CN113865607A - Path planning method, device, equipment and storage medium - Google Patents
Path planning method, device, equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the application discloses a path planning method, a device, equipment and a storage medium, wherein the method comprises the following steps: grouping at least two points to be distributed to obtain a local path planning group; obtaining a local path corresponding to each local path planning group according to each point to be distributed in each local path planning group; generating a global path corresponding to the at least two local paths to be matched according to the local paths; by the technical scheme, the hardware computing force requirement on the executing equipment of the path planning method is reduced.
Description
Technical Field
The embodiment of the application relates to the technical field of path planning, in particular to a path planning method, a path planning device, a path planning equipment and a storage medium.
Background
With the continuous development of the robot technology, the robot starts to play a role in the life and work of people, wherein the mobile robot can help people to complete corresponding tasks in many scenes due to the flexibility and the maneuverability of the mobile robot, for example, in the scenes of logistics transportation, power inspection, indoor guidance and the like, the mobile robot gradually replaces the manual work to independently execute the designated work.
At present, the existing path planning method needs to plan the path for all the points to be distributed at one time, and has higher requirements on hardware computing power of executing equipment.
Disclosure of Invention
The application provides a path planning method, a device, equipment and a storage medium, which are used for reducing the computational power requirement on executing equipment of the path planning method.
In a first aspect, an embodiment of the present application provides a path planning method, where the method includes:
grouping at least two points to be distributed to obtain a local path planning group;
obtaining a local path corresponding to each local path planning group according to each point to be distributed in each local path planning group;
and generating a global path corresponding to the at least two points to be matched according to each local path. Further, the generating a global path corresponding to the at least two to-be-matched points according to each local path includes:
and generating a global path corresponding to the at least two to-be-distributed points according to the distribution sequence between each local path and each local path planning group.
Further, the generating a global path corresponding to the at least two points to be distributed according to the distribution sequence between each local path and each local path planning group includes:
determining a distribution sequence of a local path planning group to which the local path belongs according to the position information of the initial path point in the local path;
and generating a global path corresponding to the at least two to-be-distributed points according to each local path and the corresponding distribution sequence.
Further, if the local path planning group corresponds to at least two local paths, the generating a global path corresponding to the at least two to-be-delivered points according to the local paths of the local path planning group and the corresponding delivery sequence includes:
respectively selecting local path sequence combinations with different distribution sequences from each local path planning group to generate at least one candidate global path;
and selecting a target global path from the at least one candidate global path.
Further, the selecting a target global path from the at least one candidate global path includes:
judging whether a drivable path exists between adjacent points to be distributed of different local path planning groups in the candidate global path;
and selecting a target global path from the at least one candidate global path according to the judgment result.
Further, the grouping at least two points to be distributed to obtain a local path planning group includes:
matching each point to be distributed with each candidate distribution point in a preset planning group in the operation environment;
and according to the matching result, grouping the points to be distributed to obtain the local path planning group.
Further, the method further comprises:
determining the number of points to be distributed in each local path planning group;
and splitting the local path planning group of which the number of the points to be distributed is greater than a set number threshold into at least two local path planning groups.
Further, the splitting the local path planning group with the number of the points to be distributed larger than the set number threshold into at least two local path planning groups includes:
taking the local path planning group with the number of the points to be distributed larger than a set number threshold as a group to be dismantled;
and splitting the group to be split into at least two local path planning groups according to the position information of the point to be distributed in the group to be split.
In a second aspect, an embodiment of the present application further provides a path planning apparatus, where the apparatus includes:
the distribution point grouping module is used for grouping at least two points to be distributed to obtain at least one local path planning group;
the local path generation module is used for obtaining local paths corresponding to the local path planning groups according to the points to be distributed in the local path planning groups and the current positions of the robots;
and the global path generating module is used for generating the global paths corresponding to the at least two to-be-matched points according to the local paths.
In a third aspect, an embodiment of the present application further provides an electronic device, where the device includes:
one or more processors;
a storage device for storing one or more programs,
when the one or more programs are executed by the one or more processors, the one or more processors implement any one of the path planning methods provided in the embodiments of the first aspect.
In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements any one of the path planning methods provided in the embodiments of the first aspect.
According to the method and the device for generating the global path, after the local path planning groups are obtained by grouping the at least two points to be distributed, the local paths corresponding to the local path planning groups are obtained according to the points to be distributed in the local path planning groups, and the global paths corresponding to the at least two points to be distributed are generated according to the local paths. By the technical scheme, the local path planning of at least one to-be-distributed point in each grouped local path planning group is realized, and after the local paths corresponding to each local path planning group are obtained, the local paths are combined to obtain a global path, so that the overall path planning of the to-be-distributed points to be distributed by the robot is realized. The points to be distributed are grouped for local path planning, so that global path planning is not needed to be carried out on all the points to be distributed at one time, and the pressure of single path planning is dispersed, thereby reducing the hardware calculation force requirement on the execution equipment.
