WO2022213519A1 - 路径规划方法、装置、清洁机器人及存储介质 - Google Patents

路径规划方法、装置、清洁机器人及存储介质 Download PDF

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Publication number
WO2022213519A1
WO2022213519A1 PCT/CN2021/109797 CN2021109797W WO2022213519A1 WO 2022213519 A1 WO2022213519 A1 WO 2022213519A1 CN 2021109797 W CN2021109797 W CN 2021109797W WO 2022213519 A1 WO2022213519 A1 WO 2022213519A1
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Prior art keywords
sub
area
areas
region
cleaning robot
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PCT/CN2021/109797
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English (en)
French (fr)
Inventor
任纪颖
邵林
王聪
喻强
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美智纵横科技有限责任公司
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Publication of WO2022213519A1 publication Critical patent/WO2022213519A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20—Instruments for performing navigational calculations
    • G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation
    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
    • A47L11/24—Floor-sweeping machines, motor-driven
    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
    • A47L11/40—Parts or details of machines not provided for in groups A47L11/02 - A47L11/38, or not restricted to one of these groups, e.g. handles, arrangements of switches, skirts, buffers, levers
    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
    • A47L11/40—Parts or details of machines not provided for in groups A47L11/02 - A47L11/38, or not restricted to one of these groups, e.g. handles, arrangements of switches, skirts, buffers, levers
    • A47L11/4061—Steering means; Means for avoiding obstacles; Details related to the place where the driver is accommodated
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20—Instruments for performing navigational calculations
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • G01C21/34—Route searching; Route guidance
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L2201/00—Robotic cleaning machines, i.e. with automatic control of the travelling movement or the cleaning operation
    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L2201/00—Robotic cleaning machines, i.e. with automatic control of the travelling movement or the cleaning operation
    • A47L2201/04—Automatic control of the travelling movement; Automatic obstacle detection

Definitions

  • the present application relates to the technical field of cleaning robots, and in particular to a path planning method, device, cleaning robot and storage medium.
  • the cleaning robot in the process of full coverage cleaning, can divide the area to be cleaned into a plurality of sub-areas according to obstacles, and perform path planning based on the divided sub-areas.
  • a division method will result in multiple fragmented sub-areas, requiring a longer path to perform area coverage, and the cleaning efficiency of the cleaning robot is not high.
  • embodiments of the present application provide a path planning method, device, cleaning robot, and storage medium.
  • the embodiment of the present application provides a path planning method, which is applied to a cleaning robot, including:
  • first sub-region group exists in the at least two first sub-regions
  • the first sub-regions in the first sub-region group are merged;
  • the first sub-region group consists of two adjacent sub-regions
  • a first sub-area is formed, and the cleaning robot can move from one first sub-area to another first sub-area in the first sub-area group;
  • the cleaning route planning is performed on the to-be-cleaned area.
  • the method further includes:
  • the method includes:
  • the first area is composed of continuous grids without obstacles in the grid map, and meets the requirements of the The cleaning robot can move between corresponding two first sub-areas via the first area; the grid map is pre-created by the cleaning robot;
  • two corresponding first sub-areas are determined as the first sub-area group.
  • the shortest distance between the generated boundary of the second sub-region and the corresponding boundary of the first sub-region is greater than the set distance.
  • the performing cleaning route planning on the to-be-cleaned area includes:
  • a cleaning route is planned.
  • the second area is generated with the current position of the cleaning robot as the center, including:
  • the second area at least partially or fully coincident with the first quantity of the first sub-areas is generated with the current position of the cleaning robot as the center .
  • the route planning algorithm is an A-star search algorithm, and the corresponding first number is 3.
  • the determining of at least two first sub-areas of the area to be cleaned includes:
  • the area to be cleaned is divided based on the obstacle position information, and the at least two first sub-areas are determined.
  • the embodiment of the present application also provides a path planning device, including:
  • a dividing unit configured to determine at least two first sub-areas of the area to be cleaned
  • a merging unit configured to merge the first sub-regions in the first sub-region group when the first sub-region group exists in the at least two first sub-regions;
  • the first sub-region group consists of Two adjacent first sub-areas are formed, and the cleaning robot can move from one first sub-area to another first sub-area in the first sub-area group;
  • the planning unit is configured to perform cleaning route planning on the to-be-cleaned area after the first sub-areas in the first sub-area group are merged.
  • Embodiments of the present application also provide a cleaning robot, comprising: a processor and a memory configured to store a computer program that can be executed on the processor,
  • the processor is configured to execute the steps of the above path planning method when running the computer program.
  • the embodiment of the present application further provides a storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of any of the above path planning methods are implemented.
  • the area to be cleaned is divided into at least two first sub-areas, and in the case that the cleaning robot can move between the two adjacent first sub-areas, the two adjacent sub-areas are merged , and perform cleaning route planning based on the merged sub-regions.
  • the path required for regional coverage and cleaning can be shortened, and the cleaning efficiency of the cleaning robot can be improved.
  • FIG. 1 is a schematic flowchart of a path planning method provided by an embodiment of the present application.
  • FIG. 2 is a schematic diagram of division of a first sub-area in a room according to an embodiment of the present application
  • FIG. 3 is a schematic diagram of expanding a first sub-region to generate a second sub-region according to an embodiment of the present application
  • FIG. 4 is a schematic diagram of no obstacles in eight neighborhoods of a grid provided by an embodiment of the present application.
  • FIG. 5 is a schematic diagram of obstacles in eight neighborhoods of a grid provided by an embodiment of the present application.
  • FIG. 6 is a schematic diagram of a sub-region merging provided by an embodiment of the present application.
  • FIG. 7 is a schematic flowchart of a sub-region merging provided by an embodiment of the present application.
  • FIG. 8 is a schematic diagram of expanding a first sub-region to generate a second sub-region according to another embodiment of the present application.
  • FIG. 9 is a schematic diagram of a second area generation process provided by an embodiment of the present application.
  • FIG. 10 is a schematic flowchart of a path planning method provided by another embodiment of the present application.
  • FIG. 11 is a schematic structural diagram of a path planning apparatus provided by an embodiment of the application.
  • FIG. 12 is a schematic structural diagram of a cleaning robot according to an embodiment of the present application.
  • Cleaning robots also known as sweeping robots, automatic cleaning machines, intelligent vacuum cleaners, robot vacuum cleaners, etc.
  • the cleaning robot can divide the area to be cleaned into a plurality of sub-areas according to obstacles, and perform path planning based on the divided sub-areas.
  • path planning based on the divided sub-areas.
  • such a division method will result in multiple fragmented sub-areas, requiring a longer path to perform area coverage, and the cleaning efficiency of the cleaning robot is not high.
  • the area to be cleaned is divided into at least two first sub-areas, and in the case that the cleaning robot can move between the two adjacent first sub-areas, the Two adjacent sub-regions are merged, and cleaning route planning is performed based on the merged sub-regions.
  • the path required for regional coverage and cleaning can be shortened, and the cleaning efficiency of the cleaning robot can be improved.
  • FIG. 1 is a schematic diagram of an implementation flowchart of a path planning method provided by an embodiment of the present application. As shown in Figure 1, the path planning method includes:
  • Step 101 Determine at least two first sub-areas of the area to be cleaned.
  • the area to be cleaned is divided into at least two first sub-areas.
