WO2020140682A1 - 与机器人服务有关的方法及相关***、可读存储介质 - Google Patents

与机器人服务有关的方法及相关***、可读存储介质 Download PDF

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Publication number
WO2020140682A1
WO2020140682A1 PCT/CN2019/123290 CN2019123290W WO2020140682A1 WO 2020140682 A1 WO2020140682 A1 WO 2020140682A1 CN 2019123290 W CN2019123290 W CN 2019123290W WO 2020140682 A1 WO2020140682 A1 WO 2020140682A1
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Prior art keywords
grid
service
serviceable
served
area
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PCT/CN2019/123290
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English (en)
French (fr)
Inventor
徐博
唐小军
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京东方科技集团股份有限公司
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Priority to US16/762,323 priority Critical patent/US11687095B2/en
Publication of WO2020140682A1 publication Critical patent/WO2020140682A1/zh

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    • 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
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0287—Control of position or course in two dimensions specially adapted to land vehicles involving a plurality of land vehicles, e.g. fleet or convoy travelling
    • G05D1/0291—Fleet control
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00—Programme-controlled manipulators
    • B25J9/16—Programme controls
    • B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
    • B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J11/00—Manipulators not otherwise provided for
    • B25J11/008—Manipulators for service tasks
    • B25J11/0085—Cleaning
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00—Programme-controlled manipulators
    • B25J9/16—Programme controls
    • B25J9/1602—Programme controls characterised by the control system, structure, architecture
    • B25J9/161—Hardware, e.g. neural networks, fuzzy logic, interfaces, processor
    • 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
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G05D1/0219—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory ensuring the processing of the whole working surface
    • 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
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G05D1/0246—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
    • 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
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0268—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means
    • G05D1/0274—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means using mapping information stored in a memory device
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/23—Clustering techniques
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/762—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using clustering, e.g. of similar faces in social networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/12—Computing arrangements based on biological models using genetic models
    • G06N3/126—Evolutionary algorithms, e.g. genetic algorithms or genetic programming

Definitions

  • the present disclosure relates to the field of computer technology. More specifically, it relates to a method and related system related to robot service, and a readable storage medium.
  • the multi-service robot service path planning method is usually to adopt the average distribution method of the service area. It is simply to divide the area by equal area and then plan the full coverage path, so as to provide comprehensive services regardless of whether the location of each area requires service. This method cannot identify the location of a region with service demand and performs path planning and service for it, which has low service efficiency and wastes energy consumption.
  • a method including: acquiring an image of a region to be served, wherein the region to be served includes a serviceable grid obtained by dividing the region to be served; performing pedestrian recognition on the image to obtain Pedestrian heat of each serviceable grid within a preset time period; and marking a serviceable grid with pedestrian heat exceeding a preset threshold and a serviceable grid within a preset range centered on it as a to-be-served grid.
  • the sub-area to be served composed of the grid to be served.
  • the method further includes: allocating a corresponding number of serviceable grids to each of the plurality of service robots to obtain a service area corresponding to each service robot; and determining the sub-area to be serviced and the corresponding service robot At the intersection of service areas, the service robot with the largest intersection is regarded as the service robot serving the sub-area to be served.
  • the method further includes: generating a service path of the service robot.
  • allocating a corresponding number of serviceable grids to each of the plurality of service robots includes allocating an equal number of serviceable grids to each of the plurality of service robots.
  • the method further includes: constructing an area to be served, and dividing the area to be served into an equal area grid to obtain a serviceable grid.
  • the marking of a serviceable grid with pedestrian heat exceeding a preset threshold and a serviceable grid within a preset range centered on it is marked as a grid to be served, and obtaining the subregion to be served further includes : Mark the serviceable grid with pedestrian heat exceeding the preset threshold and the serviceable grid within the preset range centered on it as the grid to be serviced, group the grids to be serviced by clustering method, according to each grouping The edge grid constitutes the sub-region to be served.
  • forming the sub-region to be served according to the edge grids in each group further includes: for each group, a serviceable grid covered by a polygonal region wrapped by a center connecting line of the edge grid in the group All serve as the grid to be served of the group, and constitute the sub-area of the group to be served.
  • the generation of the service path of the service robot further includes: if a certain service robot serves as a service robot performing at least two sub-regions to be served, then the optimal service robot is calculated by genetic algorithm for all Describe the service sequence of at least two sub-areas to be served.
  • performing pedestrian recognition on the image to obtain pedestrian popularity of each serviceable grid within a preset time period further includes: performing pedestrian recognition on the image within a preset time period to obtain each The number of pedestrians in each serviceable grid at a time; and the average value of the number of pedestrians in each serviceable grid in a preset period of time is integrated within the preset period to obtain the pedestrian heat of each serviceable grid.
  • a system including: a pedestrian heat acquisition module configured to acquire an image of an area to be served, wherein the area to be served includes a serviceable grid obtained by dividing the area to be served, and Pedestrian recognition is performed on the image to obtain the pedestrian heat of each serviceable grid within a preset time period; and the sub-region marking module to be served is configured to configure the serviceable grid with pedestrian heat exceeding a preset threshold and its center The serviceable grid within the preset range is marked as the grid to be serviced, and the subregion to be serviced composed of the grid to be serviced is obtained.
  • the system further includes: a serviceable grid division module configured to allocate a corresponding number of serviceable grids to each of the plurality of service robots to obtain a service area corresponding to each service robot; and a determination module , Configured to determine the intersection of the sub-area to be served and the service area corresponding to each service robot, and use the service robot with the largest intersection as the service robot serving the sub-area to be served.
  • a serviceable grid division module configured to allocate a corresponding number of serviceable grids to each of the plurality of service robots to obtain a service area corresponding to each service robot
  • a determination module Configured to determine the intersection of the sub-area to be served and the service area corresponding to each service robot, and use the service robot with the largest intersection as the service robot serving the sub-area to be served.
  • the determination module is further configured to: generate a service path of the service robot.
  • the serviceable grid division module is configured to allocate an equal number of serviceable grids to each of the plurality of service robots.
  • the system further includes: a serviceable grid acquisition module configured to construct a map of the area to be served, and divide the area of the service area into equal-area grids to obtain the serviceable grid.
  • a serviceable grid acquisition module configured to construct a map of the area to be served, and divide the area of the service area into equal-area grids to obtain the serviceable grid.
  • the to-be-served sub-region marking module is configured to mark a serviceable grid with pedestrian heat exceeding a preset threshold and a serviceable grid within a preset range centered on it as a to-be-served grid Grid, the grids to be served are grouped by clustering method, and the sub-regions to be served are formed according to the edge grids in each group.
  • the to-be-served sub-region marking module is further configured to form a to-be-served sub-region according to the edge grids in each group by:
  • the serviceable grids covered by the polygonal area wrapped by the center connecting line all serve as the grid to be serviced of the group, and constitute the sub-region to be serviced of the group.
