CN116069005A - Robot edge path planning method and device, robot and storage medium - Google Patents
Robot edge path planning method and device, robot and storage medium Download PDFInfo
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Abstract
The invention discloses a robot edge path planning method, a device, a robot and a storage medium, wherein the method comprises the following steps: according to the detected closed loop of the running track, boundary points of a cleaning area and outline points of obstacles in the cleaning area are obtained to serve as candidate point sets; selecting edge prepositions meeting the continuous edge conditions from the candidate point set; and re-planning the edge path according to the edge prepositions, and controlling the robot to run according to the re-planned edge path. When the robot forms a closed loop from the edge to the isolated obstacle, boundary points of the cleaning area and outline points of the obstacle in the cleaning area are obtained to serve as candidate point sets, edge prepositions meeting continuous edge conditions are selected from the candidate point sets, accordingly, an edge path is planned again according to the edge prepositions, and the robot is controlled to run according to the new edge path, so that the robot can continue to edge, confusion of robot tracks is avoided, and the aim of improving cleaning efficiency of the robot is achieved.
Description
Technical Field
The invention relates to the technical field of robot path planning, in particular to a robot edge path planning method, a robot edge path planning device, a robot and a storage medium.
Background
In the process of carrying out edge cleaning on the set cleaning area boundary, the robot is easily disturbed by dynamic obstacles in the environment (such as people or animals moving in families, and the like), so that a closed loop is formed from the edge to the isolated obstacle, the robot track is disordered, and the cleaning efficiency is low.
Disclosure of Invention
The invention aims to provide a robot edge path planning method, a device, a robot and a storage medium, which aim at the defects of the prior art, and the aim is achieved through the following technical scheme.
The first aspect of the invention provides a robot edge path planning method, which comprises the following steps:
according to the detected closed loop of the running track, boundary points of a cleaning area and outline points of obstacles in the cleaning area are obtained to serve as candidate point sets;
selecting edge prepositions meeting the continuous edge conditions from the candidate point set;
and re-planning the edge path according to the edge prepositions, and controlling the robot to run according to the re-planned edge path.
In some embodiments of the present application, the acquiring boundary points of the cleaning area and contour points of the obstacle in the cleaning area as candidate point sets includes:
acquiring boundary points of a cleaning area and contour point clusters of each obstacle in the cleaning area according to a laser map and an environment map; filtering out contour point clusters with the number of the contour points being smaller than the preset number; and taking the contour points included in the rest contour point clusters and the acquired boundary points of the cleaning area as candidate point sets.
In some embodiments of the present application, the selecting an edge pre-point from the candidate point set that satisfies a continue edge condition includes:
acquiring partial track points currently generated by the robot; determining, for each candidate point in the candidate point set, a distance between the candidate point and each track point; selecting candidate points with the distance within a preset range from the candidate point set; selecting a minimum distance from the distances between the candidate points and each track point aiming at each selected candidate point, and grading the candidate points according to the minimum distance and the track point corresponding to the minimum distance; and selecting one candidate point from the selected candidate points according to the scores as an edge leading point meeting the continuous edge condition.
In some embodiments of the present application, selecting, according to the score, one candidate point from the selected candidate points as an edge pre-point that satisfies a continuous edge condition includes:
and selecting the candidate point with the lowest score from the scores as an edge leading point meeting the continuous edge condition.
In some embodiments of the present application, the scoring the candidate points according to the minimum distance and the trajectory point corresponding to the minimum distance includes:
determining a distance score for the candidate point using the minimum distance; determining an area containing the candidate point and the track point corresponding to the minimum distance in an environment map; determining an idle index of the candidate point according to the obstacle in the area; determining an exploration index of the candidate points according to the track points contained in the area; and determining the scores of the candidate points according to the distance scores, the idle indexes and the exploration indexes.
In some embodiments of the present application, the determining the idle index of the candidate point according to the obstacle in the area includes:
determining the area proportion of the barrier in the area to the area; and determining the idle index according to the area proportion.
In some embodiments of the present application, the determining the exploration index of the candidate point according to the trajectory point contained in the region includes:
determining the area proportion of track points contained in the area to the area; and determining the exploration index according to the area proportion.