  • the area to be cleaned may be the remaining uncleaned area in the working area of the cleaning robot after the cleaning robot has performed at least one cleaning according to the planned cleaning route, or may be the complete working area that needs to be cleaned when the cleaning robot has not started cleaning.
  • Step 102 In the case where a first sub-region group exists in the at least two first sub-regions, merge the first sub-regions in the first sub-region group; the first sub-region group is composed of adjacent is composed of two first sub-areas, and the cleaning robot can move from one first sub-area to another first sub-area in the first sub-area group.
  • the two The first sub-area is determined as a first sub-area group, and two first sub-areas in the first sub-area group are combined.
  • the fact that the cleaning robot can move from one first sub-area to another first sub-area means that the boundary of the two sub-areas leaves a channel that allows the cleaning robot to move between the two sub-areas without hindrance.
  • Figure 2 shows a schematic diagram of the division of the first sub-area in the room.
  • the cleaning robot moves between the first sub-area 1 and the first sub-area 2 without passing through other sub-areas.
  • the first sub-area 1 and the first sub-area 2 is adjacent to the first sub-area, and the cleaning robot must pass through the first sub-area 2 to move between the first sub-area 1 and the first sub-area 3, so the first sub-area 1 and the first sub-area 3 are Non-adjacent first sub-regions.
  • Step 103 After merging the first sub-areas in the first sub-area group, perform cleaning route planning for the to-be-cleaned area.
  • the cleaning route planning is performed according to some or all of the first sub-areas included in the area to be cleaned, where the first sub-area includes the first sub-area that has been merged and the The first subregion that does not meet the merge condition.
  • the path planning method here can be used cyclically during the cleaning process. After executing the cleaning route planning once and performing the cleaning according to the planned route, the area to be cleaned is divided into at least two first sub-areas, and the first sub-areas that meet the conditions are divided into After a sub-area is merged, the cleaning route planning is performed for the area to be cleaned.
  • the area to be cleaned is divided into at least two first sub-areas, and when the cleaning robot can move between the two adjacent first sub-areas, the two adjacent sub-areas are merged, Perform cleaning route planning based on the merged sub-regions.
  • the path required for regional coverage and cleaning can be shortened, and the cleaning efficiency of the cleaning robot can be improved.
  • the method further includes:
  • the method includes:
  • the first area is composed of continuous grids without obstacles in the grid map, and meets the requirements of the The cleaning robot can move between corresponding two first sub-areas via the first area; the grid map is pre-created by the cleaning robot;
  • two corresponding first sub-areas are determined as the first sub-area group.
  • a grid map is pre-created by the cleaning robot to represent the area to be cleaned and the divided sub-areas.
  • the first sub-region 1 and the first sub-region 2 are divided by obstacles, and the first sub-region 1 is expanded to obtain the second sub-region 1 with bdeg as the vertex.
  • 2 Carry out external expansion to obtain the second sub-region 2 with acfh as the vertex.
  • the overlapped area is represented by a grid map.
  • the eight neighborhoods algorithm is used to judge whether there are obstacles in the eight neighborhoods of the upper, lower, left, right, upper left, upper right, lower left, and lower right of the grid in the overlapping area bcfg, as shown in Figure 4.
  • FIG. 5 shows a schematic diagram of a grid with no obstacles in the eight-neighborhood grid of the grid. Search for the existence of the first area through the eight-neighborhood algorithm. Specifically, the area formed by continuous grids satisfying the eight-neighborhood grid without obstacles is determined as a grid area.
  • the determined grid area can make The cleaning robot passes through, so that the cleaning robot can move between the corresponding two first sub-areas, then it is judged that the determined grid area is the first area, and the search result representing the existence of the first area is obtained, and the corresponding two The first sub-region is determined as the first sub-region group; otherwise, a search result indicating that the first region does not exist is obtained. After the two first sub-regions are searched, the next two adjacent first sub-regions are searched until all combinations of the two adjacent first sub-regions have been searched.
  • each grid in the grid map can be set to be represented as 5 cm by 5 cm size.
  • the first sub-area can be enlarged by setting a zoom ratio to obtain an enlarged second sub-area.
  • the set area can be set as the minimum channel area that allows the cleaning robot to pass.
  • the width of the minimum channel area can be the maximum width of the fuselage perpendicular to the direction of the cleaning path when the cleaning robot performs cleaning work plus the set width; when the grid area includes at least the set area, the determined grid area can make cleaning work Robots pass.
  • the connectivity of the fragmented sub-regions can be merged, and the route planning can be performed based on the merged sub-regions, which shortens the path required for regional coverage and cleaning, and improves the cleaning efficiency of the cleaning robot.
  • At least two first sub-areas of the area to be cleaned are determined.
  • each first sub-area Traverse each first sub-area, and based on the neighborhood principle, expand the first sub-area by half the diameter of the cleaning robot (or the maximum width of the fuselage), so that an overlapping area is generated between the sub-areas, so as to determine the phase of the first sub-area. another first sub-region adjacent to it.
  • the area formed by the continuous grids satisfying the eight neighborhoods without obstacles in the overlapping area can enable the cleaning robot to move between the corresponding two sub-areas, the two corresponding first sub-areas are merged.
  • the shortest distance between the generated boundary of the second sub-region and the corresponding boundary of the first sub-region is greater than the set distance.
  • a corresponding second sub-region is generated based on the expansion of each of the two first sub-regions, and the minimum distance between the boundary of the first sub-region and the boundary of the corresponding second sub-region is greater than the set distance.
  • two non-adjacent merged sub-areas can be merged through the eight-neighbor algorithm, so that when planning the cleaning route, multiple fragmented sub-areas divided by the cleaned route can be merged.
  • Route planning in the area can shorten the path required for area coverage and cleaning.
  • the set distance may be equal to or greater than half of the diameter of the cleaning robot (or the maximum width of the body). In this way, even if the two first sub-regions are divided by one cleaning path, since the two adjacent first sub-regions are respectively expanded by a distance greater than or equal to half of the maximum width of the fuselage, the generated two second sub-regions will In the overlapping region of the regions, when there is a first region based on the eight-neighborhood algorithm search, two adjacent first sub-regions may also be merged.
  • the performing cleaning route planning on the area to be cleaned includes:
  • a cleaning route is planned.
  • the second area is determined with the current position of the cleaning robot as the center, and the first sub-area partially or completely overlapping with the second area is determined as the third sub-area for planning the cleaning route.
  • the way of determining the third sub-region may be to determine the first sub-region that completely overlaps with the second region as the third sub-region, or to determine the first sub-region that partially or completely overlaps with the second region. is the third subregion.
  • the first sub-area around the current position of the cleaning robot will be It is set as a high-priority sub-area, thereby shortening the path required for performing area coverage cleaning and improving the cleaning efficiency of the cleaning robot.
  • the generating the second area with the current position of the cleaning robot as the center includes:
  • the second area at least partially or fully coincident with the first quantity of the first sub-areas is generated with the current position of the cleaning robot as the center .
  • an upper limit on the number of third sub-regions for planning a cleaning route may also be set. In this way, when cleaning a large area to be cleaned, by determining the cleaning sequence priority of the sub-areas and inputting an appropriate number of sub-areas for path planning, the time required for path planning can be shortened and the cleaning efficiency of the cleaning robot can be improved. .