Drawings
Fig. 1 is a flowchart of a path planning method according to an embodiment of the present application;
fig. 2 is a flowchart of a path planning method according to a second embodiment of the present application;
fig. 3 is a schematic diagram of a packet path planning according to a second embodiment of the present application;
fig. 4 is a schematic diagram of a packet path planning according to a second embodiment of the present application;
fig. 5 is a flowchart of a path planning method provided in the third embodiment of the present application;
fig. 6 is a schematic diagram of a path planning apparatus according to a fourth embodiment of the present application;
fig. 7 is a schematic view of an electronic device provided in this application embodiment five.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be further noted that, for the convenience of description, only some of the structures related to the present application are shown in the drawings, not all of the structures.
Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the steps as a sequential process, many of the steps can be performed in parallel, concurrently or simultaneously. In addition, the order of the steps may be rearranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.
Example one
Fig. 1 is a flowchart of a path planning method according to an embodiment of the present application. The method and the device for planning the paths are suitable for the situation that the paths of the to-be-distributed points to be distributed by the robot are planned. The method may be performed by a path planning apparatus, which may be implemented by software and/or hardware, and is specifically configured in an electronic device, which may be a mobile terminal or a fixed terminal. For example, the electronic device may be a robot. The electronic device may also be a server, such as a background server for managing and controlling the robot.
Referring to fig. 1, a path planning method provided in the embodiment of the present application includes:
and S110, grouping at least two points to be distributed to obtain a local path planning group.
The point to be delivered refers to a point to be delivered by the robot, that is, a point to be delivered, where the point to be delivered may be a specific point to be delivered by the food delivery robot to a dining table to be delivered in a food delivery scene, and of course, the point to be delivered may also be a point to be delivered in other application scenes.
In this embodiment, the grouped local path planning group includes at least one point to be distributed, and the points to be distributed have consistent characteristics in terms of specific attributes, for example, the points to be distributed have similar geographical locations, or the points to be distributed belong to the same cell or the same building.
Optionally, according to the positions of the points to be distributed, cluster analysis may be performed on the points to be distributed, and the points to be distributed with similar positions may be divided into the same local path planning group. Specifically, the Algorithm used for cluster analysis may be a K-Means Clustering Algorithm (K-Means Clustering Algorithm), where K is the number of clusters, that is, the number of local path planning groups in this embodiment. When the points to be distributed are grouped by specifically adopting a K-Means algorithm, the K value can be reasonably determined according to the number of the points to be distributed. The points to be distributed with close positions are divided into the same local path planning group, so that the points with close positions are relatively close in the distribution sequence, the distribution efficiency is further improved, and the problems that the robot walks many repeated curves and the distribution efficiency is low due to the fact that the robot carries out a distribution task at the target point A after the robot carries out a distribution task at the target point A and then goes to the target point C with a long distance and then distributes the target point B and the like are solved.
Or optionally, at least two points to be distributed may be grouped according to input data of the user to obtain at least one local path planning group, where the input data of the user may be grouping preference data of the user, that is, a grouping situation of the points to be distributed is determined by the user.
In some embodiments, the local path planning groups may be grouped according to the distance between the point to be distributed and the current position of the robot, so as to obtain a preset number of local path planning groups, where the number of the local path planning groups may be determined according to a classification level of the distance, for example, the distance between the point to be distributed and the current position of the robot may be classified into three distance levels, including three levels, namely a very close level, a near level, and a far level.
For example, a part of the points to be delivered, which are closer to the current position of the robot (for example, the distance is less than 100 meters), may be divided into the same local path planning group; the method can divide the parts to be delivered which are far away from the current position of the robot (such as the distance is more than or equal to 100 meters and less than 200 meters) into the same local path planning group; parts of the points to be delivered which are far away from the current position of the robot (for example, the distance is more than or equal to 200 meters) can be divided into the same local path planning group.
It is understood that there are many forms of grouping, and there are other grouping manners besides the above-mentioned grouping manner, and an appropriate grouping manner can be selected according to actual situations.
And S120, obtaining the local path corresponding to each local path planning group according to each to-be-distributed point in each local path planning group.
The robot refers to an intelligent robot capable of autonomously or interactively executing various anthropomorphic tasks in various working environments. Specific types of robots generally include, but are not limited to, meal delivery robots, logistics robots, and delivery robots, among others.
In this embodiment, a preset local path planning method may be adopted to calculate and obtain the local path corresponding to each local path planning group according to the position of each point to be distributed in each local path planning group.
The preset local path planning method may be to determine travelable paths constructed by all the distribution points in each local path planning group according to the position relationship of each to-be-distributed point in each local path planning group, and after counting all the travelable paths, determine the local paths corresponding to the local path planning groups according to a preset path selection method (such as manual selection or preset rule selection). The local path corresponding to at least one local path planning group can be determined according to the requirement, and of course, the local paths corresponding to at least two local path planning groups can also be determined.
