CN112578798B - Robot map acquisition method and device, processor and electronic device - Google Patents
Robot map acquisition method and device, processor and electronic device Download PDFInfo
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Classifications
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0246—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0214—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with safety or protection criteria, e.g. avoiding hazardous areas
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0223—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving speed control of the vehicle
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0257—Control of position or course in two dimensions specially adapted to land vehicles using a radar
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
Abstract
The invention discloses a robot map acquisition method, a robot map acquisition device, a processor and an electronic device. Wherein the method comprises the following steps: creating an initial map, wherein the initial map is a grid map, and the grid map comprises: a plurality of grids; the robot is controlled to walk in the initial map according to a preset path, and data information is obtained, wherein the data information is used for describing the probability that each grid in the multiple grids is occupied by an obstacle; and acquiring a first target map and a second target map by using the probability threshold values and the data information of a plurality of levels, wherein the movable space of the robot in the first target map is larger than that of the robot in the second target map. The invention solves the technical problem that the robot is easy to collide and then malfunction due to inaccurate grid map.
Description
Technical Field
The invention relates to the field of intelligent control, in particular to a robot map acquisition method, a robot map acquisition device, a robot map acquisition processor and an electronic device.
Background
With the continuous development of artificial intelligence technology, the control technology of robots is mature, and the robot is widely applied to the fields of automobile industry, household appliance manufacturing, e-commerce warehouse logistics, tobacco and the like. In practical application, the navigation path of the robot can be preset, and then the robot runs along the specified navigation path, so that the whole process does not need human participation.
Currently, synchronous positioning and mapping (Simultaneous Localization and Mapping, SLAM) is to position and pose of a robot under an unknown environment through surrounding environment features repeatedly detected in a motion process, and then build a map in an incremental mode according to the position of the robot, so that the aims of simultaneous positioning and map building are achieved.
The map may be a grid map, the creation of the grid map requires a laser radar installed on the robot, the occupancy rate of the grid is generated by sensing the distance between the laser radar and the obstacle, and whether the obstacle exists in the grid is determined by a preset threshold value, so that a complete grid map is finally formed.
However, the grid map is not accurate enough due to the laser scanning error, so that the robot is easy to collide with an obstacle in the moving process, and the robot is destroyed and fails.
In view of the above problems, no effective solution has been proposed at present.
Disclosure of Invention
The embodiment of the invention provides a robot map acquisition method, a robot map acquisition device, a processor and an electronic device, which are used for at least solving the technical problem that a robot is easy to collide and then malfunction due to inaccurate grid map.
According to an aspect of an embodiment of the present invention, there is provided a robot map acquisition method including: creating an initial map, wherein the initial map is a grid map, and the grid map comprises: a plurality of grids; the robot is controlled to walk in the initial map according to a preset path, and data information is obtained, wherein the data information is used for describing the probability that each grid in the multiple grids is occupied by an obstacle; and acquiring a first target map and a second target map by using the probability threshold values and the data information of a plurality of levels, wherein the movable space of the robot in the first target map is larger than that of the robot in the second target map.
Further, the probability thresholds for the multiple levels include: a first probability threshold and a second probability threshold, wherein the first probability threshold is greater than the second probability threshold.
Further, the robot map acquisition method further includes: judging whether the probability of each grid in the plurality of grids occupied by the obstacle is greater than or equal to a first probability threshold; determining that a grid with the probability of being occupied by an obstacle being greater than or equal to a first probability threshold value is a grid with the obstacle, and determining that a grid with the probability of being occupied by the obstacle being less than the first probability threshold value is a grid without the obstacle, so as to obtain first obstacle distribution information; a first target map is acquired based on the obstacle distribution information.