  • the path planning algorithm requires at least three sub-region numbers for path planning. As shown in Fig. 9, taking the cleaning robot as the center, the second area 1 is determined with a radius of 6 meters, and the first sub-area 1 and the first sub-area 3 overlap with the second area 1 partially or completely. A first sub-region is not enough to implement a route planning algorithm. Adjust the radius to 12 meters, take the cleaning robot as the center, and determine the second area 2 with a radius of 12 meters. The first sub-area 1, the first sub-area 2 and the first sub-area overlap with the second area 1 in part or in whole. 3. Three first sub-regions can be determined, sufficient to implement the route planning algorithm.
  • the route planning algorithm is an A-star search algorithm, and the corresponding first number is 3.
  • the A-star search algorithm is used as the path planning algorithm.
  • the first number of the first sub-regions required by the A-star search algorithm is 3.
  • By generating the second region at least three first sub-regions are determined as the third sub-regions, and the determined The outgoing third sub-region is passed into the A-star search algorithm for cleaning path planning.
  • the determining at least two first sub-areas of the area to be cleaned includes:
  • the area to be cleaned is divided based on the obstacle position information, and the at least two first sub-areas are determined.
  • the area to be cleaned is divided into at least two first sub-areas.
  • the obstacles can be static obstacles such as tables, chairs, sofas, or dynamic obstacles such as indoor animals.
  • the existence of obstacles determines whether the cleaning robot can pass normally, which will affect the cleaning route planning of the cleaning robot.
  • the first sub-area is divided according to the location information of the obstacles, which can realize the rationalization of the sub-areas. Divide and use the divided sub-areas for cleaning route planning, which can improve the rationality of the area covering the cleaning route and prevent the cleaning robot from getting stuck in obstacles and unable to work normally.
  • the sub-areas can be divided according to the existence of dynamic obstacles, and the sub-areas determined based on the dynamic obstacles can realize better cleaning route planning.
  • the corresponding path planning method includes the following steps:
  • Step 1001 Build a grid map.
  • the cleaning robot builds a grid map based on the edge information of the area boundary, the laser SLAM information and the location information of the covering collision obstacles.
  • Step 1002 Divide the area to be cleaned into at least two first sub-areas. Dividing the to-be-cleaned area into at least two first sub-areas The to-be-cleaned area is divided into at least two first sub-areas according to obstacle location information and the like.
  • Step 1003 Merge the sub-regions based on the eight-neighbor algorithm. At the boundary of the sub-area, it is searched whether there is a first area according to the eight-neighborhood algorithm. If the requirement that the cleaning robot can move between the two first sub-areas is met, the two areas are connected and the two sub-areas are merged. After the two sub-regions are merged, the boundary inflection point and the boundary are discretely selected as the starting point of the region.
  • Step 1004 Determine the sub-region with the highest priority, and pass it into the multi-point A-star search algorithm to query the optimal path. Generate the second area with the current position of the cleaning robot as the center, set the priority of the sub-area that partially or fully overlaps with the second area to the highest priority, and pass all the sub-areas with the highest priority into the multi-point A star search algorithm Find the best path.
  • Step 1005 After the sub-area with the highest priority is cleaned, the robot will continue to divide the existing area to be cleaned into sub-areas. After the sub-area with the highest priority is cleaned, the robot will continue to divide the existing area to be cleaned into sub-areas, and repeat the above steps until there is no area to be cleaned.
  • the embodiment of the present application further provides a path planning device, as shown in FIG. 11 , the device includes:
  • a dividing unit 1101 configured to determine at least two first sub-areas of the area to be cleaned
  • the merging unit 1102 is configured to merge the first sub-regions in the first sub-region group when there is a first sub-region group in the at least two first sub-regions; the first sub-region group It consists of two adjacent first sub-areas, and the cleaning robot can move from one first sub-area to another first sub-area in the first sub-area group;
  • the planning unit 1103 is configured to perform cleaning route planning on the to-be-cleaned area after the first sub-areas in the first sub-area group are merged.
  • the device further includes:
  • a judging unit configured to judge whether to form the first sub-region group for any two adjacent first sub-regions in the at least two first sub-regions;
  • the judging unit When judging whether to form the first sub-area group, the judging unit is configured as:
  • the overlapping area of the generated two second sub-areas search for the existence of a first area based on the eight-neighborhood algorithm;
  • the first area is composed of continuous grids without obstacles in the grid map, and the clean
  • the robot can move between the corresponding two first sub-areas via the first area;
  • the grid map is pre-created by the cleaning robot;
  • two corresponding first sub-areas are determined as the first sub-area group.
  • the shortest distance between the generated boundary of the second sub-region and the corresponding boundary of the first sub-region is greater than the set distance.
  • the planning unit 1103 is configured to:
  • a cleaning route is planned.
  • the planning unit 1103 is configured to:
  • the second area at least partially or fully coincident with the first quantity of the first sub-areas is generated with the current position of the cleaning robot as the center .
  • the route planning algorithm is an A-star search algorithm, and the corresponding first number is 3.
  • the dividing unit 1101 is configured as:
  • the area to be cleaned is divided based on the obstacle position information, and the at least two first sub-areas are determined.
  • the dividing unit 1101, the merging unit 1102, the planning unit 1103, and the judging unit may be based on a processor in the path planning device, such as a central processing unit (CPU, Central Processing Unit), a digital signal processor (DSP, Digital Signal Processor), Microcontroller Unit (MCU, Microcontroller Unit) or Programmable Gate Array (FPGA, Field-Programmable Gate Array).
  • a processor in the path planning device such as a central processing unit (CPU, Central Processing Unit), a digital signal processor (DSP, Digital Signal Processor), Microcontroller Unit (MCU, Microcontroller Unit) or Programmable Gate Array (FPGA, Field-Programmable Gate Array).
  • CPU Central Processing Unit
  • DSP Digital Signal Processor
  • MCU Microcontroller Unit
  • FPGA Field-Programmable Gate Array
  • path planning device when the path planning device provided in the above-mentioned embodiment performs path planning, only the division of the above-mentioned program modules is used as an example for illustration. That is, the internal structure of the device is divided into different program modules to complete all or part of the processing described above.
  • the path planning apparatus and the path planning method embodiments provided by the above embodiments belong to the same concept, and the specific implementation process thereof is detailed in the method embodiments, which will not be repeated here.
  • the embodiment of the present application further provides a cleaning robot.
  • the cleaning robot 1200 includes:
  • a communication interface 1210 capable of information interaction with other devices such as network devices;
  • the processor 1220 is connected to the communication interface 1210 to realize information interaction with other devices, and is configured to execute the method provided by one or more of the above technical solutions when running a computer program. And the computer program is stored on the memory 1230 .
  • bus system 1240 is configured to enable connection communication between these components.
  • bus system 1240 also includes a power bus, a control bus, and a status signal bus.
  • the various buses are labeled as bus system 1240 in FIG. 12 .
  • the memory 1230 in the embodiment of the present application is configured to store various types of data to support the operation of the cleaning robot 1200 .
  • Examples of such data include: any computer program configured to operate on cleaning robot 1200 .
  • the memory 1230 may be volatile memory or non-volatile memory, and may also include both volatile and non-volatile memory.
  • the non-volatile memory can be a read-only memory (ROM, Read Only Memory), a programmable read-only memory (PROM, Programmable Read-Only Memory), an erasable programmable read-only memory (EPROM, Erasable Programmable Read-only memory) Only Memory), Electrically Erasable Programmable Read-Only Memory (EEPROM, Electrically Erasable Programmable Read-Only Memory), Magnetic Random Access Memory (FRAM, ferromagnetic random access memory), Flash Memory (Flash Memory), Magnetic Surface Memory , CD-ROM, or CD-ROM (Compact Disc Read-Only Memory); magnetic surface memory can be disk memory or tape memory.
