CN112578798A - 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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Abstract
The invention discloses a robot map acquisition method, a robot map acquisition device, a robot map 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; controlling the robot to walk in an initial map according to a preset path, and acquiring data information, wherein the data information is used for describing the probability of each grid of the multiple grids being occupied by the obstacle; and acquiring a first target map and a second target map by using preset probability threshold values of multiple levels and data information, wherein the movable space of the robot in the first target map is larger than the movable space of the robot in the second target map. The invention solves the technical problem that the robot is easy to collide and further break down due to inaccurate grid maps.
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 the robot 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, a navigation path of the robot can be preset, and then the robot drives along the specified navigation path without human participation in the whole process.
At present, synchronous positioning and Mapping (SLAM) is that a robot positions its own position and posture through repeatedly detected surrounding environment features in a motion process in an unknown environment, and then incrementally constructs a map according to its own position, so as to achieve the purpose of simultaneously positioning and constructing the map.
The map can be a grid map, the creation of the grid map requires a laser radar installed on the robot, the occupancy of the grid is generated by sensing the distance from the obstacle, whether the obstacle exists in the grid is judged by a preset threshold value, and finally, a complete grid map is formed.
However, the grid map is not accurate enough due to laser scanning errors, and the robot is easy to collide with obstacles in the moving process, so that the robot is damaged and fails.
In view of the above problems, no effective solution has been proposed.
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, and aims to at least solve the technical problem that a robot is easy to collide and further break down due to inaccurate grid maps.
According to an aspect of an embodiment of the present invention, there is provided a robot map acquiring method, including: creating an initial map, wherein the initial map is a grid map, and the grid map comprises: a plurality of grids; controlling the robot to walk in an initial map according to a preset path, and acquiring data information, wherein the data information is used for describing the probability of each grid of the multiple grids being occupied by the obstacle; and acquiring a first target map and a second target map by using preset probability threshold values of multiple levels and data information, wherein the movable space of the robot in the first target map is larger than the movable space of the robot in the second target map.
Further, the probability thresholds for the plurality of 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: determining whether a probability of each of the plurality of grids being occupied by an obstacle is greater than or equal to a first probability threshold; determining a grid of the plurality of grids, the probability of which being occupied by the obstacle is greater than or equal to a first probability threshold, as a grid with the obstacle, and determining a grid of the plurality of grids, the probability of which being occupied by the obstacle is less than the first probability threshold, as a grid without the obstacle, 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: determining whether a probability of each of the plurality of grids being occupied by an obstacle is greater than or equal to a second probability threshold; determining grids with the probability of being occupied by the obstacle being greater than or equal to a second probability threshold value among the grids as grids with the obstacle, and determining grids with the probability of being occupied by the obstacle being less than the second probability threshold value among the grids as grids without the obstacle, so as to obtain second obstacle distribution information; and acquiring a second target map based on the second obstacle distribution information.
Further, the robot map acquisition method further includes: 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.
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, calling a first target map; and when the current moving speed is greater than or equal to the preset speed threshold value, calling a second target map.
Further, the robot map acquisition method further includes: acquiring a planned path; when map areas corresponding to part of road segments in a planned path exist in a first target map independently, determining a first target speed in a first speed range, and when the map areas corresponding to the part of road segments in the planned path exist in the first target map and a 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 through 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.
Further, the robot map acquisition method further includes: in the process of controlling the robot to walk according to a preset path, environmental scanning is carried out through a laser radar arranged on the robot, and distance information between the robot and an obstacle is collected according to reflection of laser; the data information is calculated using the distance information.
According to another aspect of the embodiments of the present invention, there is also provided a robot map acquiring apparatus including: the system comprises a creating module and a processing module, wherein the creating 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 robot comprises a first acquisition module, a second acquisition module and a control module, wherein the first acquisition module is used for controlling the robot to walk in an initial map according to a preset path and acquiring data information, and the data information is used for describing the probability of each grid of a plurality of grids being occupied by an obstacle; the second acquisition module is used for acquiring a first target map and a second target map by utilizing preset probability threshold values of multiple levels and 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.
According to another aspect of the embodiments of the present invention, there is also provided a non-volatile storage medium having a computer program stored therein, wherein the computer program is configured to execute the above-mentioned robot map acquisition method when running.
According to another aspect of the embodiments of the present invention, there is also provided a processor for executing a program, wherein the program is configured to execute the above-mentioned robot map acquisition method when running.