Further, the robot map acquisition method further includes: judging whether the probability of each grid of the plurality of grids occupied by the obstacle is greater than or equal to a second probability threshold; determining that a grid with the probability of being occupied by the obstacle being greater than or equal to a second probability threshold value is a grid with the obstacle, and determining that a grid with the probability of being occupied by the obstacle being less than the second probability threshold value is a grid without the obstacle, so as to obtain second obstacle distribution information; a second target map is acquired based on the second obstacle distribution information.
Further, the robot map acquisition method further includes: acquiring the current moving speed of the robot; a target map matching the current moving speed is called from the first target map and the second target map.
Further, the robot map acquisition method further includes: judging whether the current moving speed is smaller than a preset speed threshold value or not; when the current moving speed is smaller than a preset speed threshold value, a first target map is called; and when the current moving speed is greater than or equal to a preset speed threshold value, calling a second target map.
Further, the robot map acquisition method further includes: acquiring a planned path; when the map area corresponding to the part of road segments in the planned path exists in the first target map independently, determining a first target speed in a first speed range, and when the map area corresponding to the part of road segments in the planned path exists in the first target map and the second target map together, determining a second target speed in a second speed range to obtain speed distribution information, wherein the first speed range and the second speed range are obtained by dividing a preset speed threshold, the speed value contained in the first speed range is smaller than the preset speed threshold, and the speed value contained in the second speed range is larger than or equal to the preset speed threshold; the robot is controlled to walk on the planned path based on the speed distribution information.
Further, the robot map acquisition method further includes: in the process of controlling the robot to walk according to a preset path, performing environment scanning through a laser radar arranged on the robot, and acquiring distance information between the robot and an obstacle according to laser reflection; the data information is calculated using the distance information.
According to another aspect of the embodiment of the present invention, there is also provided a robot map acquisition apparatus including: the system comprises a creation module, a calculation module and a calculation module, wherein the creation module is used for creating an initial map, the initial map is a grid map, and the grid map comprises: a plurality of grids; the first acquisition module is used for controlling the robot to walk in the initial map according to a preset path and acquiring data information, wherein the data information is used for describing the probability that each grid in the multiple grids is occupied by an obstacle; and the second acquisition module is used for acquiring the first target map and the second target map by utilizing the probability threshold values and the data information of a plurality of levels, which are preset, wherein the movable space of the robot in the first target map is larger than that of the robot in the second target map.
According to another aspect of the embodiments of the present invention, there is also provided a non-volatile storage medium in which a computer program is stored, wherein the computer program is configured to perform the robot map acquisition method described above when run.
According to another aspect of the embodiments of the present invention, there is also provided a processor for running a program, wherein the program is configured to execute the robot map acquisition method described above at run time.
According to another aspect of the embodiments of the present invention, there is also provided an electronic device including a memory in which a computer program is stored, and a processor configured to run the computer program to perform the robot map acquisition method described above.
In the embodiment of the invention, by setting different grid maps according to probability thresholds of different levels, an initial map is created, a robot is controlled to walk in the initial map according to a preset path so as to acquire data information, and then a first target map and a second target map are acquired by utilizing the probability thresholds of a plurality of levels and the data information, wherein the initial map is a grid map, and the grid map comprises: a plurality of grids, the data information describing a probability that each of the plurality of grids is occupied by an obstacle, the robot's movable space in the first target map being greater than the robot's movable space in the second target map.
In the process, probability thresholds of multiple levels are set, different target maps are generated according to different probability thresholds, and due to the fact that the probability thresholds among the different target maps are different, risks of collision with obstacles when the robot moves in a movable space in the target map are different, wherein the movable space in the target map characterizes the level of risk of collision with the obstacles when the robot moves in the target map, in practical application, the robot can select an appropriate target map according to scene requirements, collision of the robot when the robot moves in the target map is reduced, and safety of robot movement is improved.