  • RAM Random Access Memory
  • SRAM Static Random Access Memory
  • SSRAM Synchronous Static Random Access Memory
  • DRAM Dynamic Random Access Memory
  • SDRAM Synchronous Dynamic Random Access Memory
  • DDRSDRAM Double Data Rate Synchronous Dynamic Random Access Memory
  • ESDRAM Enhanced Type Synchronous Dynamic Random Access Memory
  • SLDRAM Synchronous Link Dynamic Random Access Memory
  • DRRAM Direct Rambus Random Access Memory
  • the memory 1230 described in the embodiments of the present application is intended to include, but not limited to, these and any other suitable types of memory.
  • the methods disclosed in the above embodiments of the present application may be applied to the processor 1220 or implemented by the processor 1220 .
  • the processor 1220 may be an integrated circuit chip with signal processing capability. In the implementation process, each step of the above-mentioned method may be completed by an integrated logic circuit of hardware in the processor 1220 or an instruction in the form of software.
  • the aforementioned processor 1220 may be a general-purpose processor, a DSP, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and the like.
  • the processor 1220 may implement or execute the methods, steps, and logical block diagrams disclosed in the embodiments of this application.
  • a general purpose processor may be a microprocessor or any conventional processor or the like.
  • the steps of the method disclosed in the embodiments of the present application can be directly embodied as being executed by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor.
  • the software module may be located in a storage medium, and the storage medium is located in the memory 1230, the processor 1220 reads the program in the memory 1230, and completes the steps of the foregoing method in combination with its hardware.
  • the processor 1220 executes the program, the corresponding processes implemented by the cleaning robot in each method of the embodiments of the present application are implemented, which is not repeated here for brevity.
  • an embodiment of the present application further provides a storage medium, that is, a computer storage medium, specifically a computer-readable storage medium, for example, including a memory 1230 for storing a computer program, and the above-mentioned computer program can be stored by a processor of an electronic device. 1220 is executed to complete the steps of the aforementioned method.
  • the computer-readable storage medium may be memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface memory, optical disk, or CD-ROM.
  • the disclosed apparatus, electronic device and method may be implemented in other manners.
  • the device embodiments described above are only illustrative.
  • the division of the units is only a logical function division. In actual implementation, there may be other division methods.
  • multiple units or components may be combined, or Can be integrated into another system, or some features can be ignored, or not implemented.
  • the coupling, or direct coupling, or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be electrical, mechanical or other forms. of.
  • the unit described above as a separate component may or may not be physically separated, and the component displayed as a unit may or may not be a physical unit, that is, it may be located in one place or distributed to multiple network units; Some or all of the units may be selected according to actual needs to achieve the purpose of the solution in this embodiment.
  • each functional unit in each embodiment of the present application may all be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above integration
  • the unit can be implemented either in the form of hardware or in the form of hardware plus software functional units.