According to another aspect of the embodiments of the present invention, there is also provided an electronic apparatus, including a memory and a processor, where the memory stores a computer program, and the processor is configured to execute the computer program to perform the robot map acquisition method described above.
In the embodiment of the present invention, a method of setting different grid maps according to probability thresholds of different levels is adopted, an initial map is created, a robot is controlled to travel in the initial map according to a preset path to obtain data information, and then a first target map and a second target map are obtained by using preset probability thresholds of multiple levels and data information, wherein the initial map is a grid map, and the grid map includes: the data information is used for describing the probability of each grid in the grids being occupied by the obstacle, and the movable space of the robot in the first target map is larger than that of the robot in the second target map.
In the process, probability thresholds of multiple levels are set, different target maps are generated according to the different probability thresholds, and due to the fact that the probability thresholds of the different target maps are different, risks of collision between the robot and the obstacle when the robot moves in the movable space in the target map are different, wherein the movable space in the target map represents the level of risks of collision between the robot and the obstacle when the robot moves in the target map.
Therefore, the scheme provided by the application achieves the purpose of reducing collision when the robot moves, the technical effect of improving the moving safety of the robot is achieved, and the technical problem that the robot is prone to collision and then breaks down due to the fact that a grid map is inaccurate 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 embodiment(s) of the invention and together with the description serve to explain the invention without limiting 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 diagram of an alternative grid map according to an embodiment of the present 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 diagram of an alternative method for generating a target map based on different levels of probability thresholds according to an embodiment of the present invention;
FIG. 6 is a flow chart of an alternative robot map acquisition method according to an embodiment of the present invention;
FIG. 7 is a flow diagram of an alternative method for invoking a target map based on a moving speed of a robot, in accordance with embodiments of the present invention;
FIG. 8 is a flow chart of an alternative method of planning the travel speed of a robot in accordance with embodiments of the present invention;
fig. 9 is a schematic diagram of a robot map acquisition apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or 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
In accordance with an embodiment of the present invention, there is provided an embodiment of a method for robotic map acquisition, it being noted that the steps illustrated in the flowchart of the drawings may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than presented 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 image of an environment where the robot is to travel may be obtained, and then the environment is divided into planar grids with equal resolution to obtain a grid map, for example, fig. 2 shows a schematic diagram of an alternative grid map, and the grid map shown in fig. 2 includes 300 grids, and each grid has an equal size.
And step S104, 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 of each grid of the plurality of grids being occupied by the obstacle.
Optionally, the robot is provided with a laser radar, when the robot walks on the initial map according to the preset path, the laser radar scans the surrounding environment by 360 degrees to acquire the distance between the obstacle and the robot, and the robot determines the probability that the grid is 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 in which the probability that the grid is occupied by an obstacle is 80% or more and less than 90%; the third grid probability range represents a grid in which the probability that the grid is occupied by an obstacle is 0% or more and less than 80%.
And S106, acquiring a first target map and a second target map by utilizing preset probability threshold values of multiple levels and data information, wherein the movable space of the robot in the first target map is larger than the movable space of the robot in the second target map.
In step S106, the probability threshold includes two levels, and the probability thresholds of the plurality of levels include: 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 thresholds corresponding to the first target map and the second target map are different, the first target map corresponds to the first probability threshold, the second target map corresponds to the second probability threshold, since the first probability threshold is greater than the second probability threshold, the moveable space of the robot in the first target map is greater than the moveable space of the robot in the second target map, for example, FIG. 3 is a schematic view of a first target map, FIG. 4 is a schematic view of a second target map, in fig. 3 and 4, the black areas represent the areas where the grids occupied by the obstacles are located, and the white areas represent the areas where the grids not occupied by the obstacles are located, and it can be seen from fig. 3 and 4 that the movable space of the robot in the first target map (the white areas in fig. 3) is larger than the movable space of the robot in the second target map (the white areas in fig. 4).
Optionally, after obtaining the probability that each grid is occupied by the obstacle, 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, if the probability that the grid a is occupied by the obstacle is greater than or equal to 90%, determining that the grid a is occupied by the obstacle; for another example, in the first target map, the probability that the grid B is occupied by the obstacle is less than 90%, it is determined that the grid B is not occupied by the obstacle. And in the second target map, the probability that the grid C is occupied by the obstacle is greater than or equal to 80%, and then the grid C is determined to be occupied by the obstacle; for another example, in the second target map, the probability that the grid D is occupied by the obstacle is less than 80%, it is determined that the grid D is not occupied by the obstacle.