  • the determination module is configured to, when a certain service robot is used as a service robot that executes services for at least two sub-regions to be serviced, calculate the optimal service robot for the at least two Service order of service sub-area.
  • the pedestrian heat acquisition module is configured to perform pedestrian recognition on the image within a preset period of time to obtain the number of pedestrians that can serve the grid at each moment within the preset period of time;
  • the average value of the number of pedestrians in each serviceable grid in the system is integrated within a preset period to obtain the pedestrian heat of each serviceable grid.
  • a service system which includes a plurality of service robots and the system described above.
  • a computer-readable storage medium on which a computer program is stored, where the program implements the method described above when the program is executed by a processor.
  • a computer system including: a memory on which a computer program is stored; and one or more processors configured to execute the computer program to perform the method as described above.
  • a service robot including: a memory on which computer program instructions are stored; and a processor coupled to the memory and configured to: receive a serviceable grid of a service area of the service robot Pedestrian popularity, serviceable grids are obtained by dividing the service area into grids, determining the number of serviceable grids where pedestrian popularity exceeds a preset threshold, determining whether the number exceeds a threshold, and responding to the number A threshold is exceeded, so that the service robot serves the service area.
  • the serviceable grid is obtained by dividing the service area into equal-area grids.
  • a service robot including: a memory on which computer program instructions are stored; and a processor coupled to the memory and configured to: receive information of a plurality of sub-regions to be served, wherein The plurality of sub-regions to be serviced is composed of a serviceable grid where pedestrian heat exceeds a preset threshold, and the serviceable grid is obtained by grid dividing the region to be serviced including the plurality of sub-regions to be serviced, Calculate the number of grids where the service area of the service robot intersects the multiple service sub-areas, and determine the sub-area to be served with the largest number of intersecting grids as the service area of the service robot.
  • the serviceable grid is obtained by dividing the area to be serviced including the multiple sub-areas to be served by an equal area grid.
  • the processor is further configured to determine the sub-area to be served with the number of intersecting grids exceeding the threshold and the number of intersecting grids as the service area of the service robot.
  • FIG. 1 shows a flowchart of a service robot path planning method provided by an embodiment of the present disclosure.
  • FIG. 2 shows a schematic diagram of grid division of a service area map and distribution of serviceable grids for multiple service robots.
  • FIG. 3 shows a schematic diagram of marking a grid to be served.
  • FIG. 4 shows a schematic diagram of the intersection of the sub-area to be served and the service area corresponding to each service robot.
  • Fig. 5 shows a schematic diagram of grouping grids to be served by clustering and forming sub-regions to be served according to edge grids in each group.
  • FIG. 6 shows a schematic diagram of a service system provided by an embodiment of the present disclosure.
  • FIG. 7 is a schematic structural diagram of a service robot path planning system provided by an embodiment of the present disclosure.
  • the present disclosure relates to methods, systems, and media related to service robots.
  • the method according to some embodiments of the present disclosure may include: acquiring an image of a region to be served, wherein the region to be served includes a serviceable grid obtained by dividing the area to be serviced into equal-area grids; and then performing pedestrian recognition on the image to Obtain the pedestrian heat of each serviceable grid within the preset time period; and mark the serviceable grid with pedestrian heat exceeding the preset threshold and the serviceable grid within the preset range centered on it as the to-be-served grid to obtain
  • the sub-area to be served consists of the grid to be served.
  • This novel method for determining the sub-area to be serviced takes into account pedestrian heat, so that the area that is really necessary to be served can be effectively determined, and the area that is not necessary to be served can be avoided from being determined as the area to be served, which improves the efficiency of service and saves Unnecessary energy consumption.
  • the method according to some embodiments of the present disclosure may further include: allocating a corresponding number of serviceable grids to each of the plurality of service robots to obtain a service area corresponding to each service robot; and determining the sub-area to be serviced and the corresponding service robot The intersection of the service areas of the system takes the service robot with the largest intersection as the service robot serving the sub-area to be served.
  • This novel method of allocating service robots considers that the size of the intersection between the sub-area to be served and the service area corresponding to each service robot is different, and takes the service robot with the largest intersection as the service robot serving the sub-area to be served, so that The change of the service sub-area to determine the most suitable service robot to serve the sub-area to be served further improves service efficiency and saves energy consumption.
  • the method according to some embodiments of the present disclosure may further include: generating a service path of the service robot.
  • the service path is generated based on the sub-area to be served, thereby further improving service efficiency and saving energy consumption.
  • the services may be cleaning services, sales services, consulting services, and so on.
  • the method illustrated below includes multiple steps, and those skilled in the art may understand that one or more of the multiple steps may be omitted. In some cases, more steps can also be added.
  • an embodiment of the present disclosure provides a service robot path planning method, including:
  • the flat map of the shopping mall is divided into multiple grids, where the serviceable grids such as shopping mall channels, etc., and the non-serviceable grids such as merchants Stores, containers, etc., each service robot is allocated to a service area composed of the same number and adjacent service grids.
  • the number of service grids is not necessarily the number of service robots. It is an integer multiple. Therefore, if the number of serviceable grids is an integer multiple of the number of service robots, it should be absolutely the same, otherwise it should be roughly the same.
  • each of the multiple service robots is assigned an equal number (for example, 12) of service areas composed of serviceable grids, but those skilled in the art can understand that Each of the service robots is assigned a service area composed of a different number of serviceable grids.
  • S5. Determine the intersection of the sub-area to be served and the service area corresponding to each service robot, and use the service robot with the largest intersection as the service robot serving the sub-area to be serviced to generate the service path of the service robot; in a specific example, as shown in FIG. 4 As shown, the service area corresponding to the service robot in the upper left corner is A, and the intersection between the sub-area to be serviced and the service area A is the largest. Therefore, the service robot in the upper-left corner is regarded as the service robot serving the sub-area to be served.
  • the service robot path planning method provided in this embodiment divides the map of the area to be serviced and identifies the serviceable grid therein, and assigns corresponding service areas to multiple service robots, based on the serviceable grid identified from the image
  • the number of pedestrians is used to obtain the pedestrian heat of the serviceable grid, and the pedestrian heat is used as the basis for judging the dirty degree of the serviceable grid, and the pedestrian flow of the serviceable grid around the serviceable grid with high pedestrian heat is bound to be
  • the serviceable grid with pedestrian heat exceeding the preset threshold and the serviceable grid within the preset range centered on it are marked as the grid to be serviced, and the service range is expanded to obtain area.
  • the obtained sub-area to be served is a relatively continuous serviceable grid, which avoids over-dispersion and facilitates path planning.
  • the service robot with the largest intersection with the sub-area to be served only serves the sub-area to be serviced and does not serve all the serviceable grids. It can realize targeted local services after judging the degree of dirt damage in different areas. , Effectively avoid serving unnecessary regional locations, improve efficiency and save energy consumption.