In some embodiments of the present application, the determining the score of the candidate point according to the distance score, the idle index, and the exploration index includes:
and carrying out weighted summation on the distance score, the idle index and the exploration index to obtain the score of the candidate point.
A second aspect of the present invention proposes a robot edge path planning apparatus, the apparatus comprising:
the candidate point acquisition module is used for acquiring boundary points of a cleaning area and contour points of obstacles in the cleaning area as candidate point sets according to the fact that a closed loop exists in the detected driving track;
the screening module is used for selecting the edge prepositions meeting the continuous edge condition from the candidate point set;
and the path planning module is used for re-planning the edge path according to the edge pre-positioned point and controlling the robot to run according to the re-planned edge path.
A third aspect of the invention proposes a robot comprising a memory, a processor and a computer program stored on the memory and executable on the processor, said processor implementing the steps of the method according to the first aspect described above when said program is executed.
A fourth aspect of the invention proposes a computer readable storage medium having stored thereon a computer program which when executed by a processor implements the steps of the method according to the first aspect described above.
Based on the robot edge path planning method and the robot edge path planning device according to the first aspect and the second aspect, the invention has at least the following beneficial effects or advantages:
when the robot forms a closed loop from the edge to the isolated obstacle, boundary points of the cleaning area and outline points of the obstacle in the cleaning area are obtained to serve as candidate point sets, edge prepositions meeting continuous edge conditions are selected from the candidate point sets, accordingly, an edge path is planned again according to the edge prepositions, and the robot is controlled to run according to the new edge path, so that the robot can continue to edge, confusion of robot tracks is avoided, and the aim of improving cleaning efficiency of the robot is achieved.
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 specification, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on the invention. In the drawings:
FIG. 1 is a flow chart of an embodiment of a method for planning a robot edge path according to an exemplary embodiment of the present invention;
FIG. 2 is a schematic diagram of a process for selecting a leading edge point satisfying a follow-on edge condition according to the embodiment shown in FIG. 1;
FIG. 3 is a schematic diagram of a scoring process for candidate points according to an exemplary embodiment of the present invention;
FIG. 4 is a schematic diagram of a robot edge path planning apparatus according to an exemplary embodiment of the present invention;
fig. 5 is a schematic view showing a hardware configuration of a robot according to an exemplary embodiment of the present invention;
fig. 6 is a schematic diagram illustrating a structure of a storage medium according to an exemplary embodiment of the present invention.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the invention. Rather, they are merely examples of apparatus and methods consistent with aspects of the invention as detailed in the accompanying claims.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any or all possible combinations of one or more of the associated listed items.
It should be understood that although the terms first, second, third, etc. may be used herein to describe various information, these information should not be limited by these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the invention. The word "if" as used herein may be interpreted as "at … …" or "at … …" or "responsive to a determination", depending on the context.
In order to solve the problems that a closed loop is formed from the edge of a robot to an isolated obstacle at present, so that the robot track is disordered and the cleaning efficiency is low, the application provides a robot edge path planning method, namely when the situation that the robot edge is closed to the isolated obstacle is detected, boundary points of a cleaning area and outline points of the obstacle in the cleaning area are obtained to serve as candidate point sets, edge prepositions meeting continuous edge conditions are selected from the candidate point sets, the edge path is planned again according to the edge prepositions, and the robot is controlled to travel according to the new edge path, so that the robot can continue to edge, the robot track is prevented from being disordered, and the aim of improving the cleaning efficiency of the robot is achieved.
In order to enable those skilled in the art to better understand the present application, the following description will make clear and complete descriptions of the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application.
Embodiment one:
fig. 1 is a flowchart of an embodiment of a robot edge path planning method according to an exemplary embodiment of the present invention, in which a laser map and an environment map are generated by a robot in a cleaning mode, and areas represented on the laser map and the environment map are consistent, an area that can be scanned by a laser sensor and an area that cannot be scanned by the laser sensor are marked on the laser map, and a size of an obstacle detected by the laser is also marked in the scanned area; the running track and the obstacle position of the robot are marked on the environment map.