It should be noted that, in practical applications, the robot may select a matching 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.
It should be noted that the levels of the probability threshold are not limited to the two levels, and the specific number may be set according to actual needs, and is not limited herein.
Based on the solutions defined in steps S102 to S106, it can be known that, in the embodiment of the present invention, an initial map is created by setting different grid maps according to different levels of probability thresholds, and the robot is controlled to walk in the initial map according to a preset path to obtain data information, and then a first target map and a second target map are obtained by using preset multiple levels of probability thresholds and data information, where the initial map is a grid map, and the grid map includes: the data information is used for describing the probability of each grid in the grids being occupied by the obstacle, and the movable space of the robot in the first target map is larger than that of the robot 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 different probability thresholds between different target maps, risks of collision with obstacles when the robot moves in a movable space in the target map are different, where the movable space in the target map represents the level of risks of collision with the obstacles when the robot moves in the target map.
Therefore, the scheme provided by the application achieves the purpose of reducing collision when the robot moves, the technical effect of improving the moving safety of the robot is achieved, and the technical problem that the robot is prone to collision and then breaks down due to the fact that a grid map is inaccurate is solved.
In an alternative embodiment, after the initial map is created, 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, environment scanning is carried out 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 utilizing the distance information.
It should be noted that the probability (i.e., the data information) that each grid is occupied by the obstacle obtained by the above calculation may be the probability that the center point of each grid is occupied by the obstacle.
In an optional embodiment, in an actual application, the robot may call a corresponding target map according to an actual requirement, and optionally, a plurality of target maps are stored in the robot, where the target maps are grid maps. Optionally, in order to store 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 movable space of the robot generating the target map is, and the higher the risk that the robot collides with an obstacle is. Optionally, fig. 5 shows an optional flow chart of generating the target map based on different levels of probability thresholds, where fig. 5 sets two different levels of probability thresholds, where the first probability threshold is 90% and the second probability threshold is 80%.
Specifically, it is determined whether or not the probability that each of the plurality of grids is occupied by the obstacle is greater than or equal to a first probability threshold, a grid of the plurality of grids, the probability of which being occupied by the obstacle is greater than or equal to the first probability threshold, is determined as a grid in which the obstacle is present, and a grid of the plurality of grids, the probability of which being occupied by the obstacle is less than the first probability threshold, is determined as a grid in which the obstacle is not present, first obstacle distribution information is obtained, and the 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 environment map, and a grid with a probability of being occupied by an obstacle greater than or equal to 90% (a first probability threshold) is determined as the obstacle; and judging that no obstacle exists in the grids with the probability of being occupied by the obstacle being less than 90% (first probability threshold), finally generating a high-risk first target map, and storing the first target map in the robot.
Similarly, for the second target map, it is first determined whether the probability that each grid of the plurality of grids is occupied by the obstacle is greater than or equal to a second probability threshold, then the grid of the plurality of grids, the probability of which being occupied by the obstacle is greater than or equal to the second probability threshold, is determined as the grid with the obstacle, and the grid of the plurality of grids, the probability of which being occupied by the obstacle is less than the second probability threshold, is determined as the grid without the obstacle, so as to obtain second obstacle distribution information, and the second target map is obtained based on the second obstacle distribution information.
Optionally, in fig. 5, a probability map is generated after the laser radar scans the surrounding environment map, and a grid with a probability of being occupied by an obstacle greater than or equal to 80% (a second probability threshold) is determined as the obstacle; and judging the grids with the probability of being occupied by the obstacles being less than 80% (second probability threshold) as the grids without the obstacles, finally generating a high-risk second target map, and storing the second target map in the robot.
In an optional embodiment, when the surrounding environment is scanned by laser, due to the fact that scanned objects are different in material and different in reflection degree, errors exist in a finally generated grid map, calibration of obstacles cannot be accurate to 100%, and the robot runs in a built target map and risks 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 acquired, 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 obtaining method, and as can be seen from fig. 6, after different probability thresholds are set, the probability that each grid in the grid map is occupied by an obstacle is obtained, 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 robot acquires the current moving speed, the corresponding target map is matched according to the current moving speed of the robot.
Specifically, whether the current moving speed is smaller than a preset speed threshold value or not is judged, wherein when the current moving speed is smaller than the preset speed threshold value, a first target map is called; and when the current moving speed is greater than or equal to the preset speed threshold value, calling a second target map.