  • performing pedestrian recognition on the image in step S3 to obtain pedestrian heat of each serviceable grid within a preset time period further includes:
  • Pedestrian recognition is performed on the image within a preset period of time to obtain the number of pedestrians that can serve the grid at each moment within the preset period of time;
  • the average value of the number of pedestrians in each serviceable grid in the preset time period is separately integrated within the preset time period to obtain the pedestrian heat of each serviceable grid.
  • multiple cameras may be provided in the area to be served to ensure that all serviceable grids can be covered.
  • Pedestrian recognition is performed frame by frame with images collected by multiple cameras (by means of feature recognition of the pedestrian's head, etc.).
  • step S4 mark a serviceable grid with pedestrian heat exceeding a preset threshold and a serviceable grid within a preset range centered on it as a grid to be served, "Obtaining the subarea to be served” further includes:
  • This implementation method ensures that the grids to be served in each sub-region to be serviced are concentrated and non-continuous grids to be served in the sub-regions to be serviced are avoided, thereby ensuring that the service robot performs a short path when performing services It is convenient to plan its service path in the sub-area to be served.
  • the clustering method is used to group the grids to be served, and the sub-regions to be serviced according to the edge grids in each grouping further include:
  • the grids to be served are grouped according to the preset clustering radius and the minimum number of grids to be served in the group, and the sub-regions to be served are formed according to the edge grids in each group.
  • the clustering method is used to group the grids to be serviced according to the preset clustering radius R and the minimum number m of the grids to be served in the grouping.
  • a certain grouping is connected by In the edge grid in the group, the serviceable grid covered by the polygonal area wrapped by the center connecting line of the edge grid in the group is taken as the group to be serviced and constitutes the group to be served sub-region.
  • the generation of the service path of the service robot in step S5 further includes: if a certain service robot serves as a service robot that executes services in at least two sub-regions to be served, then using genetic algorithms The optimal service sequence of the at least two sub-regions to be serviced by the service robot is calculated, wherein the genetic algorithm may be an existing general genetic algorithm.
  • the generating the service path of the service robot in step S5 further includes: acquiring a center to-be-served grid of the service sub-region, and setting the service-to-be-served grid when the service robot executes the service Counterclockwise internal spiral service for the center.
  • the service robot can be avoided from reciprocating in the same path in the generated service path, which can further improve service efficiency and save energy consumption.
  • the counterclockwise inner spiral conforms to the pedestrian walking habit, which can reduce the Pedestrian influence.
  • the inner spiral represents the spiral movement from outside to inside.
  • the method further includes: counting a period in which the total pedestrian heat of the area to be served is the lowest in each period of each day, and the path planning manner in this period is for each service robot to serve the corresponding The service area is to provide a full service for the area to be served.
  • another embodiment of the present disclosure provides a service system, including a service robot path planning system 100 and multiple service robots 200;
  • the service robot path planning system 100 includes:
  • the serviceable grid acquisition module 101 is configured to construct a map of the area to be served, and divide the area to be serviced into equal-area grids to obtain the serviceable grid;
  • the serviceable grid division module 102 is configured to allocate a corresponding number of serviceable grids to each of a plurality of service robots to obtain a service area corresponding to each service robot;
  • the pedestrian heat obtaining module 103 is configured to obtain an image of the area to be served, and perform pedestrian recognition on the image to obtain the pedestrian heat of each serviceable grid within a preset time period;
  • the to-be-served sub-region marking module 104 is configured to mark a serviceable grid with pedestrian heat exceeding a preset threshold and a serviceable grid within a preset range centered on it as a to-be-served grid to obtain a to-be-served sub-region;
  • the determining module 105 is configured to determine the intersection of the sub-area to be served and the service area corresponding to each service robot, and use the service robot with the largest intersection as the service robot serving the sub-area to be served to generate the service path of the service robot.
  • the service robot 200 is configured to serve the sub-area to be serviced according to the service path instruction generated by the service robot path planning system 100.
  • the service robot may include, for example, a memory storing a computer program and a processor.
  • the processor may execute a computer program to cause the service robot to perform the method of the embodiments of the present disclosure.
  • the service robot may receive the pedestrian heat of the serviceable grid of the service area of the service robot.
  • the serviceable grid may be obtained by grid dividing the service area.
  • the service robot may determine the number of serviceable grids where pedestrian heat exceeds a preset threshold, determine whether the number exceeds a threshold, and in response to the number exceeding a threshold, cause the service robot to serve the service area. For example, suppose that the service robot is responsible for a certain service area containing 12 grids. When it is determined based on the received pedestrian heat information that the number of grids with pedestrian heat exceeding the threshold is 7, and the threshold exceeds 6, for example, the service robot is started. Serve the service area.
  • This solution enables service robots to perform necessary services based on pedestrian heat, avoiding unnecessary services, improving service efficiency, and saving energy consumption.
  • the service robot may include, for example, a memory storing a computer program and a processor.
  • the processor may execute a computer program to cause the service robot to perform the methods of other embodiments of the present disclosure.
  • the service robot may receive information of multiple sub-areas to be served.
  • the multiple sub-regions to be served may be composed of a serviceable grid whose pedestrian heat exceeds a preset threshold.
  • the serviceable grid is obtained by grid-dividing the area to be served that includes the plurality of sub-areas to be served.
  • the service robot may calculate the number of grids where the service area that the service robot is responsible for intersects with the plurality of service sub-areas, and determine the sub-area to be served with the largest number of intersecting grids as the service area of the service robot. For example, assuming that the service area of the service robot and the three sub-areas to be serviced all have intersections, the sub-area to be serviced with the largest number of intersecting grids is determined as the service area of the service robot.
  • the service robot determines the sub-region to be served that the number of intersecting grids exceeds the threshold and the number of intersecting grids is the service area of the service robot. That is, when the number of intersecting grids is the largest and exceeds the threshold, the corresponding sub-area to be serviced is determined as the service area of the service robot.
  • a computer system suitable for implementing the service robot path planning system and the service robot provided by this embodiment includes a central processing unit (CPU), which can be based on a program stored in a read-only memory (ROM) Or a program loaded into a random access memory (RAM) from a storage section to perform various appropriate actions and processes.
  • CPU central processing unit
  • RAM random access memory
  • various programs and data necessary for the operation of the computer system are also stored.
  • the CPU, ROM, and RAM are connected through the bus.
  • the input/input (I/O) interface is also connected to the bus.
  • the following components are connected to the I/O interface: input part including keyboard, mouse, etc.; output part including liquid crystal display (LCD), etc. and speakers; storage part including hard disk, etc.; and network including such as LAN card, modem, etc.
  • the communication part of the interface card performs communication processing via a network such as the Internet.
  • the drive is also connected to the I/O interface as needed. Removable media, such as magnetic disks, optical disks, magneto-optical disks, semiconductor memories, etc., are installed on the drive as needed, so that the computer program read out therefrom is installed into the storage portion as needed.