In some embodiments, under the condition of considering the actual working environment of the robot (for example, under the condition of considering congestion), a path planning method based on the shortest time principle can be adopted to calculate the local paths corresponding to the local path planning groups; or, a path planning method based on the shortest path principle may be adopted to calculate the local paths corresponding to the local path planning groups.
It can be understood that the local path planning method has various forms, and besides the above-mentioned local path planning method, there are other local path planning methods, and a suitable local path planning method may be selected according to actual situations, which is not limited in this embodiment of the present application.
And S130, generating at least two global paths corresponding to the points to be matched according to the local paths.
And the global path is formed by combining the local paths according to a set rule, and the generated global path is used for the robot to distribute all the points to be distributed.
For example, if there are three local paths A, B and C, a total of 6 global paths A-B-C, A-C-B, B-A-C, B-C-A, C-A-B and C-B-A can be generated. And the robot can preferentially distribute the points to be distributed in the local path with the combination order earlier in the global path.
In this embodiment, by calculating the local paths of each local path planning group, combining the local paths, and finally counting the obtained global path, a relatively superior path of at least two points to be distributed (more than 20 points to be distributed can be calculated) can be calculated by using a limited machine calculation power. In an optional embodiment, if the execution device of the path planning method is a robot, the hardware cost of the robot is reduced; if the executing device of the path planning method is a background server, the hardware cost of the server is reduced, and the high-concurrency executing condition of the path planning method can be adapted.
In an alternative embodiment, the local paths may be directly and randomly combined to generate a global path, so that the target robot proceeds to each point to be delivered according to the global path to obtain and deliver the article.
For example, in an order goods sorting scenario, if a certain order includes multiple target items and different target items are placed in points to be delivered, local paths can be planned for the points to be delivered in each local path planning group, and a global path is generated in a random combination manner. After the global path is generated, the robot is informed to go to the starting point of the global path or one of the points to be distributed, and the target articles are obtained along the global path until all the target articles are obtained. Or optionally, when the number of the robots is large, the target robot closer to the starting point of the global path is informed, and the target object starts to be acquired along the global path until all the target objects are acquired.
In another optional embodiment, a distribution sequence between the local path planning groups may also be determined, and then a global path corresponding to at least two points to be distributed is generated according to the distribution sequence between the local paths and the local path planning groups.
Optionally, when determining each local path planning group, the distribution sequence among the local path planning groups may be set manually, the correspondence between each local path planning group and the corresponding distribution sequence is stored in advance, and then the global path is generated according to the correspondence.
Optionally, the distribution order among the local path planning groups may also be determined according to the relative position relationship among the local path planning groups and/or the robot parking area. For example, the delivery order of the local path plan group close to the robot parking area is advanced, the delivery order of the local path plan group far from the robot parking area is advanced, and the like.
Optionally, according to preset preferences, manually setting delivery priorities for the local paths in advance, where the point to be delivered in the local path with the higher priority is delivered preferentially. For example, the point to be delivered in a local path is time-critical, and it is desirable that the robot can deliver in a short time, and in this case, a higher delivery priority may be manually set in advance for the local path.
For example, in a robot meal delivery scenario, the delivery priority of each local path may be determined according to at least one of attributes such as the type and weight of food items to be delivered at each point to be delivered, and the local path delivery order may be determined according to the determined priority. Continuing with the previous example, if the local path C has a higher priority, the global paths that can be generated are C-A-B and C-B-A.
Optionally, the sum of the waiting time lengths of the points to be distributed in each local path planning group is calculated, the sum of the waiting time lengths between the local path planning groups is compared, and the local path planning group with the largest value has the highest priority. Taking a robot meal delivery scene as an example, the long-term waiting of the user can be avoided, and the meal experience of the user is improved.
Or optionally, determining a global path corresponding to each local path according to the position relationship between each local path and the robot. For example, the combination order of the local paths in the global path may be determined according to the distance between the point to be delivered and the robot in the local paths.
In some embodiments, after the local paths with high priority are distributed, for each local path with the same priority, the combination order of each local path in the global path may be determined according to the position relationship between each local path and the robot.
It can be understood that, according to each local path, there are various forms of methods for generating the global path corresponding to all the points to be allocated, and the method can be selected according to actual situations.
It should be noted that, after the distribution sequence among the local path planning groups is determined, the first distributed local path planning group may perform local path planning based on the current position of the robot and the position information of each point to be distributed in the local path planning group; other local path planning groups carry out local path planning according to the position information of the ending path point in the local path planning group of the previous distribution sequence and the position information to be distributed in the local path planning group per se; correspondingly, the local paths are combined according to the distribution sequence among the local path planning groups to obtain the global path.