As shown in fig. 1, the robot edge path planning method includes the following steps:
step 101: and acquiring boundary points of the cleaning area and contour points of the obstacles in the cleaning area as candidate point sets according to the fact that the closed loop exists in the driving track.
In an alternative embodiment, the robot may detect whether a closed-loop track exists on the running track in real time during the edge running process, and when the closed-loop track is detected, the robot may deviate from the original edge path, and the robot is required to be re-navigated to the edge running process after the robot has been edge-extended to an isolated obstacle.
In step 101, the cleaning area refers to the entire cleaning area set by the user, the boundary points of which belong to points to be bordered, and the contour points of the obstacle in the cleaning area also belong to points to be bordered, for example, wall obstacles located in the cleaning area. Therefore, an optimal leading point along the edge can be selected from the points to continue to travel along the edge, so that the direct entering into a covering mode is avoided, and the cleaning efficiency is reduced.
In an alternative embodiment, the process of obtaining the candidate point set includes the steps of:
1. acquiring boundary points of a cleaning area and outline point clusters of each obstacle in the cleaning area according to the laser map and the environment map;
2. filtering out contour point clusters with the number of the contour points being smaller than the preset number;
3. and taking the contour points included in the rest contour point clusters and the acquired boundary points of the cleaning area as candidate point sets.
Wherein, because the information of the size of the obstacle is marked in the laser map, the outline point cluster surrounding the obstacle can be acquired. And by filtering the number of the contour points contained in the contour point cluster, smaller obstacles or dynamic obstacles causing closed loop formation can be filtered out, so that the rest contour points are ensured to belong to larger obstacles needing to be bordered, such as walls, cabinets and the like.
Notably, the contour point cluster of the obstacle refers to a point cloud consisting of consecutive boundary points around the obstacle.
Step 102: an edge prepended point is selected from the candidate point set that satisfies a continued edge condition.
Wherein, the leading points of the edge selected from the candidate point set can enable the robot to continue to drive along the edge instead of driving around the isolated obstacle.
For a specific implementation of selecting an edge prepended point from the candidate point set that satisfies the continue edge condition, reference may be made to the related description of the embodiments described below, which is not described in detail herein.
Step 103: and re-planning the edge path according to the edge prepositions, and controlling the robot to run according to the re-planned edge path.
It can be appreciated by those skilled in the art that the re-planning of the edge path according to the edge pre-point can be implemented by adopting a related technology, which is not particularly limited in the application, and the robot can continue to edge after traveling according to the re-planned edge path, so that the complete track information in the edge process can be ensured to be referred to, and the track confusion is avoided.
Thus, the process of planning the edgewise path shown in fig. 1 is completed, when the robot forms a closed loop from edgewise to isolated obstacles, boundary points of a cleaning area and outline points of the obstacles in the cleaning area are obtained to serve as candidate point sets, and edgewise prepositions meeting continuous edgewise conditions are selected from the candidate point sets, so that the edgewise path is planned again according to the edgewise prepositions, and the robot is controlled to run along the new edgewise path, so that the robot can continue to edge, the confusion of the robot track is avoided, and the aim of improving the cleaning efficiency of the robot is achieved.
Embodiment two:
fig. 2 is a schematic diagram of a process for selecting an edge pre-point satisfying a continuous edge condition according to the embodiment shown in fig. 1, where the process for selecting an edge pre-point from a candidate point set based on the embodiment shown in fig. 1 includes the following steps:
step 201: and acquiring partial track points currently generated by the robot.
The running track generated by the robot is composed of a series of track points, and in order to screen out the optimal edge prepositive points from the candidate point set, the track points generated recently by the robot, namely the track points forming a closed loop, need to be referred to.
Alternatively, 10% of all the trajectory points of the robot may be acquired, and the 10% trajectory point is the most recently generated point.
Step 202: for each candidate point in the set of candidate points, a distance between the candidate point and each track point is determined.
In an alternative embodiment, the distance between the candidate point and the track point may be represented by calculating the euclidean distance between the two points, and since the positions of the points in the laser map and the environment map are represented in grid coordinates, the calculated distance between the candidate point and the track point is also represented in grid distance.