  • the process described in the above flowchart can be implemented as a computer software program.
  • this embodiment includes a computer program product that includes a computer program tangibly contained on a computer-readable medium, and the above-mentioned computer program contains program code for executing the method shown in the flowchart.
  • the computer program may be downloaded and installed from the network through the communication section, and/or installed from a removable medium.
  • each block in the flowchart or schematic diagram may represent a module, a program segment, or a part of code, and the above-mentioned module, program segment, or part of code contains one or more Execute instructions.
  • the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may actually be executed in parallel, and they may sometimes be executed in reverse order, depending on the functions involved.
  • each block in the schematic and/or flowchart, and combinations of blocks in the schematic and/or flowchart can be implemented with a dedicated hardware-based system that performs the specified function or operation Or, it can be realized by a combination of dedicated hardware and computer instructions.
  • the modules described in this embodiment may be implemented in software or hardware.
  • the described module can also be set in the processor.
  • a processor including a serviceable grid acquisition module, a serviceable grid division module, a pedestrian heat acquisition module, a sub-region marking module to be served and Identify the module.
  • the names of these modules do not constitute a limitation on the module itself under certain circumstances.
  • this embodiment also provides a non-volatile computer storage medium.
  • the non-volatile computer storage medium may be the non-volatile computer storage medium included in the above-described device in the foregoing embodiment, or It may be a non-volatile computer storage medium that exists alone and is not installed in the terminal.
  • the non-volatile computer storage medium stores one or more programs.
  • the device When the one or more programs are executed by a device, the device is configured to: construct a map of the area to be served, and divide the area map of the service into an equal area grid , Obtain a serviceable grid; assign a corresponding number of serviceable grids to each of the multiple service robots to obtain a service area corresponding to each service robot; obtain an image of the area to be serviced, perform pedestrian recognition on the image to obtain a pre- Pedestrian heat of each serviceable grid within the set time period; mark the serviceable grid whose pedestrian heat exceeds the preset threshold and the serviceable grid within the preset range centered on it as the grid to be serviced to obtain the grid to be served Area; determine the intersection of the sub-area to be served and the service area corresponding to each service robot, and use the service robot with the largest intersection as the service robot serving the sub-area to be serviced to generate the service path of the service robot.

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Abstract