It is noted that global path planning is performed by means of the local paths of the local path planning groups and the distribution sequence among the local path planning groups, for instructing the robot to perform article acquisition or distribution according to the global path. When the robot runs according to the global path, the problems of low running efficiency, poor reproducibility of a global path planning result generated by the same point to be distributed and the like caused by neglecting the distribution sequence among the local path planning groups can be avoided.
According to the method and the device for generating the global path, after the local path planning groups are obtained by grouping the at least two points to be distributed, the local paths corresponding to the local path planning groups are obtained according to the points to be distributed in the local path planning groups, and the global paths corresponding to the at least two points to be distributed are generated according to the local paths. By the technical scheme, the local path planning of at least one to-be-distributed point in each grouped local path planning group is realized, and after the local paths corresponding to each local path planning group are obtained, the local paths are combined to obtain a global path, so that the overall path planning of the to-be-distributed points to be distributed by the robot is realized. The points to be distributed are grouped for local path planning, so that global path planning is not needed to be carried out on all the points to be distributed at one time, and the pressure of single path planning is dispersed, thereby reducing the hardware calculation force requirement on the execution equipment.
Example two
Fig. 2 is a flowchart of a path planning method provided in the second embodiment of the present application, and this embodiment is an optimization of the above-described scheme based on the above-described embodiment.
Further, the operation "generating a global path corresponding to the at least two points to be delivered according to each local path" is refined into "determining a delivery sequence of a local path planning group to which the local path belongs according to the position information of the initial path point in the local path; and generating a global path' corresponding to the at least two to-be-distributed points according to each local path and the corresponding distribution sequence so as to clarify the generation process of the global path.
Wherein explanations of the same or corresponding terms as those of the above-described embodiments are omitted.
Referring to fig. 2, the path planning method provided in this embodiment includes:
s210, grouping at least two points to be distributed to obtain a local path planning group.
And S220, obtaining the local path corresponding to each local path planning group according to each to-be-distributed point in each local path planning group.
And S230, determining the distribution sequence of the local path planning group to which the local path belongs according to the position information of the initial path point in the local path.
The starting path point in the local path refers to a point to be delivered, where the robot delivers the first time in the local path. Specifically, the point to be delivered closest to the current position of the robot in each local path may be used as the starting path point in the local path.
In this embodiment, for the local path planning group with the preferred distribution sequence, the robot preferentially distributes the points to be distributed in the local path planning group.
Alternatively, the distribution distance between the start path point in each local path and the robot may be determined according to the position information of the start path point in each local path and the position information of the robot, and the distribution order of the local path planning group to which the local path belongs may be determined according to the distribution distance.
Specifically, the shorter the distribution distance between the starting path point in the local path and the robot is, the robot preferentially distributes for the local path planning group where the starting path point is located.
Or alternatively, the delivery time length from the robot to the initial path point in each local path may be determined according to the position information of the initial path point in each local path and the position information of the robot, and the delivery order of the local path planning group to which the local path belongs may be determined according to the delivery time length.
Specifically, the shorter the delivery time from the robot to the starting path point in the local path, the robot will preferentially deliver for the local path planning group where the starting path point is located.
It can be understood that there are various ways to determine the distribution order of each local path planning group, which can be set according to actual situations, and certainly, the distribution order can also be determined for each local path planning group according to preference, and if an area where a certain local path planning group is located belongs to an area that needs to be distributed preferentially, the local path planning group can be distributed preferentially.
S240, generating at least two global paths corresponding to the to-be-distributed points according to the local paths and the corresponding distribution sequence.
Referring to fig. 3, a schematic diagram of a packet path plan is shown, which illustrates a case where there are A, B and C total three local path plan sets. The group A of local path planning groups comprise 4 points to be distributed in total, including P1, P2, P4 and P5, the group B of local path planning groups comprise 3 points to be distributed in total, including P3, P7 and P8, and the group C of local path planning groups comprise 5 points to be distributed in total, including P6, P9, P10, P11 and P12; the distribution sequence priority of the C group of local path planning groups is greater than that of the A group of local path planning groups, and the distribution sequence priority of the A group of local path planning groups is greater than that of the B group of local path planning groups. According to the local paths and the corresponding distribution orders, the local paths of the local path planning groups A, B and C may be sequentially connected according to the distribution order priority, so as to generate global paths corresponding to all the points to be distributed.
Specifically, according to the global path generated in fig. 3, the robot will distribute from the local path planning group C where the point to be distributed P12 is located, and after the robot reaches the point to be distributed P12, other points to be distributed (including P11, P10, P9, and P6) in the group C will be sequentially distributed according to the local path of the group C; after the robot finishes distributing the group C, the robot will come to the starting path point P4 of the group A, and then sequentially distribute other points to be distributed (including P2, P5 and P1) in the group A according to the local path of the group A; after the robot completes the distribution of the group a, the robot will come to the starting path point P8 of the group B, and then sequentially distribute the other points to be distributed (including P7 and P3) in the group B according to the local path of the group B, thereby completing the distribution of all the points to be distributed.