For example, assuming that there are 10 candidate points in the candidate point set and 30 trajectory points, 30 euclidean distances are determined for each candidate point, and finally 10×30=300 euclidean distances are obtained, where each euclidean distance corresponds to a set of candidate points and combinations of trajectory points.
Step 203: from the candidate point set, candidate points whose distances lie within a preset range are selected.
In this case, the distance between the candidate point and the trajectory point is too long or too short to be effective for the robot to continue the edge, so that the candidate point with a distance within a certain range needs to be selected as a feasible edge point.
Step 204: and selecting a minimum distance from the distances between the candidate points and each track point aiming at each selected candidate point, and grading the candidate points according to the minimum distance and the track point corresponding to the minimum distance.
The distance between the candidate points and the track points is the minimum distance, and when scoring the candidate points, the minimum distance and the position of the track point closest to the candidate points are combined for scoring, so that the scoring accuracy can be ensured.
In an alternative embodiment, the candidate points may be scored from three aspects, a first aspect that considers the distance between the candidate point and the nearest track point, a second aspect that considers the degree of openness of the region between the candidate point and the nearest track point, and a third aspect that considers the robot explored score of the region between the candidate point and the nearest track point.
Based on this, as shown in fig. 3, the process of scoring candidate points for trajectory points according to the minimum distance and the correspondence of the minimum distance may include the steps of:
step 2041: the distance score of the candidate point is determined using the minimum distance.
The calculation formula of the distance score is as follows:
A1＝1-abs(sin(π×D/best_D))
where D represents the minimum distance, best_d represents the optimum distance, and is a fixed value, for example, 20 may be taken, A1 represents the distance score, and it is known based on the distance score formula that the lower the distance score, the better the candidate point is taken as the borderline leading point.
Step 2042: and determining an area containing the candidate point and the track point corresponding to the minimum distance in the environment map.
The area containing the candidate point and the nearest track point, which is determined in the environment map, can be a preset shape area taking the candidate point and the nearest track point as boundaries, and the area is used for subsequent evaluation of the idle index and the exploration index.
Alternatively, for ease of calculation, a rectangular box region bordered by the candidate point and the nearest track point may be determined.
Step 2043: and determining the idle index of the candidate point according to the obstacles in the area.
In an alternative embodiment, it is possible that the obstacle is included in the area determined in the environment map, and the robot tends to select a more open area when selecting the edge front point, so as to avoid the robot entering a complex area and being unable to escape.
Based on this, it is possible to determine the area ratio of the obstacle in the area to the area and determine the free index from the area ratio.
Alternatively, since the obstacle is represented by a series of point clouds in the laser map, the area surrounded by these point clouds may be used to occupy the area proportion of the entire determined area.
The larger the area proportion of the obstacle is, the lower the idle degree is, so that the idle index is calculated according to the following formula:
A2＝1-S
wherein S represents the area ratio of the obstacle, A2 represents the idle index, and based on the formula, the lower the idle index is, the better the candidate point is taken as the edge prepositive point.
Step 2044: and determining the exploration index of the candidate points according to the track points contained in the region.
In an alternative embodiment, it is possible to include a portion of the robot's trajectory in an area defined in the environment map, indicating that the robot has been explored in that area.
Based on this, the exploration index may be determined by determining the area proportion of the track points contained in the region to the region, and determining the exploration index according to the area proportion.
If the robot has explored in the area, the exploration index is relatively high, so that the area proportion occupied by the track points can be directly used as the exploration index, and the lower the exploration index is, the better the candidate points are used as the edge prepositions.
Step 2045: and determining the scores of the candidate points according to the distance scores, the idle indexes and the exploration indexes.
Alternatively, the distance score, the idle index, and the search index may be weighted and summed to obtain the score of the candidate point based on the descriptions of steps 2041 to 2044.
The weight of each parameter can be set according to actual requirements.
Step 205: and selecting one candidate point from the selected candidate points according to the scores as an edge leading point meeting the continuous edge condition.