  • the aforementioned program can be stored in a computer-readable storage medium, and when the program is executed, execute It includes the steps of the above method embodiments; and the aforementioned storage medium includes: a removable storage device, a ROM, a RAM, a magnetic disk or an optical disk and other media that can store program codes.
  • the above-mentioned integrated units of the present application are implemented in the form of software function modules and sold or used as independent products, they may also be stored in a computer-readable storage medium.
  • the computer software products are stored in a storage medium and include several instructions for A computer device (which may be a personal computer, a server, or a network device, etc.) is caused to execute all or part of the methods described in the various embodiments of the present application.
  • the aforementioned storage medium includes: a removable storage device, a ROM, a RAM, a magnetic disk or an optical disk and other mediums that can store program codes.
  • connection should be understood in a broad sense, for example, it may be an electrical connection, or a communication between two elements, a direct connection, or an indirect connection through an intermediate medium.
  • connection should be understood in a broad sense, for example, it may be an electrical connection, or a communication between two elements, a direct connection, or an indirect connection through an intermediate medium.

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Abstract

一种路径规划方法、装置、清洁机器人（1200）及存储介质（1230）。其中，路径规划方法，包括：清洁机器人（1200）确定待清洁区域的至少两个第一子区域（101）；在至少两个第一子区域中存在第一子区域组的情况下，将第一子区域组中的第一子区域合并（102）；第一子区域组由相邻的两个第一子区域组成，且清洁机器人（1200）能够从第一子区域组中的一个第一子区域移动至另一个第一子区域；在对第一子区域组中的第一子区域完成合并后，对待清洁区域执行清洁路线规划（103）。

Description

[根据细则91更正 09.10.2021]　路径规划方法、装置、清洁机器人及存储介质
相关申请的交叉引用
本申请基于申请号为202110385047.4，申请日为2021年4月9日的中国专利申请提出，并要求上述中国专利申请的优先权，上述中国专利申请的全部内容在此引入本申请作为参考。
技术领域
本申请涉及清洁机器人技术领域，具体涉及一种路径规划方法、装置、清洁机器人及存储介质。
背景技术
相关技术中，清洁机器人在进行全覆盖清洁的过程中，能根据障碍物将待清洁区域划分为多个子区域，基于划分得到的子区域进行路径规划。但是，实际应用中，这样的划分方式会得到多个碎片化的子区域，需要更长的路径才能执行区域覆盖，清洁机器人的清洁效率不高。
发明内容
为解决相关技术问题，本申请实施例提供了一种路径规划方法、装置、清洁机器人及存储介质。
本申请实施例提供了一种路径规划方法，应用于清洁机器人，包括：
确定待清洁区域的至少两个第一子区域；
在所述至少两个第一子区域中存在第一子区域组的情况下，将所述第一子区域组中的第一子区域合并；所述第一子区域组由相邻的两个第一子区域组成，且所述清洁机器人能够从所述第一子区域组中的一个第一子区域移动至另一个第一子区域；
在对第一子区域组中的第一子区域完成合并后，对所述待清洁区域执行清洁路线规划。
其中，上述方案中，所述方法还包括：
对所述至少两个第一子区域中相邻的任意两个第一子区域，判断是否组成所述第一子区域组；其中，
在判断是否组成所述第一子区域组时，所述方法包括：
对两个第一子区域中每个第一子区域进行外扩，生成对应的第二子区域；
在生成的两个第二子区域的重合区域内，基于八邻域算法搜索是否存在第一区域；所述第一区域由栅格地图中不存在障碍物的连续栅格组成，且满足所述清洁机器人能够经由所述第一区域在对应的两个第一子区域之间移动；所述栅格地图由所述清洁机器人预先创建；
在搜索结果表征存在所述第一区域的情况下，将对应的两个第一子区域确定为所述第一子区域组。
上述方案中，生成的第二子区域的边界与对应的第一子区域的边界之间的最短距离大于设定距离。
上述方案中，所述对所述待清洁区域执行清洁路线规划，包括：
以所述清洁机器人的当前位置为中心，生成第二区域；
将与所述第二区域部分或全部重合的第一子区域确定为第三子区域；
根据确定出的至少一个第三子区域，规划清洁路线。
上述方案中，所述以所述清洁机器人的当前位置为中心，生成第二区域，包括：
基于路线规划算法所需的第一子区域的第一数量，以所述清洁机器人的当前位置为中心，生成至少与所述第一数量的第一子区域部分或全部重合的所述第二区域。
上述方案中，所述路线规划算法为A星搜索算法，对应的所述第一数量为3。
上述方案中，所述确定待清洁区域的至少两个第一子区域，包括：
基于障碍物位置信息划分待清洁区域，确定所述至少两个第一子区域。
本申请实施例还提供了一种路径规划装置，包括：
划分单元，配置为确定待清洁区域的至少两个第一子区域；
合并单元，配置为在所述至少两个第一子区域中存在第一子区域组的情况下，将所述第一子区域组中的第一子区域合并；所述第一子区域组由相邻的两个第一子区域组成，且所述清洁机器人能够从所述第一子区域组中的一个第一子区域移动至另一个第一子区域；
规划单元，配置为在对第一子区域组中的第一子区域完成合并后，对所述待清洁区域执行清洁路线规划。
本申请实施例还提供了一种清洁机器人，包括：处理器和配置为存储能够在处理器上运行的计算机程序的存储器，
其中，所述处理器配置为运行所述计算机程序时，执行上述路径规划方法的步骤。
本申请实施例还提供了一种存储介质，其上存储有计算机程序，所述 计算机程序被处理器执行时实现上述任一路径规划方法的步骤。
在本申请实施例中，将待清洁区域划分为至少两个第一子区域，在清洁机器人可以在相邻的两个第一子区域之间移动的情况下，将相邻的两个子区域合并，基于合并后的子区域执行清洁路线规划。这样，通过将多个碎片化的子区域进行合并，基于合并后的子区域进行路线规划，可以缩短区域覆盖清洁所需要路径，提升了清洁机器人的清洁效率。
附图说明
图1为本申请实施例提供的一种路径规划方法的流程示意图；
图2为本申请实施例提供的一种房间中第一子区域划分的示意图；
图3为本申请实施例提供的一种第一子区域外扩生成第二子区域的示意图；
图4为本申请实施例提供的一种栅格的八邻域没有障碍物的示意图；
图5为本申请实施例提供的一种栅格的八邻域有障碍物的示意图；
图6为本申请实施例提供的一种子区域合并的示意图；
图7为本申请实施例提供的一种子区域合并的流程示意图；
图8为本申请另一实施例提供的一种第一子区域外扩生成第二子区域的示意图；
图9为本申请实施例提供的一种第二区域生成过程的示意图；
图10为本申请另一实施例提供的一种路径规划方法的流程示意图；