Optionally, if the local path planning group corresponds to at least two local paths, the generating a global path corresponding to the at least two to-be-delivered points according to each local path and the corresponding delivery order includes: respectively selecting local path sequence combinations with different distribution sequences from each local path planning group to generate at least one candidate global path; and selecting a target global path from the at least one candidate global path.
The local path planning group corresponds to at least two local paths, that is, in the local path planning group, at least two paths for distributing each point to be distributed in the local path planning group are provided.
The target global path refers to a final path for the selected robot to deliver.
Referring to fig. 4, a schematic diagram of a packet path plan is shown, in which the positions and numbers of points to be dispensed, and the current position of the robot are in accordance with those in fig. 3. Assuming that group a has only 1 local path R11(P4-P2-P5-P1), group B also has only 1 local path R21(P8-P7-P3), and group C has 2 local paths R31(P9-P10-P11-P12-P6) and R32(P12-P11-P10-P9-P6), the correspondingly generated global path may include two local path combinations, local path combinations R11, R21 and R31, and R11, R21 and R32, respectively.
Wherein, different local path combinations can correspond to different delivery orders. Assuming that the distribution sequence is from R11 to R21, from R21 to R31 in the local paths R11, R21 and R31, the corresponding generated global path is R11-R21-R31, i.e. the schematic diagram of the grouping path plan exemplarily shown in fig. 4; in the local paths R11, R21, and R32, the delivery order is from R32 to R11, from R11 to R21, and the corresponding generated candidate global path is R32-R11-R21, that is, the schematic diagram of the grouping path plan exemplarily shown in fig. 3.
Of course, the schematic diagrams of the grouping path planning shown in fig. 3 and fig. 4 are only a simpler case, and the actual situation is more complex, for example, each local path planning group may have a plurality of different local paths.
It can be understood that, if the local path planning groups correspond to at least two local paths, a local path sequence combination with a different delivery sequence can be selected from each local path planning group to generate at least one candidate global path, so that diversity of the global path is ensured, and selection of an optimal global path is facilitated.
Optionally, the selecting a target global path from the at least one candidate global path includes: judging whether a drivable path exists between adjacent points to be distributed of different local path planning groups in the candidate global path; and selecting a target global path from the at least one candidate global path according to the judgment result.
In this embodiment, whether a travelable path exists between adjacent points to be delivered can be determined by combining the working environment of the robot.
Continuing to refer to the schematic diagram of the block path plan shown in fig. 4, P1 is an end path point of the group a local path plan group, P8 is a start path point of the group B local path plan group, P1 and P8 are adjacent to-be-distributed points, and a practical passable path exists between the to-be-distributed points P1 and P8; and if all the adjacent points to be distributed have the travelable paths, the candidate global path can be reserved.
It can be understood that, through the screening mechanism of the travelable route, a target global route which can smoothly pass is screened out from at least one candidate global route, and the feasibility of the target global route is ensured.
In some embodiments, through a screening mechanism of the travelable paths, there may be more than one global path screened from at least one candidate global path, and at this time, the screened global paths may be further screened according to a shortest path rule or a shortest delivery time rule (real-time traffic information may be considered), and a target global path used by a final robot for delivery is selected from the global paths, so that the delivery efficiency is further improved.
Optionally, a first waiting time threshold is set, the waiting time of each point to be distributed under each candidate global path and the distribution time of each point to be distributed when the point to be distributed is distributed according to the corresponding candidate global path are calculated, and then the predicted waiting time of each point to be distributed under each candidate global path is obtained. That is, the expected wait period is equal to the waited period plus the delivery period.
Preferably, the candidate global path which can enable the predicted waiting time of the point to be distributed to be within the first waiting time threshold value range in the largest number is selected as the target global path. For example, if the first waiting time threshold is 20 minutes, the candidate global path that can maximize the number of to-be-delivered points whose expected waiting time is 20 minutes or less is selected as the target global path. The candidate global path which can complete the delivery when the delivery points are pressed as much as possible is selected as the target global path, and particularly in a food delivery environment, the delivery of each point to be delivered can be ensured not to be overtime as much as possible, and the user experience is further improved.
Further, a second waiting time threshold is set, the second waiting time threshold is a waiting upper limit threshold, the predicted waiting time of each point to be distributed in the target global path needs to be smaller than or equal to the second waiting time threshold, and the second waiting time threshold is larger than the first waiting time threshold, so that the situation that the distribution of part of points to be distributed is seriously overtime and the user experience is influenced is avoided. If the expected waiting time of a certain point to be distributed in each candidate global path is overtime, the point can be removed, the point is changed into manual distribution, and a global path is generated based on the remaining points to be distributed, so that the distribution efficiency and the user experience are ensured.