Alternatively, based on the description of step 204, the candidate point with the lowest score may be selected from the scores of the candidate points as the edge pre-point satisfying the continuous edge condition.
Further, if more than one candidate point with the lowest score exists, the candidate point closest to the latest track point of the robot can be selected as the final edge leading point.
Thus, the above-mentioned edgewise prepositive point selection flow shown in fig. 2 is completed, by performing twice screening on the candidate point set, namely, deleting a part of candidate points to serve as feasible edgewise points according to the distance between the candidate points and the track points for the first time, and further screening optional edgewise points according to the distance between the feasible edgewise points and the nearest track points and the score determined by the nearest track points for the second time, so as to obtain the edgewise prepositive points meeting the continuous edgewise condition, avoid the confusion of the track of the robot, and further achieve the goal of improving the cleaning efficiency of the robot.
The invention also provides an embodiment of the robot edge path planning device corresponding to the embodiment of the robot edge path planning method.
Fig. 4 is a schematic structural diagram of a robot edge path planning apparatus according to an exemplary embodiment of the present invention, where the apparatus is configured to perform the robot edge path planning method according to any one of the foregoing embodiments, and as shown in fig. 4, the robot edge path planning apparatus includes:
a candidate point obtaining module 410, configured to obtain, as a candidate point set, a boundary point of a cleaning area and a contour point of an obstacle in the cleaning area according to the detection that a closed loop exists in a driving track;
a screening module 420, configured to select an edge pre-point that meets a continuous edge condition from the candidate point set;
and the path planning module 430 is configured to re-plan the edge path according to the edge pre-point, and control the robot to travel along the re-planned edge path.
In an optional implementation manner, the candidate point obtaining module 410 is specifically configured to obtain, according to a laser map and an environmental map, a boundary point of a cleaning area and a contour point cluster of each obstacle in the cleaning area; filtering out contour point clusters with the number of the contour points being smaller than the preset number; and taking the contour points included in the rest contour point clusters and the acquired boundary points of the cleaning area as candidate point sets.
In an optional implementation manner, the screening module 420 is specifically configured to obtain a part of track points currently generated by the robot; determining, for each candidate point in the candidate point set, a distance between the candidate point and each track point; selecting candidate points with the distance within a preset range from the candidate point set; selecting a minimum distance from the distances between the candidate points and each track point aiming at each selected candidate point, and grading the candidate points according to the minimum distance and the track point corresponding to the minimum distance; and selecting one candidate point from the selected candidate points according to the scores as an edge leading point meeting the continuous edge condition.
In an alternative implementation manner, the filtering module 420 is specifically configured to select, from the scores, a candidate point with the lowest score as the edge pre-point that satisfies the continuous edge condition in a process of selecting, according to the scores, one candidate point from the selected candidate points as the edge pre-point that satisfies the continuous edge condition.
In an optional implementation manner, the screening module 420 is specifically configured to determine, by using the minimum distance, a distance score of the candidate point in a process of scoring the candidate point according to the minimum distance and the trajectory point corresponding to the minimum distance; determining an area containing the candidate point and the track point corresponding to the minimum distance in an environment map; determining an idle index of the candidate point according to the obstacle in the area; determining an exploration index of the candidate points according to the track points contained in the area; and determining the scores of the candidate points according to the distance scores, the idle indexes and the exploration indexes.
In an alternative implementation manner, the screening module 420 is specifically configured to determine an area ratio of the obstacle in the area to the area in the process of determining the idle index of the candidate point according to the obstacle in the area; and determining the idle index according to the area proportion.
In an optional implementation manner, the screening module 420 is specifically configured to determine an area ratio of the track points included in the area to the area in determining the exploration index of the candidate points according to the track points included in the area; and determining the exploration index according to the area proportion.
In an alternative implementation manner, the filtering module 420 is specifically configured to, in determining the scoring process of the candidate point according to the distance score, the idle index, and the exploration index, perform weighted summation on the distance score, the idle index, and the exploration index, so as to obtain the score of the candidate point.
The implementation process of the functions and roles of each unit in the above device is specifically shown in the implementation process of the corresponding steps in the above method, and will not be described herein again.