一种与机器人服务有关的方法，包括：获取待服务区域的图像，其中待服务区域包括通过对待服务区域进行等面积栅格划分获得的可服务栅格；对图像进行行人识别以获取预设时段内各可服务栅格的行人热度；和将行人热度超过预设阈值的可服务栅格及以其为中心的预设范围内的可服务栅格标记为待服务栅格，得到由待服务栅格组成的待服务子区域。该方法能够将行人热度大的区域分配给特定机器人去执行服务，由此提高了清扫效率。还提供了执行上述与机器人服务有关的方法的***、可读存储介质。

Description

与机器人服务有关的方法及相关***、可读存储介质
相关申请的交叉引用
本申请要求于2019年1月2日提交的发明名称为“清扫机器人路径规划方法及相关***、可读存储介质”的中国专利申请第201910001378.6号的优先权，该申请的公开通过引用被全部结合于此。
技术领域
本公开涉及计算机技术领域。更具体地，涉及一种与机器人服务有关方法及相关***、可读存储介质。
背景技术
目前，多服务机器人服务路径规划方法通常为采用对待服务区域的平均分配法。其只是简单等面积划分区域后进行全覆盖路径规划，从而进行全面服务而不论各区域位置是否需要服务。该方法无法识别具有服务需求的区域位置并针对其进行路径规划及服务，服务效率低且浪费能耗。
发明内容
根据本公开一些实施例，提供一种方法，包括：获取待服务区域的图像，其中待服务区域包括通过对待服务区域进行栅格划分获得的可服务栅格；对所述图像进行行人识别以获取预设时段内各可服务栅格的行人热度；和将行人热度超过预设阈值的可服务栅格及以其为中心的预设范围内的可服务栅格标记为待服务栅格，得到由待服务栅格组成的待服务子区域。
根据本公开一些实施例，该方法还包括：为多个服务机器人的每一个分配相应数量的可服务栅格，得到对应各服务机器人的服务区域；和判断待服务子区域与对应各服务机器人的服务区域的交集，将交集最大的服务机器人作为服务待服务子区域的服务机器人。
根据本公开一些实施例，该方法还包括：生成服务机器人的服务路径。
根据本公开一些实施例，为多个服务机器人的每一个分配相应数量的可服务栅格包括为多个服务机器人的每一个分配等数量的可服务栅格。
根据本公开一些实施例，该方法还包括：构建待服务区域，并对待服务区域进行等面积栅格划分，获取可服务栅格.
根据本公开一些实施例，所述将行人热度超过预设阈值的可服务栅格及以其为中心的预设范围内的可服务栅格标记为待服务栅格，得到待服务子区域进一步包括：将行人热度超过预设阈值的可服务栅格及以其为中心的预设范围内的可服务栅格标记为待服务栅格，通过聚类方法将待服务栅格分组，根据各分组中的边缘栅格构成待服务子区域。
根据本公开一些实施例，根据各分组中的边缘栅格构成待服务子区域进一步包括：对于各分组，通过将该分组中的边缘栅格的中心连接线包裹的多边形区域覆盖的可服务栅格均作为该分组的待服务栅格，构成该分组的待服务子区域。
根据本公开一些实施例，所述生成服务机器人的服务路径进一步包括：若某个服务机器人作为执行服务至少两个待服务子区域的服务机器人，则通过遗传算法计算得到最优的服务机器人对于所述至少两个待服务子区域的服务顺序。
根据本公开一些实施例，对所述图像进行行人识别以获取预设时段内各可服务栅格的行人热度进一步包括：在预设时段内对所述图像进行行人识别，得到预设时段内各时刻各可服务栅格的行人数量；和分别对预设时段内各可服务栅格的行人数量的平均值在预设时段内进行积分，得到各可服务栅格的行人热度。
根据本公开一些实施例，提供一种***，包括：行人热度获取模块，配置为：获取待服务区域的图像，其中待服务区域包括通过对待服务区域进行栅格划分获得的可服务栅格，和对所述图像进行行人识别以获取预设时段内各可服务栅格的行人热度；以及待服务子区域标记模块，配置为将行人热度超过预设阈值的可服务栅格及以其为中心的预设范围内的可服务栅格标记为待服务栅格，得到由待服务栅格组成的待服务子区域。
根据本公开一些实施例，该***还包括：可服务栅格划分模块，配置为为多个服务机器人的每一个分配相应数量的可服务栅格，得到对应各服务机器人的服务区域；和确定模块，配置为判断待服务子区域与对应各服务机器人的服务区域的交集，将交集最大的服务机器人作为服务待服务子区域的服务机器人。
根据本公开一些实施例，所述确定模块还配置为：生成服务机器人的服务路径。
根据本公开一些实施例，可服务栅格划分模块被配置为为多个服务机器人的每一个分配等数量的可服务栅格。
根据本公开一些实施例，该***还包括：可服务栅格获取模块，配置为构建待服务区域地图，并对待服务区域地图进行等面积栅格划分，获取可服务栅格。
根据本公开一些实施例，所述待服务子区域标记模块，配置为将行人热度超过预设阈值的可服务栅格及以其为中心的预设范围内的可服务栅格标记为待服务栅格，通过聚类方法将待服务栅格分组，根据各分组中的边缘栅格构成待服务子区域。
根据本公开一些实施例，所述待服务子区域标记模块进一步配置为通过以下方式来根据各分组中的边缘栅格构成待服务子区域：对于各分组，通过将该分组中的边缘栅格的中心连接线包裹的多边形区域覆盖的可服务栅格均作为该分组的待服务栅格，构成该分组的待服务子区域。
根据本公开一些实施例，所述确定模块配置为在某个服务机器人作为执行服务至少两个待服务子区域的服务机器人时，通过遗传算法计算得到最优的服务机器人对于所述至少两个待服务子区域的服务顺序。
根据本公开一些实施例，所述行人热度获取模块配置为在预设时段内对所述图像进行行人识别，得到预设时段内各时刻各可服务栅格的行人数量；和分别对预设时段内各可服务栅格的行人数量的平均值在预设时段内进行积分，得到各可服务栅格的行人热度。
根据本公开一些实施例，提供一种服务***，其中，包括多个服务机器人和上所述的***。
根据本公开一些实施例，提供一种计算机可读存储介质，其上存储有计算机程序，其中，该程序被处理器执行时实现如上所述的方法。
根据本公开一些实施例，提供一种计算机***，包括：存储器，其上存储计算机程序；以及一个或多个处理器，配置为执行所述计算机程序来执行如上所述的方法。
根据本公开一些实施例，提供一种服务机器人，包括：存储器，其上存储计算机程序指令；和处理器，其与存储器耦接并被配置为：接收该服务机器人的服务区域的可服务栅格的行人热度，可服务栅格是通过对服务区域进行栅格划分获得的，确定行人热度超过预设阈值的可服务栅格的数量，确定所述数量是否超过一阈值，以及响应于所述数量超过一阈值，使得服务机器人服务该服务区域。
根据本公开一些实施例，可服务栅格是通过对服务区域进行等面积栅格划分获得的。
根据本公开一些实施例，提供一种服务机器人，包括：存储器，其上存储计算机程序指令；和处理器，其与存储器耦接并被配置为：接收多个待服务子区域的信息，其中所述多个待服务子区域是由行人热度超过预设阈值的可服务栅格组成的，可服务栅格是通过对包括所述多个待服务子区域的待服务区域进行栅格划分获得的，计算服务机器人的服务区域与所述多个服务子区域相交的栅格数，将相交的栅格数最大的待服务子区域确定为该服务机器人的服务区域。
根据本公开一些实施例，可服务栅格是通过对包括所述多个待服务子区域的待服务区域进行等面积栅格划分获得的。
根据本公开一些实施例，处理器还配置为：将相交的栅格数超过阈值并且相交的栅格数最多的待服务子区域确定为该服务机器人的服务区域。
附图说明
下面结合附图对本公开的具体实施方式作进一步详细的说明；
图1示出本公开实施例提供的服务机器人路径规划方法的流程图。
图2示出对待服务区域地图进行栅格划分及为多个服务机器人分配可服务栅格的示意图。
图3示出标记待服务栅格的示意图。