Optionally, fig. 7 shows an optional flowchart for calling a target map according to the 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), it is determined that the robot is in a low-speed moving state, and since the robot is damaged less by a low-speed collision, a first target map with a higher risk may be called for the robot to use, and the robot may 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), the robot is judged to be in a high-speed moving state, and a second target map with lower risk is called for use at the moment because the damage caused by high-speed collision of the robot is larger, so that the robot can run in a smaller space as safe as possible.
In an alternative embodiment, the robot may also plan the moving speed of the robot according to the planned path of the robot. Specifically, after the planned path is acquired, when map areas corresponding to part of road segments in the planned path exist in a first target map alone, a first target speed is determined in a first speed range, and when the map areas corresponding to part of road segments in the planned path exist in the first target map and a second target map together, a second target speed is determined in a second speed range, so that speed distribution information is obtained, and the robot is controlled 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 through 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 a flow chart of an alternative method for planning the moving 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 a path in all the movable active areas in the two target maps. Then, speed matching is carried out according to a target map corresponding to the planned path, for example, when only the moving area of a first target map with high risk exists in the planned path, the speed of the robot is planned within a range (namely a first speed range) with the speed less than 2 cm/s; to improve the robot work efficiency when the planned path may exist in the active area of the first target map with low risk, the speed of the robot may be planned within a range of speeds greater than or equal to 2cm/s (i.e., the second speed range). And finally, the robot completes the final operation task planning by combining the path planning and the speed corresponding to each segmented path.
By last, the target map of different risk degree can be stored to this application, through the target map of the different risk degree of the high-low adaptation of robot translation rate for the robot does not bump at high-speed removal in-process, moves the striking dynamics that the in-process reduced the collision at low-speed, has guaranteed robot safety. In addition, the moving speed of the robot can be planned according to the path planning, the collision risk of the robot and an obstacle can be reduced, and the moving safety of the robot is guaranteed.
Example 2
According to an embodiment of the present invention, there is also provided an embodiment of a robot map acquiring method, where fig. 9 is a schematic diagram of a robot map acquiring 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 an initial map according to a preset path, and obtain data information, where the data information is used to describe a probability that each grid 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 preset probability thresholds of multiple levels and data information, where a movable space of the robot in the first target map is larger than a movable space of the robot in the second target map.
It should be noted that the creating module 901, the first obtaining module 903, and the second obtaining module 905 correspond to steps S102 to S106 in the foregoing embodiment, and the three modules are the same as the corresponding steps in the implementation example and application scenarios, but are not limited to the disclosure in embodiment 1.
Optionally, the probability thresholds of multiple levels include: 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 judgment module, a first determination module and a third acquisition module. The first judging module is used for judging whether the probability of each grid in the plurality of grids occupied by the obstacle is larger than or equal to a first probability threshold value or not; a first determination module, configured to determine, as a grid with an obstacle, a grid with a probability of being occupied by the obstacle being greater than or equal to a first probability threshold among the plurality of grids, and determine, as a grid without an obstacle, a grid with a probability of being occupied by the obstacle being less than the first probability threshold among the plurality of grids, and obtain first obstacle distribution information; and the third acquisition module is used for acquiring the first target map based on the obstacle distribution information.
Optionally, the second obtaining module includes: the device comprises a second judgment module, a second determination module and a fourth acquisition module. The second judging module is used for judging whether the probability of each grid in the plurality of grids occupied by the obstacle is larger than or equal to a second probability threshold value or not; a second determination module, configured to determine, as a grid with an obstacle, a grid of the multiple grids, for which a probability of being occupied by the obstacle is greater than or equal to a second probability threshold, and determine, as a grid without an obstacle, a grid of the multiple grids, for which the probability of being occupied by the obstacle is less than the second probability threshold, so as to obtain second obstacle distribution information; and the fourth acquisition module is used for acquiring a second target map based on the second obstacle distribution information.
Optionally, the robot map acquiring apparatus further includes: a fifth obtaining 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; and the second calling module is used for calling the second target map when the current moving speed is greater than or equal to the preset speed threshold.
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 obtaining module is used for obtaining the planned path; a third determining module, 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 the 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 both the first target map and the second target map, so as to obtain speed distribution information, where the first speed range and the second speed range are obtained by dividing using 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 device comprises an acquisition module and a calculation module. The system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for scanning the environment through a laser radar arranged on the robot in the process of controlling the robot to walk according to a preset path and acquiring the distance information between the robot and an obstacle according to the reflection of laser; and the calculation module is used for calculating the data information by utilizing the distance information.