For the device embodiments, reference is made to the description of the method embodiments for the relevant points, since they essentially correspond to the method embodiments. The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purposes of the present invention. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
The embodiment of the invention also provides a robot corresponding to the robot edge path planning method provided by the previous embodiment, so as to execute the robot edge path planning method.
Fig. 5 is a hardware configuration diagram of a robot according to an exemplary embodiment of the present invention, the robot including: a communication interface 601, a processor 602, a memory 603 and a bus 604; wherein the communication interface 601, the processor 602 and the memory 603 perform communication with each other via a bus 604. The processor 602 may perform the robot edge path planning method described above by reading and executing machine executable instructions in the memory 603 corresponding to the control logic of the robot edge path planning method, the details of which are referred to in the above embodiments and will not be described here.
The memory 603 referred to herein may be any electronic, magnetic, optical, or other physical storage device that may contain stored information, such as executable instructions, data, or the like. In particular, the memory 603 may be RAM (Random Access Memory ), flash memory, a storage drive (e.g., hard drive), any type of storage disk (e.g., optical disk, DVD, etc.), or a similar storage medium, or a combination thereof. The communication connection between the system network element and at least one other network element is achieved through at least one communication interface 601 (which may be wired or wireless), the internet, a wide area network, a local network, a metropolitan area network, etc. may be used.
The processor 602 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuitry in hardware or instructions in software in the processor 602. The processor 602 may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), etc.; but may also be a Digital Signal Processor (DSP), application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the embodiments of the present application may be embodied directly in hardware, in a decoded processor, or in a combination of hardware and software modules in a decoded processor.
The robot provided by the embodiment of the application and the robot edge path planning method provided by the embodiment of the application are the same in the invention conception, and have the same beneficial effects as the method adopted, operated or realized by the robot.
The present embodiment also provides a computer readable storage medium corresponding to the robot edge path planning method provided in the foregoing embodiment, and referring to fig. 6, the computer readable storage medium is shown as an optical disc 30, on which a computer program (i.e. a program product) is stored, where the computer program, when executed by a processor, performs the robot edge path planning method provided in any of the foregoing embodiments.
It should be noted that examples of the computer readable storage medium may also include, but are not limited to, a phase change memory (PRAM), a Static Random Access Memory (SRAM), a Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a flash memory, or other optical or magnetic storage medium, which will not be described in detail herein.
The computer readable storage medium provided by the above embodiment of the present application and the robot edge path planning method provided by the embodiment of the present application are the same inventive concept, and have the same advantages as the method adopted, operated or implemented by the application program stored therein.
Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather to enable any modification, equivalent replacement, improvement or the like to be made within the spirit and principles of the invention.
Claims (11)
1. A method for planning a robot edge path, the method comprising:
according to the detected closed loop of the running track, boundary points of a cleaning area and outline points of obstacles in the cleaning area are obtained to serve as candidate point sets;
selecting edge prepositions meeting the continuous edge conditions from the candidate point set;
and re-planning the edge path according to the edge prepositions, and controlling the robot to run according to the re-planned edge path.
2. The method of claim 1, wherein the acquiring boundary points of the cleaning area and contour points of the obstacle in the cleaning area as candidate point sets comprises:
acquiring boundary points of a cleaning area and contour point clusters of each obstacle in the cleaning area according to a laser map and an environment map;
filtering out contour point clusters with the number of the contour points being smaller than the preset number;
and taking the contour points included in the rest contour point clusters and the acquired boundary points of the cleaning area as candidate point sets.
3. The method of claim 1, wherein selecting an edge pre-point from the set of candidate points that satisfies a continue edge condition comprises:
acquiring partial track points currently generated by the robot;
determining, for each candidate point in the candidate point set, a distance between the candidate point and each track point;
selecting candidate points with the distance within a preset range from the candidate point set;
selecting a minimum distance from the distances between the candidate points and each track point aiming at each selected candidate point, and grading the candidate points according to the minimum distance and the track point corresponding to the minimum distance;
and selecting one candidate point from the selected candidate points according to the scores as an edge leading point meeting the continuous edge condition.