图4示出待服务子区域与对应各服务机器人的服务区域的交集的示意图。
图5示出通过聚类方法将待服务栅格分组并根据各分组中的边缘栅格构成待服务子 区域的示意图。
图6示出本公开实施例提供的服务***的示意图。
图7示出本公开实施例提供的服务机器人路径规划***的结构示意图。
具体实施方式
为了更清楚地说明本公开，下面结合优选实施例和附图对本公开做进一步的说明。附图中相似的部件以相同的附图标记进行表示。本领域技术人员应当理解，下面所具体描述的内容是说明性的而非限制性的，不应以此限制本公开的保护范围。
概述
本公开涉及与服务机器人有关的方法、***、介质。
根据本公开一些实施例的方法，可以包括：获取待服务区域的图像，其中待服务区域包括通过对待服务区域进行等面积栅格划分获得的可服务栅格；然后对所述图像进行行人识别以获取预设时段内各可服务栅格的行人热度；和将行人热度超过预设阈值的可服务栅格及以其为中心的预设范围内的可服务栅格标记为待服务栅格，得到由待服务栅格组成的待服务子区域。
该新颖的确定待服务子区域的方法，考虑了行人热度，从而能够有效确定真正有必要被服务的区域，可以避免不必要被服务的区域被确定为待服务区域，提高了服务的效率，节省了不必要的能耗。
根据本公开一些实施例的方法，进一步可以包括：为多个服务机器人的每一个分配相应数量的可服务栅格，得到对应各服务机器人的服务区域；以及判断待服务子区域与对应各服务机器人的服务区域的交集，将交集最大的服务机器人作为服务待服务子区域的服务机器人。
该新颖的分配服务机器人的方法，考虑了判断待服务子区域与对应各服务机器人的服务区域的交集的大小不同，将交集最大的服务机器人作为服务待服务子区域的服务机器人，从而能够根据待服务子区域的变化来确定最适合服务待服务子区域的服务机器人，进一步提高了服务效率，节约了能耗。
根据本公开一些实施例的方法，进一步可以包括：生成服务机器人的服务路径。该服务路径基于待服务子区域生成，从而进一步提高了服务效率，节约了能耗。
所述服务可以是清扫服务，销售服务，咨询服务等。
以下例示的方法中包含多个步骤，本领域技术人员可以理解，这多个步骤中的一个或多个可以省略。在一些情况下，也可以增加更多的步骤。
如图1所示，本公开的一个实施例提供了一种服务机器人路径规划方法，包括：
S1、构建待服务区域地图，并对待服务区域地图进行等面积栅格划分，获取可服务栅格；
S2、为在待服务区域中布置的多个服务机器人的每一个分配相应数量的可服务栅格，得到对应各服务机器人的服务区域。
在一个具体示例中，如图2所示，假设待服务区域为商场，将商场的平面地图等分为 多个栅格，其中，可服务栅格例如商场通道等，而不可服务栅格例如商家店铺、货柜等，各服务机器人被分配到由数量相同的且相邻的可服务栅格组成的服务区域，可理解的是，由于可服务栅格的个数不一定是服务机器人的个数的整数倍，因此，若恰好可服务栅格的个数是服务机器人的个数的整数倍，则应为绝对相同，否则为大致相同即可。在图2中，为了便于说明，示出的是为多个服务机器人的每一个分配相等数量(例如12个)的可服务栅格组成的服务区域，但是本领域技术人员可以理解，可以为多个服务机器人的每一个分配不同数量的可服务栅格组成的服务区域。
S3、获取待服务区域的图像，对所述图像进行行人识别以获取预设时段内各可服务栅格的行人热度；
S4、将行人热度超过预设阈值的可服务栅格及以其为中心的预设范围内的可服务栅格标记为待服务栅格，得到待服务子区域；在一个具体示例中，如图3所示，可先将行人热度超过预设阈值的可服务栅格标记为热度临界栅格，再将以各热度临界栅格为中心的半径r范围内的可服务栅格及热度临界栅格本身标记为待服务栅格，得到由相邻待服务栅格构成的待服务子区域，图3中的待服务子区域为两个；
S5、判断待服务子区域与对应各服务机器人的服务区域的交集，将交集最大的服务机器人作为服务待服务子区域的服务机器人，生成服务机器人的服务路径；在一个具体示例中，如图4所示，对应左上角的服务机器人的服务区域为A，而待服务子区域与服务区域A的交集最大，因此将左上角的服务机器人作为服务待服务子区域的服务机器人。
本实施例提供的服务机器人路径规划方法，在将待服务区域地图进行划分并识别其中的可服务栅格后，为多个服务机器人分配对应的服务区域，根据从图像中识别的可服务栅格的行人数量获取可服务栅格的行人热度，将行人热度作为判断可服务栅格的脏损程度的判断依据，而由于行人热度高的可服务栅格周围的可服务栅格的行人流量必然会在预设时段之后增加，因此将行人热度超过预设阈值的可服务栅格及以其为中心的预设范围内的可服务栅格标记为待服务栅格，扩充服务范围，得到待服务子区域。这样，得到的待服务子区域为比较连续的可服务栅格，避免了过于分散，也利于路径规划。最后，利用与待服务子区域交集最大的服务机器人仅服务待服务子区域而并非对所有可服务栅格均进行服务，可实现在判断不同区域位置的脏损程度后进行有针对性的局部服务，有效地避免了对不必要的区域位置进行服务，提高了效率且节省了能耗。
在本实施例的一些可选的实现方式中，步骤S3中对所述图像进行行人识别以获取预设时段内各可服务栅格的行人热度进一步包括：
在预设时段内对所述图像进行行人识别，得到预设时段内各时刻各可服务栅格的行人数量；
分别对预设时段内各可服务栅格的行人数量的平均值在预设时段内进行积分，得到各可服务栅格的行人热度。
在一个具体示例中，可在待服务区域设置多个摄像头，保证所有可服务栅格均能被覆盖。通过多个摄像头采集的图像逐帧进行行人识别(可通过对行人的头部进行特征识别等方式)，对于各可服务栅格，计算单位时间段t内某可服务栅格中的行人数量平均值n， 之后在t时间段内进行积分以得到该可服务栅格的行人热度h，假设单位时间段t内图像采集的总帧数为p，则单位时间段t内该可服务栅格可服务栅格的行人热度为h＝∫ tn·Δt，行人热度为行人数量对时间的累计值。
在本实施例的一些可选的实现方式中，步骤S4“将行人热度超过预设阈值的可服务栅格及以其为中心的预设范围内的可服务栅格标记为待服务栅格，得到待服务子区域”进一步包括：
将行人热度超过预设阈值的可服务栅格及以其为中心的预设范围内的可服务栅格标记为待服务栅格，通过聚类方法将待服务栅格分组，根据各分组中的边缘栅格构成待服务子区域。
采用此实现方式，保证了每个待服务子区域中的待服务栅格较集中且避免了待服务子区域中出现非连续的待服务栅格，进而保证了服务机器人执行服务时路径较短且便于规划其在待服务子区域中的服务路径。
在本实施例的一些可选的实现方式中，所述通过聚类方法将待服务栅格分组，根据各分组中的边缘栅格构成待服务子区域进一步包括：
根据预设的聚类半径和分组中待服务栅格最小数量将待服务栅格分组，根据各分组中的边缘栅格构成待服务子区域。
采用此实现方式，避免了出现包含待服务栅格过少的服务子区域，进一步避免了服务子区域的划定较分散的情况。
在一个具体示例中，如图5所示，由于可服务栅格可能分布的较分散，此时可能会出现若某个服务机器人负责的待服务子区域中的某些待服务栅格距离同一待服务子区域中的其他大多数待服务栅格较远，而距其他待服务子区域中的待服务栅格较近的情况，这样不利于提高服务效率和节省能耗。因此本实现方式在标记待服务栅格后，通过聚类方法，根据预设的聚类半径R和分组中待服务栅格最小数量m将待服务栅格分组，对于各分组，通过连接某分组中的边缘栅格，将该分组中的边缘栅格的中心连接线包裹的多边形区域覆盖的可服务栅格均作为该分组的待服务栅格，构成该分组的待服务子区域。