图11为本申请实施例提供的一种路径规划装置的结构示意图；
图12为本申请实施例提供的一种清洁机器人的结构示意图。
具体实施方式
清洁机器人，又称扫地机器人、自动打扫机、智能吸尘、机器人吸尘器等，清洁机器人的工作环境中存在各种动态或静态的障碍物。相关技术中，清洁机器人在进行全覆盖清洁的过程中，能根据障碍物将待清洁区域划分为多个子区域，基于划分得到的子区域进行路径规划。但是，实际应用中，这样的划分方式会得到多个碎片化的子区域，需要更长的路径才能执行区域覆盖，清洁机器人的清洁效率不高。
基于此，在本申请的各种实施例中，将待清洁区域划分为至少两个第一子区域，在清洁机器人可以在相邻的两个第一子区域之间移动的情况下，将相邻的两个子区域合并，基于合并后的子区域执行清洁路线规划。这样，通过将多个碎片化的子区域进行合并，基于合并后的子区域进行路线规划，可以缩短区域覆盖清洁所需要路径，提升了清洁机器人的清洁效率。
为了使本申请的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细说明。应当理解，此处描述的具体实 施例仅仅用以解释本申请，并不用于限定本申请。
图1为本申请实施例提供的路径规划方法的实现流程示意图。如图1示出的，路径规划方法包括：
步骤101：确定待清洁区域的至少两个第一子区域。
将待清洁区域划分为至少两个第一子区域。
对待清洁区域进行子区域划分，得到至少两个第一子区域。这里，待清洁区域可以是在清洁机器人已经按照规划的清洁路线执行了至少一次清洁后，清洁机器人工作区域中剩余的未清洁区域，也可以是清洁机器人尚未开始清洁时需要清洁的完整工作区域。
步骤102：在所述至少两个第一子区域中存在第一子区域组的情况下，将所述第一子区域组中的第一子区域合并；所述第一子区域组由相邻的两个第一子区域组成，且所述清洁机器人能够从所述第一子区域组中的一个第一子区域移动至另一个第一子区域。
在由待清洁区域划分成的至少两个第一子区域中，当存在两个相邻的第一子区域使清洁机器人可以在两个第一子区域之间移动的情况下，将这两个第一子区域确定为第一子区域组，并将这个第一子区域组中的两个第一子区域合并。这里，清洁机器人能够从一个第一子区域移动至另一个第一子区域，是指两个子区域的边界留有允许清洁机器人无障碍地在两个子区域之间移动的通道。
如图2所示出房间中第一子区域划分的示意图，清洁机器人在第一子区域1和第一子区域2之间移动无需经过其它子区域，第一子区域1和第一子区域2为相邻的第一子区域，而清洁机器人在第一子区域1和第一子区域3之间之间移动必须经过第一子区域2，所以第一子区域1和第一子区域3为不相邻的第一子区域。
步骤103：在对第一子区域组中的第一子区域完成合并后，对所述待清洁区域执行清洁路线规划。
在第一子区域组中的第一子区域完成合并后，根据待清洁区域包括的部分或全部第一子区域执行清洁路线规划，这里的第一子区域包括已经执行合并的第一子区域和不满足合并条件的第一子区域。
这里的路径规划方法，可以在清洁过程中循环采用，在执行完一次清洁路线规划，并按照规划的路线执行清洁后，再划分待清洁区域为至少两个第一子区域，将满足条件的第一子区域合并后对待清洁区域执行清洁路线规划。
在本实施例中，将待清洁区域划分为至少两个第一子区域，在清洁机器人可以在相邻的两个第一子区域之间移动的情况下，将相邻的两个子区域合并，基于合并后的子区域执行清洁路线规划。这样，通过将多个碎片化的子区域进行合并，基于合并后的子区域进行路线规划，可以缩短区域覆盖清洁所需要路径，提升了清洁机器人的清洁效率。
其中，在一实施例中，所述方法还包括：
对所述至少两个第一子区域中相邻的任意两个第一子区域，判断是否组成所述第一子区域组；其中，
在判断是否组成所述第一子区域组时，所述方法包括：
对两个第一子区域中每个第一子区域进行外扩，生成对应的第二子区域；
在生成的两个第二子区域的重合区域内，基于八邻域算法搜索是否存在第一区域；所述第一区域由栅格地图中不存在障碍物的连续栅格组成，且满足所述清洁机器人能够经由所述第一区域在对应的两个第一子区域之间移动；所述栅格地图由所述清洁机器人预先创建；
在搜索结果表征存在所述第一区域的情况下，将对应的两个第一子区域确定为所述第一子区域组。
通过清洁机器人预先创建栅格地图表示待清洁区域和划分的子区域。如图3所示出，以障碍物划分的第一子区域1和第一子区域2，对第一子区域1进行外扩得到以bdeg为顶点的第二子区域1，对第一子区域2进行外扩得到以acfh为顶点的第二子区域2，生成的第二子区域1和第二子区域2之间存在以bcfg为顶点的重合区域，并用栅格地图表示的重合区域。通过八邻域算法判断重合区域bcfg内栅格的上、下、左、右、左上、右上、左下、右下这八个方向的八个邻域是否有障碍物存在，图4所示出的是八邻域栅格存在障碍物的栅格示意图，图5所示出的是栅格的八邻域栅格不存在障碍物的栅格示意图。通过八邻域算法搜索是否存在第一区域，具体地，通过将满足八邻域栅格没有障碍物存在的连续栅格构成的区域确定为一个栅格区域，若确定出的栅格区域能够令清洁机器人通过，从而使清洁机器人能够在对应的两个第一子区域之间移动，则判断确定出的栅格区域为第一区域，得到表征第一区域存在的搜索结果，将对应的两个第一子区域确定为第一子区域组；否则，得到表征第一区域不存在的搜索结果。在这两个第一子区域搜索完毕后，对下两个相邻的第一子区域进行搜索，直至所有的两个相邻的第一子区域组合均已搜索完毕。
实际应用时，如图6所示出的，在清洁机器人直径(或机身最大宽度)为30厘米的情况下，可以将栅格地图中的每个栅格设置为表征为5厘米乘以5厘米大小。将第一子区域外扩为第二子区域，可以通过设定缩放比例放大第一子区域，得到放大的第二子区域。判断确定的栅格区域能否令清洁机器人通过，可以通过判断栅格区域是否至少包括允许清洁机器人通过的设定区域，实际应用中，可以将设定区域设置为允许清洁机器人通过的最小通道区域，最小通道区域的宽度可以是清洁机器人在执行清扫工作时垂直于清扫路径方向的机身最大宽度加上设定宽度；当栅格区域至少包括设定区域，则确定的栅格区域能够令清洁机器人通过。
这样，在清洁路线规划时，可以将基于碎片化的子区域的连通性进行 合并，基于合并后的子区域进行路线规划，缩短区域覆盖清洁所需要路径，提升了清洁机器人的清洁效率。
实际应用时，如图7所示出的子区域合并的流程示意图，判断相邻的任意两个第一子区域是否组成第一子区域组，将第一子区域组中的第一子区域合并时，包括：
确定待清洁区域的至少两个第一子区域。
遍历每个第一子区域，基于邻域原则，将第一子区域外扩半个清洁机器人直径(或机身最大宽度)，使子区域之间产生重合区域，从而确定第一子区域的相邻的另一个第一子区域。
若重合区域中满足八邻域无障碍物的连续栅格构成的区域能够使清洁机器人在对应的两个子区域之间移动，则将两个对应的第一子区域合并。
重复以上第一子区域合并条件的判断，直至所有满足条件的相邻的第一子区域都已被合并。
在一实施例中，生成的第二子区域的边界与对应的第一子区域的边界之间的最短距离大于设定距离。
基于两个第一子区域中每个第一子区域外扩生成对应的第二子区域，第一子区域的边界和对应的第二子区域的边界之间的最小距离大于设定距离。这样，可以通过八邻域算法将两个并不邻接的合并子区域合并，从而在清洁路线规划时，可以将被已清扫路径划分的多个碎片化的子区域进行合并，基于合并后的子区域进行路线规划，可以缩短区域覆盖清洁所需要路径。
这里，如图8所示出，设定距离可以大于等于清洁机器人直径(或机身最大宽度)的一半。这样，即使是被一次清扫路径划分开的两个第一子区域，由于两个相邻的第一子区域分别外扩了大于等于一半机身最大宽度的距离，在生成的两个第二子区域的重合区域内，基于八邻域算法搜索存在第一区域的情况下，也可以将两个相邻的第一子区域合并。
在一实施例中，所述对所述待清洁区域执行清洁路线规划，包括：
以所述清洁机器人的当前位置为中心，生成第二区域；
将与所述第二区域部分或全部重合的第一子区域确定为第三子区域；
根据确定出的至少一个第三子区域，规划清洁路线。
以清洁机器人当前位置为中心确定第二区域，将与第二区域部分或全部重合的第一子区域确定为用于规划清洁路线第三子区域。这里，确定第三子区域的方式，可以是将与第二区域全部重合的第一子区域确定为第三子区域，也可以是将与第二区域部分或全部重合的第一子区域都确定为第三子区域。
通过确定与清洁机器人当前位置最接近的第一子区域，并基于这些确定出的第一子区域进行路线规划，这样，在进行下一次路径规划时，将清洁机器人当前位置周边的第一子区域设置为高优先级的子区域，从而缩短 执行区域覆盖清洁所需要路径，提升了清洁机器人的清洁效率。
在一实施例中，所述以所述清洁机器人的当前位置为中心，生成第二区域，包括：
基于路线规划算法所需的第一子区域的第一数量，以所述清洁机器人的当前位置为中心，生成至少与所述第一数量的第一子区域部分或全部重合的所述第二区域。