The embodiment of the application specifically refines the generation process of the global path on the basis of the above embodiment, determines the distribution sequence of the local path planning group to which the local path belongs according to the position information of the initial path point in the local path, and then generates the global path corresponding to at least two to-be-distributed points according to each local path and the corresponding distribution sequence. According to the technical scheme, the distribution sequence of each local path is determined by considering the position information of the initial path point in the local path, the local paths are combined according to the distribution sequence to obtain the global path, and the generation process of the global path is optimized, so that the problem of poor reproducibility of the global path planning result caused by neglecting the distribution sequence is avoided, and the distribution efficiency of the robot is improved.
In an optional embodiment, the local paths of the local path planning groups can be respectively determined in a parallel execution mode, and then the distribution sequence among the local path planning groups is obtained, so that the global path is generated, the generation efficiency of the global path can be obviously improved, and the distribution efficiency of the robot is further improved.
EXAMPLE III
Fig. 5 is a flowchart of a path planning method provided in the third embodiment of the present application, and this embodiment is an optimization of the above-described scheme based on the above-described embodiment.
Further, the operation of grouping at least two points to be distributed to obtain at least one local path planning group is refined into the operation of matching each point to be distributed with each candidate distribution point in a preset planning group in the operation environment; and according to the matching result, grouping the points to be distributed to obtain at least one local path planning group so as to clarify the generation process of the local path planning group.
Wherein explanations of the same or corresponding terms as those of the above-described embodiments are omitted.
Referring to fig. 5, the path planning method provided in this embodiment includes:
s310, matching each point to be distributed with each candidate distribution point in a preset planning group in the working environment.
The working environment of the robot can be a restaurant, a workshop or a sorting center.
The preset planning group is obtained by logically grouping the to-be-distributed points which are relatively centralized and close to each other in advance by combining the operation environment of the robot.
For example, in a robot meal delivery scenario, restaurants may be divided into a plurality of different preset plan groups according to dining areas of the restaurants, for example, restaurants may be divided into 5 preset plan groups of area a, area B, area C, area D, and area E. Wherein each preset planning group comprises at least one predetermined candidate delivery point.
Of course, when the working environment of the robot changes, the candidate distribution points in the preset planning group can be adjusted in time, so that the grouping setting of the candidate distribution points in the preset planning group is in accordance with reality.
Specifically, the manner of matching each point to be delivered with each candidate delivery point in the preset planning group in the working environment may be: matching the position of each point to be distributed with the position of each candidate distribution point in a preset planning group in the operation environment according to the position information of each point to be distributed; or, the identifier of each point to be distributed can be matched with the identifier of each candidate distribution point in a preset planning group in the working environment according to the identifier information of each point to be distributed.
And S320, grouping the points to be distributed according to the matching result to obtain a local path planning group.
In this embodiment, it is considered that the number of points to be distributed in each local path planning group after grouping is greatly different, which affects the local path planning of the local path planning group, and therefore, the number of points to be distributed in each local path planning group can be further determined; and splitting the local path planning group of which the number of the points to be distributed is greater than a set number threshold into at least two local path planning groups.
The set quantity threshold refers to a quantity limit requirement preset for the points to be distributed in the local path planning group, for example, the quantity of the points to be distributed in the grouped local path planning group is not greater than 5. Of course, the number of points to be distributed in the local path planning group may also be other number limiting requirements, such as 8 or 3, and the specific number limiting requirements may be reasonably set according to actual situations, which is not limited in this embodiment of the present application.
In some embodiments, if the number of the points to be distributed in the grouped local path planning group is greater than the set number threshold, the local path planning group may be further grouped again to meet the requirement of the local path planning group on the limitation of the number of the points to be distributed.
It can be understood that the number of the points to be distributed in the local path planning groups is limited by means of threshold comparison, so that the number of the points to be distributed in each local path planning group is reasonably controlled, the subsequent local path planning of the points to be distributed in the local path planning groups is facilitated, and the computation amount is reduced.
Specifically, the splitting the local path planning group whose number of the points to be distributed is greater than the set number threshold into at least two local path planning groups includes: taking the local path planning group with the number of the points to be distributed larger than a set number threshold as a group to be dismantled; and splitting the group to be split into at least two local path planning groups according to the position information of the point to be distributed in the group to be split.
In this embodiment, according to the position information of the to-be-distributed points in the to-be-distributed group, the to-be-distributed points with similar positions in the to-be-distributed group can be distributed to the same local path planning group by adopting a clustering analysis method such as a K-Means algorithm; or, for simplicity, after the central point of the group to be split is determined, the points to be distributed on the left of the connection line between the robot and the central point may be split into the same local path planning group, and the points to be distributed on the right of the connection line between the robot and the central point may be split into the same local path planning group. Of course, other grouping methods (such as a manual grouping method or a preset planning group matching method) may also be used to group the to-be-split groups.