Therefore, the scheme provided by the application achieves the purpose of reducing the collision generated when the robot moves, so that the technical effect of improving the safety of the robot movement is achieved, and the technical problem that the robot is easy to collide and then fails due to inaccurate grid map is solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on the invention. In the drawings:
fig. 1 is a flowchart of a robot map acquisition method according to an embodiment of the present invention;
FIG. 2 is a schematic illustration of an alternative grid map according to an embodiment of the invention;
FIG. 3 is a schematic illustration of an alternative first target map according to an embodiment of the invention;
FIG. 4 is a schematic illustration of an alternative second target map according to an embodiment of the invention;
FIG. 5 is a flow chart of an alternative generation of a target map based on different levels of probability threshold values in accordance with an embodiment of the present invention;
FIG. 6 is a flow chart of an alternative robotic map acquisition method according to an embodiment of the invention;
FIG. 7 is a flowchart of an alternative invocation of a target map according to the speed of movement of the robot, in accordance with an embodiment of the invention;
FIG. 8 is a flow chart of an alternative planning of the movement speed of a robot according to an embodiment of the invention;
fig. 9 is a schematic view of a robotic map acquiring device according to an embodiment of the invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
According to an embodiment of the present invention, there is provided an embodiment of a robot map acquisition method, it being noted that the steps shown in the flowcharts of the drawings may be performed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowcharts, in some cases the steps shown or described may be performed in an order different from that herein.
Fig. 1 is a flowchart of a robot map acquisition method according to an embodiment of the present invention, as shown in fig. 1, the method including the steps of:
step S102, an initial map is created, wherein the initial map is a grid map, and the grid map comprises: a plurality of grids, a plurality of grids.
Alternatively, in step S102, an environmental image on which the robot is to travel may be first acquired, and then the environmental image may be divided into planar grids of equal resolution, to obtain a grid map, for example, fig. 2 shows a schematic diagram of an alternative grid map, in which 300 grids are included in the grid map shown in fig. 2, and each grid is equal in size.
Step S104, the robot is controlled to walk in the initial map according to a preset path, and data information is acquired, wherein the data information is used for describing the probability that each grid in the multiple grids is occupied by an obstacle.
Optionally, a laser radar is installed on the robot, and when the robot walks on the initial map according to a preset path, the laser radar scans the surrounding environment by 360 degrees to collect the distance between the obstacle and the robot, and the robot determines the probability of the grid occupied by the obstacle according to the distance. For example, in the schematic diagram of the grid map shown in fig. 2, different colors represent different probability ranges, for example, the first grid probability range represents a grid in which the probability that the grid is occupied by an obstacle is 90% or more and 100% or less; the second grid probability range represents a grid having a probability of the grid being occupied by an obstacle of 80% or more and less than 90%; the third grid probability range represents a grid having a probability that the grid is occupied by an obstacle of 0% or more and less than 80%.
And S106, acquiring a first target map and a second target map by utilizing the probability threshold values and the data information of a plurality of levels, wherein the movable space of the robot in the first target map is larger than that of the robot in the second target map.
In step S106, the probability threshold includes two levels, and the probability threshold for the plurality of levels includes: a first probability threshold and a second probability threshold, wherein the first probability threshold is greater than the second probability threshold, e.g., the first probability threshold may be 90% and the second probability threshold 80%. Optionally, the probability threshold values corresponding to the first target map and the second target map are different, the first target map corresponds to the first probability threshold value, the second target map corresponds to the second probability threshold value, and since the first probability threshold value is greater than the second probability threshold value, the movable space of the robot in the first target map is greater than the movable space of the robot in the second target map, for example, fig. 3 is a schematic diagram of the first target map, fig. 4 is a schematic diagram of the second target map, in fig. 3 and 4, the black area represents the area where the grid occupied by the obstacle is located, the white area represents the area where the grid not occupied by the obstacle is located, and as can be seen from fig. 3 and 4, the movable space of the robot in the first target map (white area in fig. 3) is greater than the movable space of the robot in the second target map (white area in fig. 4).
