupied zone echo signals, so the second number of occupied zone echo signals is 80 instead of 100 or 150. In summary, the degree of matching may be 80/100, i.e., 80%.

In one possible embodiment, after receiving the echo signal returned after the laser signal detects the target object, the distance between the target object and the radar may be determined based on the echo signal, and the determination is not limited in this manner, and the function of the echo signal is to give the distance between the target object and the radar.

Based on the emission direction of the laser signal and the distance, a target grid in which the target object is located, which is matched to a certain grid among a plurality of grids of the grid map, may be determined. The position of the target object is determined based on the target grid. For example, if the target grid matches a grid of the travel area, the target object is located in the travel area; if the target grid is matched with the grid of the occupied area, the target object is positioned in the occupied area; if the target grid matches a grid of a non-traveling region, the target object is located in the non-traveling region.

For example, since each grid of the grid map has a corresponding attribute, such as a first attribute, a second attribute, or a third attribute, if the target grid has the first attribute, it means that the target grid is a first type of grid of the occupied area, that is, a light gray grid of fig. 5D, and the target object is located in the occupied area. If the target grid has the second attribute, the second type of grid indicating the target grid is a non-traveling area, i.e., the white grid of fig. 5D, where the target object is located. If the target grid has a third attribute, it indicates that the target grid is a third type of grid of the traveling area, i.e., the dark gray grid of fig. 5D, where the target object is located.

Step 404, determining positioning information of the robot based on the matching degree.

For example, in the laser SLAM, the robot may be positioned based on the degree of matching, that is, the degree of matching of the laser signal and the grid map, which is an important index for evaluating the accuracy of the positioning information, determines the positioning information (i.e., pose information) of the robot. For example, the higher the matching degree is, the higher the positioning reliability is, and the lower the matching degree is, the lower the positioning reliability is, and the process will not be described.

For example, the above execution sequence is only an example given for convenience of description, and in practical application, the execution sequence between steps may be changed, which is not limited. Moreover, in other embodiments, the steps of the corresponding methods need not be performed in the order shown and described herein, and the methods may include more or less steps than described herein. Furthermore, individual steps described in this specification, in other embodiments, may be described as being split into multiple steps; various steps described in this specification, in other embodiments, may be combined into a single step.

As can be seen from the above technical solution, in the embodiment of the present application, if the target object is located in the traveling area of the robot, the echo signal is determined to be an invalid echo signal, so as to remove the interference laser signal in the traveling area of the robot, improve the matching degree of the laser signal and the grid map, improve the accuracy of the matching degree in characterizing the positioning effect, and obtain accurate positioning information. In the motion process of the robot, even if shielding for laser signals exists, the matching degree is not reduced, and the reliability of a positioning result is improved. The travel area can be determined through the travel route, and marked in the grid map, so that the scheme is simple and reliable. If the on-site operation route is adjusted, the operation of adding and deleting the travel route can be performed according to the actual situation, the travel area is regenerated, the travel area is re-marked in the grid map, and the operation is very convenient.

With respect to fig. 2A and 2B, after the above technical solution is adopted, it is assumed that there are unknown obstacles and other robots in the traveling area of the topological map, as shown in fig. 6A, a schematic diagram of the topological map is shown, a black area is an occupied area, a white area is a non-traveling area, a gray area is a traveling area, and there are unknown obstacles and other robots in the traveling area. Referring to fig. 6B, a schematic diagram of a grid map is shown, in which a light gray grid is a first type of grid occupying an area, a white grid is a second type of grid not traveling an area, and a dark gray grid is a third type of grid traveling an area. In fig. 6B, the occupied area has a target object, the non-traveling area has no target object, and the traveling area has a target object (black circles indicate target objects in the traveling area).

Assuming that the target object of the occupied area returns 80 echo signals and the target object of the traveling area returns 20 echo signals, the number of echo signals of the occupied area is 80. Since the 20 echo signals returned by the target object of the traveling region are not effective echo signals, the number of effective echo signals is 80 instead of 100. In summary, the degree of matching is 100%. Obviously, compared with fig. 2A and 2B, the matching degree is improved from 80% to 100%, so that the phenomenon of laser interference is avoided, and the reduction of the matching degree is avoided.

With respect to fig. 3A, 3B, and 3C, after the above-described technical solution is adopted, if an unknown obstacle exists in the traveling area of the topological map, a target object exists in the occupied area, a target object does not exist in the non-traveling area, and a target object exists in the traveling area in the grid map. In this case, assuming that the target object occupying the area returns 80 echo signals and the target object traveling the area returns 20 echo signals, the number of echo signals occupying the area is 80, the number of effective echo signals is 80, and the matching degree is 100%.

In summary, since the matching degree is 100%, there is no case where the matching degree of fig. 3B is 90%, and there is no case where the matching degree of fig. 3C is 80%, the problem of the matching degree trap does not occur.

Based on the same application concept as the above method, an apparatus for determining positioning information is provided in this embodiment of the present application, as shown in fig. 7, which is a schematic structural diagram of the apparatus, where the apparatus may include:

an acquisition module 71 for acquiring a grid map of a robot, the grid map including an occupied area and an idle area, the idle area including a traveling area and a non-traveling area; wherein the occupied area represents an area where a known obstacle exists, the free area represents an area where no known obstacle exists, the traveling area represents an area where the robot passes during traveling in the free area, and the non-traveling area represents an area where the robot does not pass during traveling in the free area;

a determining module 72, configured to transmit, by a radar of the robot, a plurality of laser signals during a traveling process of the robot, and for each laser signal, receive an echo signal returned after the laser signal detects a target object; if the target object is located in the travelling area, determining the echo signal as an invalid echo signal; if the target object is located in the occupied area or the non-traveling area, determining the echo signal as a valid echo signal;

And the positioning module 73 is configured to determine a matching degree of the laser signals and the grid map based on the first number of effective echo signals corresponding to the plurality of laser signals, and determine positioning information of the robot based on the matching degree.