以清洁机器人的当前位置为中心生成第二区域，判断与生成的第二区域部分或全部重合的第一子区域数量，当判断结果表征第一子区域数量少于路线规划算法所需的子区域的数量的下限，也就是说确定出的第一子区域不足以实现路线规划算法，调整第二区域的大小，直到与生成的第二区域部分或全部重合的第一子区域数量足以实现路线规划算法。这样，可以根据需要确定足够数量的第一子区域用于进行路线规划。
这里，还可以设置用于规划清洁路线的第三子区域的数量的上限。这样，在清洁较大面积的待清洁区域时，通过对子区域的清洁顺序优先级进行确定，输入适当数量的子区域进行路径规划，可以缩短路径规划所需的时间，提高清洁机器人的清洁效率。
在一应用实施例中，路径规划算法需要至少三个子区域数量用于路径规划。如图9所示出，以清洁机器人为中心，以6米为半径确定第二区域1，与第二区域1部分或全部重合的是第一子区域1和第一子区域3，可以确定两个第一子区域，不足以实现路线规划算法。调整半径至12米，以清洁机器人为中心，以12米为半径确定第二区域2，与第二区域1部分或全部重合的是第一子区域1、第一子区域2和第一子区域3，可以确定三个第一子区域，足以实现路线规划算法。
在一实施例中，所述路线规划算法为A星搜索算法，对应的所述第一数量为3。
采用A星搜索算法为路径规划算法，A星搜索算法所需的第一子区域的第一数量为3，通过生成第二区域确定至少三个第一子区域为第三子区域，并将确定出的第三子区域传入A星搜索算法进行清洁路径规划。
这样，在清洁较大面积的待清洁区域时，通过确定适当数量的子区域进行路径规划，可以缩短路径规划所需的时间，提高清洁机器人的清洁效率。
在一实施例中，所述确定待清洁区域的至少两个第一子区域，包括：
基于障碍物位置信息划分待清洁区域，确定所述至少两个第一子区域。
通过获取同步定位与地图构建(SLAM，Simultaneous Localization And Mapping)信息和区域边界沿边信息，结合得到的覆盖碰撞障碍物信息，将待清洁区域划分为至少两个第一子区域。这里，障碍物可以是静态障碍物如桌椅、沙发，也可以是动态障碍物如室内的动物。
清洁机器人在执行清洁过程中，障碍物的存在决定清洁机器人是否可 以正常通过，因而会影响到清洁机器人的清洁路线规划，根据障碍物的位置信息划分得到第一子区域，可以实现子区域的合理化划分，将划分的子区域用于清洁路线规划，可以提升区域覆盖清洁路径的合理性，避免清洁机器人卡在障碍物中无法正常工作。并且，通过在清洁过程中循环确定待清洁区域的第一子区域，可以根据动态障碍物的存在进行子区域的划分，基于动态障碍物的确定的子区域可以实现更优的清洁路线规划。
下面结合应用实施例对本申请再作进一步的详细描述。
结合图10，对应的路径规划方法，包括以下步骤：
步骤1001：建立格栅地图。清洁机器人根据区域边界沿边信息、激光SLAM信息和覆盖碰撞障碍物位置信息，建立格栅地图。
步骤1002：将待清洁区域划分为至少两个第一子区域。将待清洁区域划分为至少两个第一子区域将待清洁区域根据障碍物位置信息等划分为至少两个第一子区域。
步骤1003：基于八邻域算法合并子区域。在子区域边界根据八邻域算法搜索是否存在第一区域，若满足清洁机器人能够在两个第一子区域之间移动的要求，则两区域连通，将两个子区域进行合并。在两个子区域合并之后，离散选择边界拐点和边界处作为区域起始点。
步骤1004：确定优先级最高的子区域，并传入多点A星搜索算法中查询到最优路径。以清洁机器人的当前位置为中心生成第二区域，将与第二区域有部分或全部重合的子区域优先级设置为最高，并将优先级最高的全部子区域传入多点A星搜索算法中查询到最优路径。
步骤1005：当优先级最高的子区域清扫结束之后，机器人将对现有的待清洁区域继续划分子区域。当优先级最高的子区域清扫结束之后，机器人将对现有的待清洁区域继续划分子区域，并循环以上步骤，直到不存在待清洁区域。
为实现本申请实施例的方法，本申请实施例还提供了一种路径规划装置，如图11所示，该装置包括：
划分单元1101，配置为确定待清洁区域的至少两个第一子区域；
合并单元1102，配置为在所述至少两个第一子区域中存在第一子区域组的情况下，将所述第一子区域组中的第一子区域合并；所述第一子区域组由相邻的两个第一子区域组成，且所述清洁机器人能够从所述第一子区域组中的一个第一子区域移动至另一个第一子区域；
规划单元1103，配置为在对第一子区域组中的第一子区域完成合并后，对所述待清洁区域执行清洁路线规划。
其中，在一个实施例中，所述装置还包括：
判断单元，配置为对所述至少两个第一子区域中相邻的任意两个第一子区域，判断是否组成所述第一子区域组；其中，
在判断是否组成所述第一子区域组时，所述判断单元，配置为：
对两个第一子区域中每个第一子区域进行外扩，生成对应的第二子区域；
在生成的两个第二子区域的重合区域内，基于八邻域算法搜索是否存在第一区域；所述第一区域由栅格地图中不存在障碍物的连续栅格组成，且所述清洁机器人能够经由所述第一区域在对应的两个第一子区域之间移动；所述栅格地图由所述清洁机器人预先创建；
在搜索结果表征存在所述第一区域的情况下，将对应的两个第一子区域确定为所述第一子区域组。
在一个实施例中，生成的第二子区域的边界与对应的第一子区域的边界之间的最短距离大于设定距离。
在一个实施例中，所述规划单元1103，配置为：
以所述清洁机器人的当前位置为中心，生成第二区域；
将与所述第二区域部分或全部重合的第一子区域确定为第三子区域；
根据确定出的至少一个第三子区域，规划清洁路线。
在一个实施例中，所述规划单元1103，配置为：
基于路线规划算法所需的第一子区域的第一数量，以所述清洁机器人的当前位置为中心，生成至少与所述第一数量的第一子区域部分或全部重合的所述第二区域。
在一个实施例中，所述路线规划算法为A星搜索算法，对应的所述第一数量为3。
在一个实施例中，所述划分单元1101，配置为：
基于障碍物位置信息划分待清洁区域，确定所述至少两个第一子区域。
实际应用时，所述划分单元1101、合并单元1102、规划单元1103、判断单元可由基于路径规划装置中的处理器，比如中央处理器(CPU，Central Processing Unit)、数字信号处理器(DSP，Digital Signal Processor)、微控制单元(MCU，Microcontroller Unit)或可编程门阵列(FPGA，Field－Programmable Gate Array)等实现。
需要说明的是：上述实施例提供的路径规划装置在进行路径规划时，仅以上述各程序模块的划分进行举例说明，实际应用中，可以根据需要而将上述处理分配由不同的程序模块完成，即将装置的内部结构划分成不同的程序模块，以完成以上描述的全部或者部分处理。另外，上述实施例提供的路径规划装置与路径规划方法实施例属于同一构思，其具体实现过程详见方法实施例，这里不再赘述。
基于上述程序模块的硬件实现，且为了实现本申请实施例路径规划方法，本申请实施例还提供了一种清洁机器人，如图12所示，该清洁机器人1200包括：
通信接口1210，能够与其它设备比如网络设备等进行信息交互；
处理器1220，与所述通信接口1210连接，以实现与其它设备进行信息 交互，配置为运行计算机程序时，执行上述一个或多个技术方案提供的方法。而所述计算机程序存储在存储器1230上。
当然，实际应用时，清洁机器人1200中的各个组件通过总线系统1240耦合在一起。可理解，总线系统1240配置为实现这些组件之间的连接通信。总线系统1240除包括数据总线之外，还包括电源总线、控制总线和状态信号总线。但是为了清楚说明起见，在图12中将各种总线都标为总线系统1240。
本申请实施例中的存储器1230配置为存储各种类型的数据以支持清洁机器人1200的操作。这些数据的示例包括：配置为在清洁机器人1200上操作的任何计算机程序。
可以理解，存储器1230可以是易失性存储器或非易失性存储器，也可包括易失性和非易失性存储器两者。其中，非易失性存储器可以是只读存储器(ROM，Read Only Memory)、可编程只读存储器(PROM，Programmable Read-Only Memory)、可擦除可编程只读存储器(EPROM，Erasable Programmable Read-Only Memory)、电可擦除可编程只读存储器(EEPROM，Electrically Erasable Programmable Read-Only Memory)、磁性随机存取存储器(FRAM，ferromagnetic random access memory)、快闪存储器(Flash Memory)、磁表面存储器、光盘、或只读光盘(CD-ROM，Compact Disc Read-Only Memory)；磁表面存储器可以是磁盘存储器或磁带存储器。易失性存储器可以是随机存取存储器(RAM，Random Access Memory)，其用作外部高速缓存。通过示例性但不是限制性说明，许多形式的RAM可用，例如静态随机存取存储器(SRAM，Static Random Access Memory)、同步静态随机存取存储器(SSRAM，Synchronous Static Random Access Memory)、动态随机存取存储器(DRAM，Dynamic Random Access Memory)、同步动态随机存取存储器(SDRAM，Synchronous Dynamic Random Access Memory)、双倍数据速率同步动态随机存取存储器(DDRSDRAM，Double Data Rate Synchronous Dynamic Random Access Memory)、增强型同步动态随机存取存储器(ESDRAM，Enhanced Synchronous Dynamic Random Access Memory)、同步连接动态随机存取存储器(SLDRAM，SyncLink Dynamic Random Access Memory)、直接内存总线随机存取存储器(DRRAM，Direct Rambus Random Access Memory)。本申请实施例描述的存储器1230旨在包括但不限于这些和任意其它适合类型的存储器。