Optionally, after the probability that each grid is occupied by the obstacle is obtained, determining whether the grid has the obstacle according to the probability that each grid is occupied by the obstacle, for example, in the first target map, determining that the grid a is occupied by the obstacle if the probability that the grid a is occupied by the obstacle is greater than or equal to 90%; for another example, in the first target map, the probability that the grid B is occupied by an obstacle is less than 90%, and it is determined that the grid B is not occupied by an obstacle. In the second target map, if the probability that the grid C is occupied by the obstacle is greater than or equal to 80%, determining that the grid C is occupied by the obstacle; for another example, in the second target map, the probability that the grid D is occupied by an obstacle is less than 80%, and it is determined that the grid D is not occupied by an obstacle.
In practical application, the robot can select a matched target map according to the moving speed of the robot, so as to reduce the risk of collision between the robot and an obstacle when the robot moves in the target map, and further improve the safety of the robot when the robot moves.
Note that, the level of the probability threshold is not limited to the above two, and the specific number may be set according to the actual requirement, and is not limited herein.
Based on the above-mentioned schemes defined in step S102 to step S106, it may be known that in the embodiment of the present invention, by setting different grid maps according to probability thresholds of different levels, an initial map is created, and a robot is controlled to walk in the initial map according to a preset path, so as to obtain data information, and then, a first target map and a second target map are obtained by using probability thresholds of a plurality of levels and the data information, which are set in advance, where the initial map is a grid map, and the grid map includes: a plurality of grids, the data information describing a probability that each of the plurality of grids is occupied by an obstacle, the robot's movable space in the first target map being greater than the robot's movable space in the second target map.
It is easy to note that in the above process, probability thresholds of multiple levels are set, different target maps are generated according to different probability thresholds, and due to the fact that the probability thresholds between different target maps are different, risks of collision with obstacles when the robot moves in a movable space in the target map are different, wherein the movable space in the target map characterizes the level of risk of collision with the obstacles when the robot moves in the target map, in practical application, the robot can select a proper target map according to scene requirements, collisions of the robot when moving in the target map are reduced, and safety of robot movement is improved.
Therefore, the scheme provided by the application achieves the purpose of reducing the collision generated when the robot moves, so that the technical effect of improving the safety of the robot movement is achieved, and the technical problem that the robot is easy to collide and then fails due to inaccurate grid map is solved.
In an alternative embodiment, after creating the initial map, the robot is controlled to walk in the initial map according to a preset path to acquire the data information. Specifically, in the process of controlling the robot to walk according to a preset path, environmental scanning is performed through a laser radar arranged on the robot, distance information between the robot and an obstacle is collected according to reflection of laser, and then data information is calculated by using the distance information.
It should be noted that the probability that each grid is occupied by an obstacle (i.e., data information) obtained by the above calculation may be the probability that the center point of each grid is occupied by an obstacle.
In an alternative embodiment, in practical application, the robot may call the corresponding target map according to the actual requirement, and optionally, a plurality of target maps are stored in the robot, and the target map is a grid map. Optionally, to save a plurality of target maps with different risk degrees, a plurality of probability thresholds with different levels may be set, where the larger the probability threshold is, the wider the robot movable space for generating the target map is, and the higher the risk that the robot collides with an obstacle. Alternatively, fig. 5 shows an alternative flow chart for generating a target map based on probability thresholds of different levels, wherein fig. 5 sets probability thresholds of two different levels, wherein the first probability threshold is 90% and the second probability threshold is 80%.
Specifically, whether the probability of each of the plurality of grids being occupied by an obstacle is greater than or equal to a first probability threshold is determined, a grid of the plurality of grids, which is occupied by an obstacle and has a probability of being greater than or equal to the first probability threshold, is determined to be a grid with an obstacle, and a grid of the plurality of grids, which is occupied by an obstacle and has a probability of being less than the first probability threshold, is determined to be a grid without an obstacle, first obstacle distribution information is obtained, and a first target map is obtained based on the obstacle distribution information.