Example 3
According to another aspect of embodiments of the present invention, there is also provided a non-volatile storage medium having a computer program stored therein, wherein the computer program is configured to execute the robot map acquisition method in embodiment 1 described above when running.
Example 4
According to another aspect of the embodiments of the present invention, there is also provided a processor for executing a program, wherein the program is configured to execute the robot map acquiring method in embodiment 1 described above when running.
Example 5
According to another aspect of the embodiments of the present invention, there is also provided an electronic apparatus including a memory in which a computer program is stored and a processor configured to execute the computer program to perform the robot map acquiring method in embodiment 1 described above.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
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 can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute 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), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (12)
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;
controlling the robot to walk in the initial map according to a preset path to acquire data information, wherein the data information is used for describing the probability of each grid of the plurality of grids being occupied by the obstacle;
and acquiring a first target map and a second target map by using preset probability thresholds of multiple levels and the data information, wherein the movable space of the robot in the first target map is larger than the movable space of the robot in the second target map.
2. The robot map acquisition method according to claim 1, wherein the probability thresholds of the plurality of levels include: a first probability threshold and a second probability threshold, wherein the first probability threshold is greater than the second probability threshold.
3. The robot map acquisition method according to claim 2, wherein acquiring the first target map using the data information and the probability thresholds for the plurality of levels includes:
determining whether a probability of each grid of the plurality of grids being occupied by the obstacle is greater than or equal to the first probability threshold;
determining, as a grid in which the obstacle exists, a grid in which a probability of being occupied by the obstacle is greater than or equal to the first probability threshold among the plurality of grids, and determining, as a grid in which the obstacle does not exist, a grid in which the probability of being occupied by the obstacle is less than the first probability threshold among the plurality of grids, to obtain first obstacle distribution information;
acquiring the first target map based on the obstacle distribution information.
4. The robot map acquisition method according to claim 2, wherein acquiring the second target map using the data information and the probability thresholds for the plurality of levels includes:
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 a grid of the plurality of grids, the probability of which being occupied by the obstacle is greater than or equal to the second probability threshold, as a grid in which the obstacle exists, and determining a grid of the plurality of grids, the probability of which being occupied by the obstacle is less than the second probability threshold, as a grid in which the obstacle does not exist, to obtain second obstacle distribution information;
acquiring the second target map based on the second obstacle distribution information.
5. The robot map acquisition method according to claim 1, characterized in that the method further comprises:
acquiring the current moving speed of the robot;
calling a target map matching the current moving speed from the first target map and the second target map.
6. The robot map acquiring method according to claim 5, wherein the calling up a target map matching the current moving speed from the first target map and the second target map 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 the preset speed threshold value, calling the first target map;
and when the current moving speed is greater than or equal to the preset speed threshold value, calling the second target map.
7. The robot map acquisition method according to claim 1, characterized in that the method further comprises:
acquiring a planned path;
when map areas corresponding to part of road segments in the planned path exist in the first target map alone, determining a first target speed in a first speed range, and when the map areas corresponding to part of road segments in the planned 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 through 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.
8. The robot map acquisition method according to claim 1, wherein controlling the robot to walk in the initial map according to the preset path, and acquiring the data information includes:
in the process of controlling the robot to walk according to the preset path, environmental scanning is carried out through a laser radar arranged on the robot, and distance information between the robot and the obstacle is collected according to reflection of laser;
and calculating the data information by using the distance information.
9. A robot map acquisition apparatus, characterized by comprising:
the system comprises a creating module, a searching module and a processing module, wherein the creating 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 of each grid of the plurality of grids being occupied by an obstacle;
the second acquisition module is used for acquiring a first target map and a second target map by utilizing preset probability thresholds of multiple levels and the data information, wherein the movable space of the robot in the first target map is larger than the movable space of the robot in the second target map.
10. A non-volatile storage medium, in which a computer program is stored, wherein the computer program is arranged to execute the robot map acquisition method according to any one of claims 1 to 8 when running.
11. A processor for running a program, wherein the program is arranged to perform the robot map acquisition method of any of claims 1 to 8 when running.
12. An electronic device comprising a memory and a processor, wherein the memory has stored therein a computer program, and the processor is configured to execute the computer program to perform the robot map acquisition method according to any one of claims 1 to 8.
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