上述本申请实施例揭示的方法可以应用于处理器1220中，或者由处理器1220实现。处理器1220可能是一种集成电路芯片，具有信号的处理能力。在实现过程中，上述方法的各步骤可以通过处理器1220中的硬件的集成逻辑电路或者软件形式的指令完成。上述的处理器1220可以是通用处理器、DSP，或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件等。处理器1220可以实现或者执行本申请实施例中的公开的各方法、 步骤及逻辑框图。通用处理器可以是微处理器或者任何常规的处理器等。结合本申请实施例所公开的方法的步骤，可以直接体现为硬件译码处理器执行完成，或者用译码处理器中的硬件及软件模块组合执行完成。软件模块可以位于存储介质中，该存储介质位于存储器1230，处理器1220读取存储器1230中的程序，结合其硬件完成前述方法的步骤。
可选地，所述处理器1220执行所述程序时实现本申请实施例的各个方法中由清洁机器人实现的相应流程，为了简洁，在此不再赘述。
在示例性实施例中，本申请实施例还提供了一种存储介质，即计算机存储介质，具体为计算机可读存储介质，例如包括存储计算机程序的存储器1230，上述计算机程序可由电子设备的处理器1220执行，以完成前述方法所述步骤。计算机可读存储介质可以是FRAM、ROM、PROM、EPROM、EEPROM、Flash Memory、磁表面存储器、光盘、或CD-ROM等存储器。
在本申请所提供的几个实施例中，应该理解到，所揭露的装置、电子设备和方法，可以通过其它的方式实现。以上所描述的设备实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，如：多个单元或组件可以结合，或可以集成到另一个系统，或一些特征可以忽略，或不执行。另外，所显示或讨论的各组成部分相互之间的耦合、或直接耦合、或通信连接可以是通过一些接口，设备或单元的间接耦合或通信连接，可以是电性的、机械的或其它形式的。
上述作为分离部件说明的单元可以是、或也可以不是物理上分开的，作为单元显示的部件可以是、或也可以不是物理单元，即可以位于一个地方，也可以分布到多个网络单元上；可以根据实际的需要选择其中的部分或全部单元来实现本实施例方案的目的。
另外，在本申请各实施例中的各功能单元可以全部集成在一个处理单元中，也可以是各单元分别单独作为一个单元，也可以两个或两个以上单元集成在一个单元中；上述集成的单元既可以采用硬件的形式实现，也可以采用硬件加软件功能单元的形式实现。
本领域普通技术人员可以理解：实现上述方法实施例的全部或部分步骤可以通过程序指令相关的硬件来完成，前述的程序可以存储于一计算机可读取存储介质中，该程序在执行时，执行包括上述方法实施例的步骤；而前述的存储介质包括：移动存储设备、ROM、RAM、磁碟或者光盘等各种可以存储程序代码的介质。
或者，本申请上述集成的单元如果以软件功能模块的形式实现并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请实施例的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机、服务器、或者网络设备等)执行本申请各个实施例所述方法的全部或 部分。而前述的存储介质包括：移动存储设备、ROM、RAM、磁碟或者光盘等各种可以存储程序代码的介质。
需要说明的是，本申请实施例所记载的技术方案之间，在不冲突的情况下，可以任意组合。除非另有说明和限定，术语“连接”应做广义理解，例如，可以是电连接，也可以是两个元件内部的连通，可以是直接相连，也可以通过中间媒介间接相连，对于本领域的普通技术人员而言，可以根据具体情况理解上述术语的具体含义。
另外，在本申请实例中，“第一”、“第二”等是用于区别类似的对象，而不必用于描述特定的顺序或先后次序。应该理解“第一\第二\第三”区分的对象在适当情况下可以互换，以使这里描述的本申请的实施例可以除了在这里图示或描述的那些以外的顺序实施。
以上所述，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应以所述权利要求的保护范围为准。
在具体实施方式中所描述的各个实施例中的各个具体技术特征，在不矛盾的情况下，可以进行各种组合，例如通过不同的具体技术特征的组合可以形成不同的实施方式，为了避免不必要的重复，本申请中各个具体技术特征的各种可能的组合方式不再另行说明。

Claims (10)

  1. 一种路径规划方法，应用于清洁机器人，所述方法包括：
    确定待清洁区域的至少两个第一子区域；
    在所述至少两个第一子区域中存在第一子区域组的情况下，将所述第一子区域组中的第一子区域合并；所述第一子区域组由相邻的两个第一子区域组成，且所述清洁机器人能够从所述第一子区域组中的一个第一子区域移动至另一个第一子区域；
    在对第一子区域组中的第一子区域完成合并后，对所述待清洁区域执行清洁路线规划。
  2. 根据权利要求1所述的路径规划方法，其中，所述方法还包括：
    对所述至少两个第一子区域中相邻的任意两个第一子区域，判断是否组成所述第一子区域组；其中，
    在判断是否组成所述第一子区域组时，所述方法包括：
    对两个第一子区域中每个第一子区域进行外扩，生成对应的第二子区域；
    在生成的两个第二子区域的重合区域内，基于八邻域算法搜索是否存在第一区域；所述第一区域由栅格地图中不存在障碍物的连续栅格组成，且所述清洁机器人能够经由所述第一区域在对应的两个第一子区域之间移动；所述栅格地图由所述清洁机器人预先创建；
    在搜索结果表征存在所述第一区域的情况下，将对应的两个第一子区域确定为所述第一子区域组。
  3. 根据权利要求2所述的路径规划方法，其中，生成的第二子区域的边界与对应的第一子区域的边界之间的最短距离大于设定距离。
  4. 根据权利要求1所述的路径规划方法，其中，所述对所述待清洁区域执行清洁路线规划，包括：
    以所述清洁机器人的当前位置为中心，生成第二区域；
    将与所述第二区域部分或全部重合的第一子区域确定为第三子区域；
    根据确定出的至少一个第三子区域，规划清洁路线。
  5. 根据权利要求4所述的路径规划方法，其中，所述以所述清洁机器人的当前位置为中心，生成第二区域，包括：
    基于路线规划算法所需的第一子区域的第一数量，以所述清洁机器人的当前位置为中心，生成至少与所述第一数量的第一子区域部分或全部重合的所述第二区域。
  6. 根据权利要求4或5所述的路径规划方法，其中，所述路线规划算法为A星搜索算法，对应的所述第一数量为3。
  7. 根据权利要求1至5任一项所述的路径规划方法，其中，所述确定待清洁区域的至少两个第一子区域，包括：
    基于障碍物位置信息划分待清洁区域，确定所述至少两个第一子区域。
  8. 一种路径规划装置，包括：
    划分单元，配置为确定待清洁区域的至少两个第一子区域；
    合并单元，配置为在所述至少两个第一子区域中存在第一子区域组的情况下，将所述第一子区域组中的第一子区域合并；所述第一子区域组由相邻的两个第一子区域组成，且所述清洁机器人能够从所述第一子区域组中的一个第一子区域移动至另一个第一子区域；
    规划单元，配置为在对第一子区域组中的第一子区域完成合并后，对所述待清洁区域执行清洁路线规划。
  9. 一种清洁机器人，包括：处理器和配置为存储能够在处理器上运行的计算机程序的存储器，
    其中，所述处理器配置为运行所述计算机程序时，执行权利要求1至7任一项所述的路径规划方法的步骤。
  10. 一种存储介质，其上存储有计算机程序，所述计算机程序被处理器执行时实现权利要求1至7任一项所述的路径规划方法的步骤。
PCT/CN2021/109797 2021-04-09 2021-07-30 路径规划方法、装置、清洁机器人及存储介质 WO2022213519A1 (zh)

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