Optionally, in fig. 5, a probability map is generated after the laser radar scans the surrounding map, and a grid with a probability of being occupied by an obstacle being greater than or equal to 90% (a first probability threshold) is determined as an obstacle; and judging that the barrier does not exist in the grid with the probability of being occupied by the barrier less than 90 percent (a first probability threshold), finally generating a first target map with high risk, and storing the first target map in the robot.
Similarly, for the second target map, it is first determined whether the probability of each of the plurality of grids being occupied by the obstacle is greater than or equal to a second probability threshold, then the grids of the plurality of grids having the probability of being occupied by the obstacle greater than or equal to the second probability threshold are determined as the grids having the obstacle, and the grids of the plurality of grids having the probability of being occupied by the obstacle less than the second probability threshold are determined as the grids having no obstacle, second obstacle distribution information is obtained, and the second target map is acquired based on the second obstacle distribution information.
Optionally, in fig. 5, a probability map is generated after the laser radar scans the surrounding map, and a grid with a probability of being occupied by an obstacle being greater than or equal to 80% (second probability threshold) is determined as an obstacle; and judging that the grid with the probability of being occupied by the obstacle being less than 80% (second probability threshold) is not provided with the obstacle, finally generating a second target map with high risk, and storing the second target map in the robot.
In an alternative embodiment, when the laser scans the surrounding environment, due to different materials of scanned objects and different reflection degrees, errors exist in the finally generated grid map, calibration of the obstacle cannot reach 100% accuracy, and the robot runs in the built target map and is at risk of collision. In order to reduce collision damage of the robot, the moving speed of the robot is read in real time in the running process of the robot. Specifically, the current moving speed of the robot is firstly obtained, and a target map matched with the current moving speed is called from the first target map and the second target map.
Optionally, fig. 6 shows a flowchart of an alternative robot map acquisition method, and as can be seen from fig. 6, after setting different probability thresholds, the probability that each grid in the grid map is occupied by an obstacle is acquired, then a corresponding target map is generated according to the different probability thresholds, and the target map is stored in the robot. In practical application, after the current moving speed is obtained, the robot matches the corresponding target map according to the current moving speed of the robot.
Specifically, judging whether the current moving speed is smaller than a preset speed threshold, wherein when the current moving speed is smaller than the preset speed threshold, a first target map is called; and when the current moving speed is greater than or equal to a preset speed threshold value, calling a second target map.
Optionally, fig. 7 shows an optional flow chart for calling a target map according to a moving speed of the robot, and as can be seen from fig. 7, after the current moving speed of the robot is obtained, when the current moving speed of the robot is less than 2cm/s (i.e. a preset speed threshold), the robot is determined to be in a low-speed moving state, and the damage to the robot caused by low-speed collision is less, at this time, a first target map with a larger risk can be called for the robot, and the robot can move in a larger space; when the current moving speed of the robot is greater than or equal to 2cm/s (namely a preset speed threshold value), the robot is judged to be in a high-speed moving state, and the damage caused by high-speed collision of the robot is larger, and a second target map with lower risk is called for use at the moment, so that the robot operates in a smaller space as safe as possible.
In an alternative embodiment, the robot may also plan the movement speed of the robot according to the planned path of the robot. Specifically, after the planned path is acquired, when a map area corresponding to a part of road segments in the planned path exists in a first target map alone, determining a first target speed in a first speed range, and when the map area corresponding to the part of road segments in the planned path exists in the first target map and a second target map together, determining a second target speed in a second speed range, obtaining speed distribution information, and controlling the robot to walk on the planned path based on the speed distribution information. The first speed range and the second speed range are obtained by dividing a preset speed threshold, the speed value contained in the first speed range is smaller than the preset speed threshold, and the speed value contained in the second speed range is larger than or equal to the preset speed threshold.