在本实施例的一些可选的实现方式中，步骤S5中所述生成服务机器人的服务路径进一步包括：若某个服务机器人作为执行服务至少两个待服务子区域的服务机器人，则通过遗传算法计算得到最优的服务机器人对于所述至少两个待服务子区域的服务顺序，其中，遗传算法可为现有的通用遗传算法。
采用此实现方式，可合理规划作为执行服务至少两个待服务子区域的服务机器人对其负责的各待服务子区域的服务顺序，利于合理生成服务机器人的服务路径。
在本实施例的一些可选的实现方式中，步骤S5中所述生成服务机器人的服务路径进一步包括：获取服务子区域的中心待服务栅格，设置服务机器人执行服务时以中心待服务栅格为中心进行逆时针内螺旋服务。
采用此实现方式，可在生成的服务路径中避免服务机器人在同一路径往复运动，可进一步地提高服务效率并节省能耗，另外，逆时针内螺旋符合行人走路的习惯，可减少服务机器人运动对行人的影响。其中，内螺旋表示由外至内的螺旋运动。负责两个以上服务子 区域时，对每个服务子区域依次进行逆时针内螺旋服务，而对服务子区域的服务顺序可通过遗传算法计算得到。
在本实施例的一些可选的实现方式中，该方法还包括：统计每日各时段中待服务区域的行人总热度最低的时段，在该时段的路径规划方式为所有服务机器人服务各自对应的服务区域，即进行一次待服务区域的全面服务。
如图6所示，本公开的另一个实施例提供了一种服务***，包括服务机器人路径规划***100和多个服务机器人200；
其中，服务机器人路径规划***100包括：
可服务栅格获取模块101，配置为构建待服务区域地图，并对待服务区域地图进行等面积栅格划分，获取可服务栅格；
可服务栅格划分模块102，配置为为多个服务机器人的每一个分配相应数量的可服务栅格，得到对应各服务机器人的服务区域；
行人热度获取模块103，配置为获取待服务区域的图像，对所述图像进行行人识别以获取预设时段内各可服务栅格的行人热度；
待服务子区域标记模块104，配置为将行人热度超过预设阈值的可服务栅格及以其为中心的预设范围内的可服务栅格标记为待服务栅格，得到待服务子区域；
确定模块105，配置为判断待服务子区域与对应各服务机器人的服务区域的交集，将交集最大的服务机器人作为服务待服务子区域的服务机器人，生成服务机器人的服务路径。
服务机器人200，配置为根据服务机器人路径规划***100生成的服务路径指令对待服务子区域进行服务。
在本公开一些实施例中，服务机器人例如可以包括存储计算机程序的存储器和处理器。处理器可以执行计算机程序来使得服务机器人执行本公开实施例的方法。
例如，服务机器人可以接收该服务机器人的服务区域的可服务栅格的行人热度。如上所述，可服务栅格可以是通过对服务区域进行栅格划分获得的。服务机器人可以确定行人热度超过预设阈值的可服务栅格的数量，确定所述数量是否超过一阈值，以及响应于所述数量超过一阈值，使得服务机器人服务该服务区域。例如，假设服务机器人负责包含12个栅格的某一服务区域，当基于接收的行人热度信息确定行人热度超过阈值的栅格的数量为7个，超过了阈值例如6个，则使得服务机器人开始服务该服务区域。
该方案使得服务机器人可以根据行人热度来进行必要的服务，避免了不必要的服务，提高了服务效率，节约了能耗。
在本公开另一些实施例中，服务机器人例如可以包括存储计算机程序的存储器和处理器。处理器可以执行计算机程序来使得服务机器人执行本公开另一些实施例的方法。
例如，服务机器人可以接收多个待服务子区域的信息。多个待服务子区域可以是由行人热度超过预设阈值的可服务栅格组成的。如上所述，可服务栅格是通过对包括所述多个待服务子区域的待服务区域进行栅格划分获得的。服务机器人可以计算该服务机器人自己负责的服务区域与所述多个服务子区域相交的栅格数，并将相交的栅格数最大的待服务子区域确定为该服务机器人的服务区域。例如，假设服务机器人的服务区域与3个待服务子 区域都有交集，则与之具有最大相交栅格数的待服务子区域被确定为该服务机器人的服务区域。
在一些实施例中，服务机器人将相交的栅格数超过阈值并且相交的栅格数最多的待服务子区域确定为该服务机器人的服务区域。即，当相交的栅格数最多并且超过阈值时，将相应的待服务子区域确定为该服务机器人的服务区域。
需要说明的是，本实施例提供的服务***中的服务机器人路径规划***100的原理及工作流程与上述服务机器人路径规划方法相似，相关之处可以参照上述说明，在此不再赘述。
如图7所示，适于用来实现本实施例提供的服务机器人路径规划***以及服务机器人的计算机***，包括中央处理器(CPU)，其可以根据存储在只读存储器(ROM)中的程序或者从存储部分加载到随机访问存储器(RAM)中的程序而执行各种适当的动作和处理。在RAM中，还存储有计算机***操作所需的各种程序和数据。CPU、ROM以及RAM通过总线被此相连。输入/输入(I/O)接口也连接至总线。
以下部件连接至I/O接口:包括键盘、鼠标等的输入部分；包括诸如液晶显示器(LCD)等以及扬声器等的输出部分；包括硬盘等的存储部分；以及包括诸如LAN卡、调制解调器等的网络接口卡的通信部分。通信部分经由诸如因特网的网络执行通信处理。驱动器也根据需要连接至I/O接口。可拆卸介质，诸如磁盘、光盘、磁光盘、半导体存储器等等，根据需要安装在驱动器上，以便于从其上读出的计算机程序根据需要被安装入存储部分。
特别地，根据本实施例，上文流程图描述的过程可以被实现为计算机软件程序。例如，本实施例包括一种计算机程序产品，其包括有形地包含在计算机可读介质上的计算机程序，上述计算机程序包含用于执行流程图所示的方法的程序代码。在这样的实施例中，该计算机程序可以通过通信部分从网络上被下载和安装，和/或从可拆卸介质被安装。
附图中的流程图和示意图，图示了本实施例的***、方法和计算机程序产品的可能实现的体系架构、功能和操作。在这点上，流程图或示意图中的每个方框可以代表一个模块、程序段或代码的一部分，上述模块、程序段或代码的一部分包含一个或多个用于实现规定的逻辑功能的可执行指令。也应当注意，在有些作为替换的实现中，方框中所标注的功能也可以以不同于附图中所标注的顺序发生。例如，两个接连地表示的方框实际上可以基本并行地执行，它们有时也可以按相反的顺序执行，这依所涉及的功能而定。也要注意的是，示意图和/或流程图中的每个方框、以及示意和/或流程图中的方框的组合，可以用执行规定的功能或操作的专用的基于硬件的***来实现，或者可以用专用硬件与计算机指令的组合来实现。
描述于本实施例中所涉及到的模块可以通过软件的方式实现，也可以通过硬件的方式来实现。所描述的模块也可以设置在处理器中，例如，可以描述为：一种处理器，包括可服务栅格获取模块、可服务栅格划分模块、行人热度获取模块、待服务子区域标记模块和确定模块。其中，这些模块的名称在某种情况下并不构成对该模块本身的限定。
作为另一方面，本实施例还提供了一种非易失性计算机存储介质，该非易失性计算机存储介质可以是上述实施例中上述装置中所包含的非易失性计算机存储介质，也可以是单 独存在，未装配入终端中的非易失性计算机存储介质。上述非易失性计算机存储介质存储有一个或者多个程序，当上述一个或者多个程序被一个设备执行时，使得上述设备：构建待服务区域地图，并对待服务区域地图进行等面积栅格划分，获取可服务栅格；为多个服务机器人的每一个分配相应数量的可服务栅格，得到对应各服务机器人的服务区域；获取待服务区域的图像，对所述图像进行行人识别以获取预设时段内各可服务栅格的行人热度；将行人热度超过预设阈值的可服务栅格及以其为中心的预设范围内的可服务栅格标记为待服务栅格，得到待服务子区域；判断待服务子区域与对应各服务机器人的服务区域的交集，将交集最大的服务机器人作为服务待服务子区域的服务机器人，生成服务机器人的服务路径。