It should be noted that, when all the points to be allocated are grouped for the first time, the used grouping method may be the same as or different from the above grouping method for grouping the groups to be split, and may be determined specifically according to the actual situation.
It can be understood that, considering the position information of the points to be distributed, the points to be distributed in the groups to be distributed are reasonably distributed, which is beneficial to performing the local path planning on the points to be distributed in the local path planning group subsequently.
And S330, obtaining the local path corresponding to each local path planning group according to each to-be-distributed point in each local path planning group.
And S340, generating at least two global paths corresponding to the points to be matched according to the local paths.
The method comprises the steps that on the basis of the embodiment, the generation process of the local path planning group is specifically refined, all points to be distributed are matched with all candidate distribution points in a preset planning group in the operation environment, and the points to be distributed are grouped according to the matching result to obtain at least one local path planning group; through the technical scheme, the points to be distributed are reasonably grouped according to the preset planning group in the operation environment, and the calculation amount of the process of determining the local path planning group is reduced, so that the generation process of the local path planning group is optimized, the path planning of the points to be distributed by the robot is facilitated, and the distribution efficiency of the robot is improved.
Example four
Fig. 6 is a schematic structural diagram of a path planning apparatus according to a fourth embodiment of the present application. Referring to fig. 6, a path planning apparatus provided in an embodiment of the present application includes: a distribution point grouping module 410, a local path generation module 420, and a global path generation module 430.
A distribution point grouping module 410, configured to group at least two points to be distributed to obtain a local path planning group;
a local path generating module 420, configured to obtain, according to each to-be-distributed point in each local path planning group, a local path corresponding to each local path planning group;
a global path generating module 430, configured to generate a global path corresponding to the at least two points to be provisioned according to each local path.
According to the method and the device for generating the global path, after the local path planning groups are obtained by grouping the at least two points to be distributed, the local paths corresponding to the local path planning groups are obtained according to the points to be distributed in the local path planning groups, and the global paths corresponding to the at least two points to be distributed are generated according to the local paths. By the technical scheme, the local path planning of at least one to-be-distributed point in each grouped local path planning group is realized, and after the local paths corresponding to each local path planning group are obtained, the local paths are combined to obtain a global path, so that the overall path planning of the to-be-distributed points to be distributed by the robot is realized. The points to be distributed are grouped for local path planning, so that global path planning is not needed to be carried out on all the points to be distributed at one time, and the pressure of single path planning is dispersed, thereby reducing the hardware calculation force requirement on the execution equipment.
Further, the distribution point grouping module 410 includes:
the matching sub-module is used for matching each point to be distributed with each candidate distribution point in a preset planning group in the operation environment;
and the first distribution point grouping submodule is used for grouping the points to be distributed according to the matching result to obtain the local path planning group.
Further, the distribution point grouping module 410 further includes:
the distribution point number determining submodule is used for determining the number of points to be distributed in each local path planning group;
and the second distribution point grouping submodule is used for splitting the local path planning groups of which the number of the points to be distributed is greater than the set number threshold into at least two local path planning groups.
Further, the global path generating module 403 includes:
and the global path generation submodule is used for generating the global paths corresponding to the at least two to-be-distributed points according to the distribution sequence between each local path and each local path planning group.
Further, the global path generation submodule includes:
a distribution sequence determining unit, configured to determine a distribution sequence of a local path planning group to which the local path belongs according to position information of a start path point in the local path;
and the path generating unit is used for generating a global path corresponding to the at least two to-be-delivered points according to each local path and the corresponding delivery sequence.
Further, the path generation unit includes:
a candidate path generation subunit, configured to, if the local path planning group corresponds to at least two local paths, select a local path sequence combination with a different delivery sequence from each local path planning group, and generate at least one candidate global path;
and the path selection subunit is used for selecting a target global path from the at least one candidate global path.
Further, the path generation subunit includes:
the judging slave unit is used for judging whether a drivable path exists between adjacent points to be distributed of different local path planning groups in the candidate global path; and the path generation slave unit is used for selecting a target global path from the at least one candidate global path according to the judgment result.
The path planning device provided by the embodiment of the application can execute the path planning method provided by any embodiment of the application, and has corresponding functional modules and beneficial effects of the execution method.
EXAMPLE five
Fig. 7 is a structural diagram of an electronic device according to a fifth embodiment of the present application. FIG. 7 illustrates a block diagram of an exemplary electronic device 512 suitable for use in implementing embodiments of the present application. The electronic device 512 shown in fig. 7 is only an example and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 7, the electronic device 512 is in the form of a general purpose computing device. Components of the electronic device 512 may include, but are not limited to: one or more processors or processing units 516, a system memory 528, and a bus 518 that couples the various system components including the system memory 528 and the processing unit 516.