Alternatively, fig. 8 shows an alternative flow chart for planning the movement speed of the robot, and as can be seen from fig. 8, the robot first reads all the stored target maps (i.e. the first target map and the second target map) and plans the path in all the movable active areas in both target maps. Then, speed matching is carried out according to a target map corresponding to the planned path, for example, when the planned path only exists in an active area of a first target map with high risk, the speed of the robot is planned in a range (namely, a first speed range) with the speed less than 2 cm/s; to increase robot work efficiency, the speed of the robot may be planned in a range where the speed is greater than or equal to 2cm/s (i.e., a second speed range) when the planned path may exist in the active area of the first target map of low risk. And finally, the robot combines the path planning and the speeds corresponding to the segmented paths to finish the final operation task planning.
From the above, the method and the device can store the target maps with different risk degrees, and adapt the target maps with different risk degrees through the height of the moving speed of the robot, so that the robot does not collide in the high-speed moving process, the collision force of the collision is reduced in the low-speed moving process, and the safety of the robot is ensured. In addition, the moving speed of the robot can be planned according to the path planning, the collision risk of the robot and the obstacle can be reduced, and the moving safety of the robot is ensured.
Example 2
According to an embodiment of the present invention, there is further provided an embodiment of a robot map acquisition method, wherein fig. 9 is a schematic diagram of a robot map acquisition apparatus according to an embodiment of the present invention, as shown in fig. 9, the apparatus includes: a creation module 901, a first acquisition module 903 and a second acquisition module 905.
The creating module 901 is configured to create an initial map, where the initial map is a grid map, and the grid map includes: a plurality of grids; a first obtaining module 903, configured to control the robot to walk in the initial map according to a preset path, and obtain data information, where the data information is used to describe a probability that each of the multiple grids is occupied by an obstacle; the second obtaining module 905 is configured to obtain a first target map and a second target map by using probability thresholds and data information of a plurality of levels, where an available space of the robot in the first target map is greater than an available space of the robot in the second target map.
It should be noted that the creation module 901, the first acquisition module 903, and the second acquisition module 905 correspond to steps S102 to S106 in the above embodiment, and the three modules are the same as examples and application scenarios implemented by the corresponding steps, but are not limited to those disclosed in the above embodiment 1.
Optionally, the probability threshold for the plurality of levels includes: a first probability threshold and a second probability threshold, wherein the first probability threshold is greater than the second probability threshold.
Optionally, the second obtaining module includes: the device comprises a first judging module, a first determining module and a third obtaining module. The first judging module is used for judging whether the probability of each grid of the multiple grids occupied by the obstacle is larger than or equal to a first probability threshold value; a first determining module, configured to determine that a grid with a probability of being occupied by an obstacle greater than or equal to a first probability threshold is a grid with an obstacle, and determine that a grid with a probability of being occupied by an obstacle less than the first probability threshold is a grid without an obstacle, so as to obtain first obstacle distribution information; and a third acquisition module for acquiring the first target map based on the obstacle distribution information.
Optionally, the second obtaining module includes: the device comprises a second judging module, a second determining module and a fourth obtaining module. The second judging module is used for judging whether the probability of each grid of the multiple grids occupied by the obstacle is larger than or equal to a second probability threshold value; a second determining module, configured to determine that a grid with a probability of being occupied by an obstacle greater than or equal to a second probability threshold is a grid with an obstacle, and determine that a grid with a probability of being occupied by an obstacle less than the second probability threshold is a grid without an obstacle, so as to obtain second obstacle distribution information; and a fourth acquisition module for acquiring a second target map based on the second obstacle distribution information.
Optionally, the robot map acquiring apparatus further includes: and a fifth acquisition module and a calling module. The fifth acquisition module is used for acquiring the current moving speed of the robot; and the calling module is used for calling the target map matched with the current moving speed from the first target map and the second target map.