Illustratively, the determining module 72 is further configured to: and is also configured to count a second number of echo signals located in the occupied zone;

the positioning module 73 is specifically configured to, when determining the matching degree between the laser signals and the grid map based on the first number of effective echo signals corresponding to the plurality of laser signals: the degree of matching is determined based on the first number and a second number of echo signals located in the occupied area.

Illustratively, the positioning module 73 is specifically configured to determine the matching degree based on the first number and a second number of echo signals located in the occupied area: the degree of matching is determined based on a quotient of the second number and the first number.

Illustratively, the determining module 72 is further configured to determine, when a travel task of the robot is obtained, a travel route indicated by the travel task, and determine a travel area of the robot based on the travel route; the acquiring module 71 is specifically configured to, when acquiring the grid map of the robot: marking the advancing area on the original topological map of the robot to obtain a target topological map of the robot; wherein the target topology map includes an occupied area and a free area, and the free area includes a traveling area and a non-traveling area; acquiring a grid map based on the target topological map; the occupied area of the target topological map is mapped to the occupied area of the grid map, the idle area of the target topological map is mapped to the idle area of the grid map, the traveling area of the target topological map is mapped to the traveling area of the grid map, and the non-traveling area of the target topological map is mapped to the non-traveling area of the grid map.

The determining module 72 is specifically configured to, when determining a travel area of the robot based on the travel route: determining a target size M, N, M representing the number of longitudinal pixels, N representing the number of transverse pixels in the running process of the robot, expanding M pixels for the longitudinal running route of the running route, and expanding N pixels for the transverse running route of the running route to obtain an initial area; and performing expansion processing on the initial area to obtain the advancing area of the robot.

Based on the same application concept as the above method, a robot (i.e. an intelligent mobile device) is proposed in the embodiment of the present application, and referring to fig. 8, the robot includes: a processor 81 and a machine-readable storage medium 82, the machine-readable storage medium 82 storing machine-executable instructions executable by the processor 81; the processor 81 is configured to execute machine executable instructions to implement the following steps:

Based on the same application concept as the above method, the embodiment of the present application further provides a machine-readable storage medium, where a plurality of computer instructions are stored on the machine-readable storage medium, and when the computer instructions are executed by a processor, the method for determining positioning information disclosed in the above example of the present application can be implemented.

Wherein the machine-readable storage medium may be any electronic, magnetic, optical, or other physical storage device that can contain or store information, such as executable instructions, data, or the like. For example, a machine-readable storage medium may be: RAM (Radom Access Memory, random access memory), volatile memory, non-volatile memory, flash memory, a storage drive (e.g., hard drive), a solid state drive, any type of storage disk (e.g., optical disk, dvd, etc.), or a similar storage medium, or a combination thereof.

The system, apparatus, module or unit set forth in the above embodiments may be implemented in particular by a computer chip or entity, or by a product having a certain function. A typical implementation device is a computer, which may be in the form of a personal computer, laptop computer, cellular telephone, camera phone, smart phone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or a combination of any of these devices.

For convenience of description, the above devices are described as being functionally divided into various units, respectively. Of course, the functions of each element may be implemented in one or more software and/or hardware elements when implemented in the present application.

It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present application may take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

Moreover, these computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and changes may be made to the present application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc. which are within the spirit and principles of the present application are intended to be included within the scope of the claims of the present application.

Claims

1. A method of determining positioning information, the method comprising:

2. The method of claim 1, wherein the step of determining the position of the substrate comprises,

after receiving the echo signal returned after the laser signal detects the target object, the method further comprises: counting a second number of echo signals located in the occupied area;

3. The method of claim 2, wherein determining the degree of matching based on the first number and a second number of echo signals located in the occupied zone comprises:

4. The method of claim 1, wherein prior to the acquiring the grid map of the robot, the method further comprises: when a travel task of the robot is obtained, determining a travel route indicated by the travel task, and determining a travel area of the robot based on the travel route;

the acquiring the grid map of the robot includes:

marking the advancing area on the original topological map of the robot to obtain a target topological map of the robot; wherein the target topology map includes an occupied area and a free area, and the free area includes a traveling area and a non-traveling area;

5. The method of claim 4, wherein the step of determining the position of the first electrode is performed,

the determining a travel area of the robot based on the travel route includes:

determining a target size M, N, M representing the number of longitudinal pixels, N representing the number of transverse pixels in the running process of the robot, expanding M pixels for the longitudinal running route of the running route, and expanding N pixels for the transverse running route of the running route to obtain an initial area;

6. The method of claim 5, wherein the target size is a preconfigured size; or, the target size is the size of the robot; alternatively, in a scenario where there are at least two robots, the target size is a maximum size determined based on the sizes of all robots.

7. The method of any of claims 1-6, wherein after receiving the echo signal returned after the laser signal detected the target object, the method further comprises:

8. A device for determining positioning information, the device comprising:

9. The apparatus of claim 8, wherein the device comprises a plurality of sensors,

the determining module is further used for counting a second number of echo signals in the occupied area;

10. A robot, comprising: a processor and a machine-readable storage medium storing machine-executable instructions executable by the processor;