The system memory 528 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)530 and/or cache memory 532. The electronic device 512 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 534 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 7, and commonly referred to as a "hard drive"). Although not shown in FIG. 7, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 518 through one or more data media interfaces. System memory 528 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the application.
A program/utility 540 having a set (at least one) of program modules 542 may be stored, for example, in system memory 528, such program modules 542 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. The program modules 542 generally perform the functions and/or methods of the embodiments described herein.
The electronic device 512 may also communicate with one or more external devices 514 (e.g., keyboard, pointing device, display 524, etc.), with one or more devices that enable a user to interact with the electronic device 512, and/or with any devices (e.g., network card, modem, etc.) that enable the electronic device 512 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interfaces 522. Also, the electronic device 512 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via the network adapter 520. As shown, the network adapter 520 communicates with the other modules of the electronic device 512 via the bus 518. It should be appreciated that although not shown in FIG. 7, other hardware and/or software modules may be used in conjunction with the electronic device 512, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processing unit 516 executes various functional applications and data processing by running at least one of other programs stored in the system memory 528, for example, implementing any of the path planning methods provided in the embodiments of the present application.
EXAMPLE six
An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements a path planning method provided in any embodiment of the present application, and the method includes:
grouping at least two points to be distributed to obtain at least one local path planning group; obtaining local paths corresponding to the local path planning groups according to the points to be distributed in the local path planning groups and the current positions of the robots; and generating a global path corresponding to the at least two points to be matched according to each local path.
From the above description of the embodiments, it is obvious for those skilled in the art that the present application can be implemented by software and necessary general hardware, and certainly can be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the methods described in the embodiments of the present application.
It should be noted that, in the embodiment of the path planning apparatus, each included unit and each included module are only divided according to functional logic, but are not limited to the above division, as long as the corresponding function can be implemented; in addition, specific names of the functional units are only used for distinguishing one functional unit from another, and are not used for limiting the protection scope of the application.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present application and the technical principles employed. It will be understood by those skilled in the art that the present application is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the application. Therefore, although the present application has been described in more detail with reference to the above embodiments, the present application is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present application, and the scope of the present application is determined by the scope of the appended claims.
Claims (11)
1. A method of path planning, comprising:
grouping at least two points to be distributed to obtain a local path planning group;
obtaining a local path corresponding to each local path planning group according to each point to be distributed in each local path planning group;
and generating a global path corresponding to the at least two points to be matched according to each local path.
2. The method according to claim 1, wherein the generating, according to each of the local paths, a global path corresponding to the at least two points to be delivered comprises:
and generating a global path corresponding to the at least two to-be-distributed points according to the distribution sequence between each local path and each local path planning group.
3. The method according to claim 2, wherein the generating a global path corresponding to the at least two points to be delivered according to the delivery order between each local path and each local path planning group comprises:
determining a distribution sequence of a local path planning group to which the local path belongs according to the position information of the initial path point in the local path;
and generating a global path corresponding to the at least two to-be-distributed points according to each local path and the corresponding distribution sequence.
4. The method according to claim 3, wherein if the local path planning group corresponds to at least two local paths, the generating a global path corresponding to the at least two to-be-delivered points according to each of the local paths and the corresponding delivery sequence comprises:
respectively selecting local path sequence combinations with different distribution sequences from each local path planning group to generate at least one candidate global path;
and selecting a target global path from the at least one candidate global path.
5. The method according to claim 4, wherein said selecting a target global path from said at least one candidate global path comprises:
judging whether a drivable path exists between adjacent points to be distributed of different local path planning groups in the candidate global path;
and selecting a target global path from the at least one candidate global path according to the judgment result.
6. The method according to claim 1, wherein the grouping of the at least two points to be distributed to obtain a local path plan group comprises:
matching each point to be distributed with each candidate distribution point in a preset planning group in the operation environment;
and according to the matching result, grouping the points to be distributed to obtain the local path planning group.
7. The method of claim 1, further comprising:
determining the number of points to be distributed in each local path planning group;
and splitting the local path planning group of which the number of the points to be distributed is greater than a set number threshold into at least two local path planning groups.
8. The method according to claim 7, wherein the splitting the local path plan group with the number of points to be distributed larger than a set number threshold into at least two local path plan groups comprises:
taking the local path planning group with the number of the points to be distributed larger than a set number threshold as a group to be dismantled;
and splitting the group to be split into at least two local path planning groups according to the position information of the point to be distributed in the group to be split.
9. A path planning apparatus, comprising:
the distribution point grouping module is used for grouping at least two points to be distributed to obtain a local path planning group;
a local path generation module, configured to obtain, according to each to-be-distributed point in each local path planning group, a local path corresponding to each local path planning group;
and the global path generating module is used for generating the global paths corresponding to the at least two to-be-matched points according to the local paths.
10. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement a path planning method as claimed in any one of claims 1-8.
11. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out a path planning method according to any one of claims 1-8.
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