Optionally, the calling module includes: the device comprises a third judging module, a first calling module and a second calling module. The third judging module is used for judging whether the current moving speed is smaller than a preset speed threshold value or not; the first calling module is used for calling the first target map when the current moving speed is smaller than a preset speed threshold value; and the second calling module is used for calling a second target map when the current moving speed is greater than or equal to a preset speed threshold value.
Optionally, the robot map acquiring apparatus further includes: the device comprises a sixth acquisition module, a third determination module and a control module. The sixth acquisition module is used for acquiring the planned path; the third determining module is configured to determine a first target speed in a first speed range when a map area corresponding to a part of road segments in the planned path exists in a first target map alone, and determine a second target speed in a second speed range when the map area corresponding to the part of road segments in the planned path exists in the first target map and a second target map together, so as to obtain speed distribution information, where the first speed range and the second speed range are divided by a preset speed threshold, a speed value included in the first speed range is smaller than the preset speed threshold, and a speed value included in the second speed range is greater than or equal to the preset speed threshold; and the control module is used for controlling the robot to walk on the planned path based on the speed distribution information.
Optionally, the first obtaining module includes: the system comprises an acquisition module and a calculation module. The acquisition module is used for carrying out environment scanning through a laser radar arranged on the robot in the process of controlling the robot to walk according to a preset path and acquiring distance information between the robot and an obstacle according to the reflection of laser; and the calculating module is used for calculating the data information by utilizing the distance information.
Example 3
According to another aspect of the embodiments of the present invention, there is also provided a nonvolatile storage medium in which a computer program is stored, wherein the computer program is configured to execute the robot map acquisition method in the above embodiment 1 at the time of execution.
Example 4
According to another aspect of the embodiments of the present invention, there is also provided a processor for running a program, wherein the program is configured to execute the robot map acquisition method in embodiment 1 described above at the time of running.
Example 5
According to another aspect of the embodiments of the present invention, there is also provided an electronic device including a memory in which a computer program is stored, and a processor configured to run the computer program to perform the robot map acquisition method in the above embodiment 1.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
In the foregoing embodiments of the present invention, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed technology content may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of the units, for example, may be a logic function division, and may be implemented in another manner, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (11)
1. A robot map acquisition method, comprising:
creating an initial map, wherein the initial map is a grid map, and the grid map comprises: a plurality of grids;
the robot is controlled to walk in the initial map according to a preset path, and data information is obtained, wherein the data information is used for describing the probability that each grid in the multiple grids is occupied by an obstacle;
acquiring a first target map and a second target map by using preset probability thresholds of a plurality of grades and the data information, wherein the movable space of the robot in the first target map is larger than that of the robot in the second target map, and the probability thresholds of the plurality of grades comprise: a first probability threshold and a second probability threshold, the first probability threshold being greater than the second probability threshold, the first target map being determined by first obstacle distribution information, the first obstacle distribution information comprising: a grid of the plurality of grids having a probability of being occupied by an obstacle greater than or equal to the first probability threshold, a grid of the plurality of grids having a probability of being occupied by an obstacle less than the first probability threshold, the second target map being determined from second obstacle distribution information, the second obstacle distribution information comprising: a grid of the plurality of grids having a probability of being occupied by an obstacle greater than or equal to the second probability threshold, a grid of the plurality of grids having a probability of being occupied by an obstacle less than the second probability threshold.
2. The robotic map acquisition method of claim 1, wherein acquiring the first target map using the probability threshold for the plurality of levels and the data information comprises:
determining whether a probability of each of the plurality of grids being occupied by the obstacle is greater than or equal to the first probability threshold;
determining that a grid with a probability of being occupied by the obstacle being greater than or equal to the first probability threshold value is a grid with the obstacle, and determining that a grid with a probability of being occupied by the obstacle being less than the first probability threshold value is a grid without the obstacle, so as to obtain first obstacle distribution information;
the first target map is acquired based on the first obstacle distribution information.