4. A method according to claim 3, wherein selecting a candidate point from the selected candidate points as an edge pre-point satisfying a follow-on edge condition according to the score comprises:
and selecting the candidate point with the lowest score from the scores as an edge leading point meeting the continuous edge condition.
5. A method according to claim 3, wherein said scoring said candidate points according to said minimum distance and said locus points corresponding to said minimum distance comprises:
determining a distance score for the candidate point using the minimum distance;
determining an area containing the candidate point and the track point corresponding to the minimum distance in an environment map;
determining an idle index of the candidate point according to the obstacle in the area;
determining an exploration index of the candidate points according to the track points contained in the area;
and determining the scores of the candidate points according to the distance scores, the idle indexes and the exploration indexes.
6. The method of claim 5, wherein the determining the free index of the candidate points from obstructions within the area comprises:
determining the area proportion of the barrier in the area to the area;
and determining the idle index according to the area proportion.
7. The method of claim 5, wherein the determining the exploration index of the candidate points from the trajectory points contained within the region comprises:
determining the area proportion of track points contained in the area to the area;
and determining the exploration index according to the area proportion.
8. The method of claim 5, wherein the determining the score for the candidate point based on the distance score, the idleness index, and the exploration index comprises:
and carrying out weighted summation on the distance score, the idle index and the exploration index to obtain the score of the candidate point.
9. A robot edge path planning apparatus, the apparatus comprising:
the candidate point acquisition module is used for acquiring boundary points of a cleaning area and contour points of obstacles in the cleaning area as candidate point sets according to the fact that a closed loop exists in the detected driving track;
the screening module is used for selecting the edge prepositions meeting the continuous edge condition from the candidate point set;
and the path planning module is used for re-planning the edge path according to the edge pre-positioned point and controlling the robot to run according to the re-planned edge path.
10. A robot comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1-8 when the program is executed.
11. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the steps of the method according to any of claims 1-8.
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| CN202111277346.2A CN116069005A (en) | 2021-10-29 | 2021-10-29 | Robot edge path planning method and device, robot and storage medium |
| PCT/CN2021/136015 WO2023070840A1 (en) | 2021-10-29 | 2021-12-07 | Robot edgewise path planning method and apparatus, and robot and storage medium |
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| CN202111277346.2A CN116069005A (en) | 2021-10-29 | 2021-10-29 | Robot edge path planning method and device, robot and storage medium |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117553804A (en) * | 2024-01-11 | 2024-02-13 | 深圳市普渡科技有限公司 | Path planning method, path planning device, computer equipment and storage medium |
| CN117629185A (en) * | 2023-12-01 | 2024-03-01 | 安徽工业大学 | Photovoltaic cleaning robot running path planning method under complex working condition |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116907512B (en) * | 2023-09-14 | 2023-12-22 | 山东博昂信息科技有限公司 | Combined dotting cleaning method for outdoor unmanned cleaning machine |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107102294A (en) * | 2017-06-19 | 2017-08-29 | 安徽味唯网络科技有限公司 | A kind of method in sweeping robot intelligent planning path |
| CN109464074B (en) * | 2018-11-29 | 2021-05-28 | 深圳市银星智能科技股份有限公司 | Area division method, subarea cleaning method and robot thereof |
| CN111857127B (en) * | 2020-06-12 | 2021-10-01 | 珠海市一微半导体有限公司 | Clean partition planning method for robot walking along edge, chip and robot |
| CN112631281A (en) * | 2020-12-10 | 2021-04-09 | 尚科宁家(中国)科技有限公司 | Cleaning robot and path planning method thereof |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117629185A (en) * | 2023-12-01 | 2024-03-01 | 安徽工业大学 | Photovoltaic cleaning robot running path planning method under complex working condition |
| CN117553804A (en) * | 2024-01-11 | 2024-02-13 | 深圳市普渡科技有限公司 | Path planning method, path planning device, computer equipment and storage medium |
| CN117553804B (en) * | 2024-01-11 | 2024-04-09 | 深圳市普渡科技有限公司 | Path planning method, path planning device, computer equipment and storage medium |
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