需要说明的是，在本公开的描述中，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括所述要素的过程、方法、物品或者设备中还存在另外的相同要素。
显然，本公开的上述实施例仅仅是为清楚地说明本公开所作的举例，而并非是对本公开的实施方式的限定，对于本领域的普通技术人员来说，在上述说明的基础上还可以做出其它不同形式的变化或变动，这里无法对所有的实施方式予以穷举，凡是属于本公开的技术方案所引伸出的显而易见的变化或变动仍处于本公开的保护范围之列。

Claims (26)

  1. 一种方法，包括：
    获取待服务区域的图像，其中待服务区域包括通过对待服务区域进行栅格划分获得的可服务栅格；
    对所述图像进行行人识别以获取预设时段内各可服务栅格的行人热度；和
    将行人热度超过预设阈值的可服务栅格及以其为中心的预设范围内的可服务栅格标记为待服务栅格，得到由待服务栅格组成的待服务子区域。
  2. 如权利要求1所述的方法，还包括：
    为多个服务机器人的每一个分配相应数量的可服务栅格，得到对应各服务机器人的服务区域；
    判断待服务子区域与对应各服务机器人的服务区域的交集，将交集最大的服务机器人作为服务待服务子区域的服务机器人。
  3. 如权利要求2所述的方法，还包括：
    生成服务机器人的服务路径。
  4. 如权利要求3所述的方法，其中，为多个服务机器人的每一个分配相应数量的可服务栅格包括为多个服务机器人的每一个分配等数量的可服务栅格。
  5. 如权利要求4所述的方法，还包括：
    构建待服务区域，并对待服务区域进行等面积栅格划分，获取可服务栅格。
  6. 根据权利要求1-5中任一项所述的方法，其中，所述将行人热度超过预设阈值的可服务栅格及以其为中心的预设范围内的可服务栅格标记为待服务栅格，得到待服务子区域进一步包括：
    将行人热度超过预设阈值的可服务栅格及以其为中心的预设范围内的可服务栅格标记为待服务栅格，通过聚类方法将待服务栅格分组，根据各分组中的边缘栅格构成待服务子区域。
  7. 据权利要求6所述的方法，其中，根据各分组中的边缘栅格构成待服务子区域进一步包括：
    对于各分组，通过将该分组中的边缘栅格的中心连接线包裹的多边形区域覆盖的可服务栅格均作为该分组的待服务栅格，构成该分组的待服务子区域。
  8. 根据权利要求3所述的方法，其中，所述生成服务机器人的服务路径进一步包括：若某个服务机器人作为执行服务至少两个待服务子区域的服务机器人，则通过遗传算法计算得到最优的服务机器人对于所述至少两个待服务子区域的服务顺序。
  9. 根据权利要求1-5中任一项所述的方法，其中，对所述图像进行行人识别以获取预设时段内各可服务栅格的行人热度进一步包括：
    在预设时段内对所述图像进行行人识别，得到预设时段内各时刻各可服务栅格的行人数量；
    分别对预设时段内各可服务栅格的行人数量的平均值在预设时段内进行积分，得到各可服务栅格的行人热度。
  10. 一种***，包括：
    行人热度获取模块，配置为：
    获取待服务区域的图像，其中待服务区域包括通过对待服务区域进行栅格划分获得的可服务栅格，和
    对所述图像进行行人识别以获取预设时段内各可服务栅格的行人热度；以及
    待服务子区域标记模块，配置为将行人热度超过预设阈值的可服务栅格及以其为中心的预设范围内的可服务栅格标记为待服务栅格，得到由待服务栅格组成的待服务子区域。
  11. 如权利要求10所述的***，还包括：
    可服务栅格划分模块，配置为为多个服务机器人的每一个分配相应数量的可服务栅格，得到对应各服务机器人的服务区域；和
    确定模块，配置为判断待服务子区域与对应各服务机器人的服务区域的交集，将交集最大的服务机器人作为服务待服务子区域的服务机器人。
  12. 如权利要求11所述的***，其中，所述确定模块还配置为：
    生成服务机器人的服务路径。
  13. 如权利要求12所述的***，其中，可服务栅格划分模块被配置为为多个服务机器人的每一个分配等数量的可服务栅格。
  14. 如权利要求13所述的***，还包括：
    可服务栅格获取模块，配置为构建待服务区域地图，并对待服务区域地图进行等面积栅格划分，获取可服务栅格。
  15. 根据权利要求10-14所述的***，其中，所述待服务子区域标记模块，配置为将行人热度超过预设阈值的可服务栅格及以其为中心的预设范围内的可服务栅格标记为待 服务栅格，通过聚类方法将待服务栅格分组，根据各分组中的边缘栅格构成待服务子区域。
  16. 根据权利要求15所述的***，其中，所述待服务子区域标记模块进一步配置为通过以下方式来根据各分组中的边缘栅格构成待服务子区域：
    对于各分组，通过将该分组中的边缘栅格的中心连接线包裹的多边形区域覆盖的可服务栅格均作为该分组的待服务栅格，构成该分组的待服务子区域。
  17. 根据权利要求10-14中任一项所述的***，其中，所述确定模块，配置为在某个服务机器人作为执行服务至少两个待服务子区域的服务机器人时，通过遗传算法计算得到最优的服务机器人对于所述至少两个待服务子区域的服务顺序。
  18. 根据权利要求10-14所述的***，其中，所述行人热度获取模块，配置为在预设时段内对所述图像进行行人识别，得到预设时段内各时刻各可服务栅格的行人数量；分别对预设时段内各可服务栅格的行人数量的平均值在预设时段内进行积分，得到各可服务栅格的行人热度。
  19. 一种服务***，其中，包括多个服务机器人和如权利要求10-18中任一项所述的***。
  20. 一种计算机可读存储介质，其上存储有计算机程序，其中，该程序被处理器执行时实现如权利要求1-9中任一项所述的方法。
  21. 一种计算机***，包括：
    存储器，其上存储计算机程序；以及
    一个或多个处理器，配置为执行所述计算机程序来执行如权利要求1-9中任一项所述的方法。
  22. 一种服务机器人，包括：
    存储器，其上存储计算机程序指令；和
    处理器，其与存储器耦接并被配置为：
    接收该服务机器人的服务区域的可服务栅格的行人热度，可服务栅格是通过对服务区域进行栅格划分获得的，
    确定行人热度超过预设阈值的可服务栅格的数量，
    确定所述数量是否超过一阈值，以及
    当确定所述数量超过一阈值，使得服务机器人服务该服务区域。
  23. 如权利要求22所述的服务机器人，其中，可服务栅格是通过对服务区域进行等面积 栅格划分获得的。
  24. 一种服务机器人，包括：
    存储器，其上存储计算机程序指令；和
    处理器，其与存储器耦接并被配置为：
    接收多个待服务子区域的信息，其中所述多个待服务子区域是由行人热度超过预设阈值的可服务栅格组成的，可服务栅格是通过对包括所述多个待服务子区域的待服务区域进行栅格划分获得的，
    计算服务机器人的服务区域与所述多个服务子区域相交的栅格数，和
    将相交的栅格数最大的待服务子区域确定为该服务机器人的服务区域。
  25. 如权利要求24的服务机器人，其中，可服务栅格是通过对包括所述多个待服务子区域的待服务区域进行等面积栅格划分获得的。
  26. 如权利要求24或25的服务机器人，其中，处理器还配置为：
    将相交的栅格数超过阈值并且相交的栅格数最多的待服务子区域确定为该服务机器人的服务区域。
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