3. The robotic map acquisition method of claim 1, wherein acquiring the second target map using the probability threshold for the plurality of levels and the data information comprises:
determining whether a probability of each of the plurality of grids being occupied by the obstacle is greater than or equal to the second probability threshold;
determining that a grid with the probability of being occupied by the obstacle being greater than or equal to the second probability threshold value is a grid with the obstacle, and determining that a grid with the probability of being occupied by the obstacle being less than the second probability threshold value is a grid without the obstacle, so as to obtain second obstacle distribution information;
and acquiring the second target map based on the second obstacle distribution information.
4. The robotic map acquisition method of claim 1, wherein the method further comprises:
acquiring the current moving speed of the robot;
and calling a target map matched with the current moving speed from the first target map and the second target map.
5. The robotic map acquisition method of claim 4, wherein invoking the target map matching the current movement speed from the first target map and the second target map comprises:
judging whether the current moving speed is smaller than a preset speed threshold value or not;
when the current moving speed is smaller than the preset speed threshold value, the first target map is called;
and when the current moving speed is greater than or equal to the preset speed threshold value, calling the second target map.
6. The robotic map acquisition method of claim 1, wherein the method further comprises:
acquiring a planned path;
when a map area corresponding to a part of road segments in the planning path exists in the first target map independently, determining a first target speed in a first speed range, and when map areas corresponding to the part of road segments in the planning path exist in the first target map and the second target map together, determining a second target speed in a second speed range to obtain speed distribution information, wherein the first speed range and the second speed range are obtained by dividing a preset speed threshold, a speed value contained in the first speed range is smaller than the preset speed threshold, and a speed value contained in the second speed range is larger than or equal to the preset speed threshold;
and controlling the robot to walk on the planned path based on the speed distribution information.
7. The robot map acquisition method according to claim 1, wherein controlling the robot to walk in the initial map according to the preset path, the acquiring the data information includes:
in the process of controlling the robot to walk according to the preset path, performing environment scanning through a laser radar arranged on the robot, and collecting distance information between the robot and the obstacle according to reflection of laser;
and calculating the data information by using the distance information.
8. A robot map acquisition apparatus, comprising:
the system comprises a creation module, a storage module and a storage module, wherein the creation module is used for creating an initial map, the initial map is a grid map, and the grid map comprises: a plurality of grids;
the first acquisition module is used for controlling the robot to walk in the initial map according to a preset path and acquiring data information, wherein the data information is used for describing the probability that each grid in the multiple grids is occupied by an obstacle;
a second obtaining module, configured to obtain a first target map and a second target map by using a probability threshold value of a plurality of levels and the data information, where an available space of the robot in the first target map is greater than an available space of the robot in the second target map, and the probability threshold values of the plurality of levels include: a first probability threshold and a second probability threshold, the first probability threshold being greater than the second probability threshold, the first target map being determined by first obstacle distribution information, the first obstacle distribution information comprising: a grid of the plurality of grids having a probability of being occupied by an obstacle greater than or equal to the first probability threshold, a grid of the plurality of grids having a probability of being occupied by an obstacle less than the first probability threshold, the second target map being determined from second obstacle distribution information, the second obstacle distribution information comprising: a grid of the plurality of grids having a probability of being occupied by an obstacle greater than or equal to the second probability threshold, a grid of the plurality of grids having a probability of being occupied by an obstacle less than the second probability threshold.
9. A non-volatile storage medium, characterized in that a computer program is stored in the non-volatile storage medium, wherein the computer program is arranged to perform the robot map acquisition method of any one of claims 1 to 7 when run.
10. A processor, characterized in that the processor is adapted to run a program, wherein the program is arranged to execute the robot map acquisition method as claimed in any one of the claims 1 to 7 at run time.
11. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to run the computer program to perform the robot map acquisition method as claimed in any one of the claims 1 to 7.
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