WO2022193762A1 - 用于控制搬运机器人的方法和设备 - Google Patents

用于控制搬运机器人的方法和设备 Download PDF

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Publication number
WO2022193762A1
WO2022193762A1 PCT/CN2021/139582 CN2021139582W WO2022193762A1 WO 2022193762 A1 WO2022193762 A1 WO 2022193762A1 CN 2021139582 W CN2021139582 W CN 2021139582W WO 2022193762 A1 WO2022193762 A1 WO 2022193762A1
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Prior art keywords
handling robot
scene
mode
work
operation mode
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PCT/CN2021/139582
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English (en)
French (fr)
Inventor
吕俊龙
梁璐
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灵动科技（北京）有限公司
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Priority claimed from CN202110305475.1A external-priority patent/CN115108231B/zh
Application filed by 灵动科技（北京）有限公司 filed Critical 灵动科技（北京）有限公司
Publication of WO2022193762A1 publication Critical patent/WO2022193762A1/zh

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
    • B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
    • B65G1/00—Storing articles, individually or in orderly arrangement, in warehouses or magazines
    • B65G1/02—Storage devices
    • B65G1/04—Storage devices mechanical
    • B65G1/137—Storage devices mechanical with arrangements or automatic control means for selecting which articles are to be removed
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
    • B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
    • B65G1/00—Storing articles, individually or in orderly arrangement, in warehouses or magazines
    • B65G1/02—Storage devices
    • B65G1/04—Storage devices mechanical
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
    • B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
    • B65G1/00—Storing articles, individually or in orderly arrangement, in warehouses or magazines
    • B65G1/02—Storage devices
    • B65G1/04—Storage devices mechanical
    • B65G1/137—Storage devices mechanical with arrangements or automatic control means for selecting which articles are to be removed
    • B65G1/1373—Storage devices mechanical with arrangements or automatic control means for selecting which articles are to be removed for fulfilling orders in warehouses
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders

Definitions

  • the present invention relates to a method for controlling a handling robot, a device for controlling a handling robot, a handling robot, a scheduling system and a computer program product.
  • a common picking method known in the prior art is “vehicle-to-person” or “goods-to-person”.
  • the AMR arrives at the predetermined storage location based on the content of the picking task. After the manual picker puts the designated goods on the AMR's cargo platform, the AMR transports the goods to the working platform.
  • the AMR completes the handling and transports the goods to the sorting workstation, where manual sorting is performed uniformly by human pickers.
  • the purpose of the present invention is to provide a method for controlling a handling robot, a device for controlling a handling robot, a handling robot, a scheduling system and a computer program product to at least solve the problems in the prior art. part of the problem.
  • a method for controlling a handling robot comprising the steps of:
  • S2 Match the operation mode of the handling robot to the scheduling task and/or work scene.
  • the present invention includes the following technical concepts:
  • the method according to the present invention can, for example, realize the optimal operation mode of the handling robot for different task types or task phases, so that the behavior of the handling robot can meet diverse application requirements.
  • the task completion quality and success rate of the handling robot are closely related to the work scene in which it is located.
  • the risk of damage to the handling robot in a specific scene can be especially reduced, thereby ensuring the safety of the entire solution. reliability.
  • the control strategy of the present invention improves the flexibility of the entire scheduling system, and enables the handling robot to adapt to complex and changeable task scenarios more intelligently.
  • the work scene includes a retail scene.
  • the step S2 includes: making the handling robot work according to the operation mode specified in the scheduling task and/or the work scene, and/or, determining the operation mode according to the task attribute of the scheduling task and/or the environmental attribute of the work scene, Make the transfer robot work according to the determined operation mode.
  • a predefined operating mode can be assigned to each scheduled task or work scenario, so that when a scheduled task is received or when a certain work scenario is reached, the specified operating mode can be directly operated, which advantageously reduces the computational cost.
  • the operation mode includes a switchable implementation of a first operation mode and a second operation mode, in which the handling robot is made to work autonomously, and in the second operation mode, the handling robot is made to work with the personnel. Work in a cooperative way.
  • the autonomous working mode of the handling robot is not suitable for all task stages or work scenarios, and often for tasks with more complex procedures or scenarios with many variables, work in coordination with personnel is adopted.
  • An approach may be advantageous, in which case, by flexibly switching between the first and second operation modes, the smoothness of the entire task process can be ensured, and an optimal balance between improving work efficiency and job completion is achieved.
  • the handling robot and the person are caused to move along a uniform trajectory, in particular in a man-to-car mode or a vehicle-to-people mode; and/or, in the second operating mode, the handling robot and the person are made to move separately.
  • Move along independent trajectories especially work according to the mode of finding a car near a person or finding a person near a car.
  • the man-carrying mode is understood to mean that the transport robot follows the man.
  • the car-to-people mode is understood to be guided by the handling robot.
  • the mode of people looking for a car nearby is understood as: the person goes to the nearest location where the handling robot is parked, and selects the corresponding product according to the task sub-task in the scheduling task of the handling robot. After completing the selection, the handling robot drives to the next position.
  • the mode of finding people near the car is understood as: the handling robot travels along a predefined path and stops at the nearest person on the predefined path.
  • the flexibility of the overall control scheme can be increased because the handling robot moves together with the person, instead of only one moving and the other fixing the position, as in existing picking strategies. After completing the corresponding task for one work location (such as a shelf), neither the personnel nor the handling robot need to stay in place, but allow both parties to move to the next work location, thus helping to avoid redundancy in personnel deployment.
  • the working scene includes an unmanned scene and a human-computer interaction scene.
  • the handling robot In the unmanned scene, the handling robot is switched to the first operation mode, and in the human-computer interaction scene, the handling robot is switched to the second operation. in mode.
  • a handling robot operating in autonomous mode can be advantageous, since in particular no human influences need to be taken into account during the path planning and the picking of goods, thus making it possible to To reduce the computational and time overhead to a certain extent.
  • a retail environment similar to a supermarket at least there are many uncertain factors in path planning, which puts forward higher requirements for the path planning and safety level of the handling robot. In this case, it is necessary to cooperate with or be supervised mode of operation is advantageous.
  • the step S2 includes: selecting the following operation modes of the handling robot in terms of goods picking according to the density of people or the flow of people in the work scene: picking-while-sorting mode or first-picking-then-sorting mode.
  • the first-to-sort mode can be preferentially selected. This saves the handling robot's dwell time in a specific area.
  • the sorting can be completed at the same time as picking, so as to save the cost of subsequent secondary sorting or packing.
  • the step S2 includes: generating a man-vehicle pairing result according to the number of personnel allocated for the scheduling task and/or work scene, and selecting the following operation modes of the handling robot based on the man-vehicle pairing result: one-person-one-vehicle mode, one-person-multiple vehicles mode or multiplayer multi-vehicle mode.
  • one-person-one-vehicle mode one-person-multiple vehicles mode or multiplayer multi-vehicle mode.
  • the step S2 includes: acquiring the characteristics of obstacles in the working scene of the handling robot, so that the operation mode of the handling robot matches the characteristics of the obstacles.
  • the following technical advantages are achieved: through the adaptation of the obstacle avoidance strategy and the characteristics of the obstacle, not only the damage caused by the handling robot to the obstacle is reduced, but also the movement trajectory or braking strategy can be planned more targetedly, reducing the The probability that the mission execution is interrupted by failure to avoid obstacles.
  • the handling robot when a stationary obstacle is involved, the handling robot is made to execute an active obstacle avoidance strategy, especially a 360° obstacle avoidance or low-profile obstacle avoidance strategy, and when a moving obstacle is involved, the handling robot is made to execute
  • the obstacle avoidance strategy of decelerating, especially decelerating until stopping, when the obstacle involves people determines the obstacle avoidance strategy of the handling robot according to the density of people and/or the height of the people. In this way, the collision risk between the handling robot and the obstacle can be rationally reduced, and the safety is improved.
  • the step S1 includes: creating an electronic map, especially a three-dimensional map, of the working scene of the handling robot based on the sensor data, wherein, especially for different working scenes, different types of information are marked in the electronic map and/or different types of information are marked in the electronic map. way to label information. This makes it possible to provide the handling robot with required information for the switched work scene, so that the handling robot can better adapt to the changed work scene.
  • the location of the commodity, the location of the unloading point, the location of the weighing area, the location of the packing point, the checkout location, the shelf location, the location of the charging pile and/or the location of the product are marked in the electronic map. channel location.
  • the corresponding relationship between the commodity and the shelf is marked in the electronic map.
  • the shelf positions are marked in the electronic map according to commodity categories and/or commodity sales attributes, wherein the commodity sales attributes especially include bulk sales and package sales. .
  • the following technical advantages are achieved: Unlike in the electronic map of conventional logistics manufacturing, which only needs to mark simple shelf numbers and passable areas, in retail environments such as supermarkets, it is necessary to take into account the goods before delivery.
  • the pre-processing process (such as weighing, packaging, scanning and settlement, etc.) before sale and the sale attributes of the product.
  • the handling robot can plan the path more efficiently and improve the time efficiency.
  • the step S2 includes: obtaining the repetition rate of goods and/or the correspondence between the goods and the picking positions in the orders included in the scheduling task, and selecting the following operation modes of the handling robot according to the repetition rate and/or correspondence of the goods : Combined operation mode or sequential operation mode.
  • the goods of the same category in the scheduling task are merged and/or the goods at the same picking position are merged, so that the handling robot works according to the merged scheduling task.
  • the sequential operation mode make the handling robot work in the order of the initial order in the scheduling task.
  • the distribution of the goods categories in the same batch of orders can be seen from the goods repetition rate, and for goods of the same category, the picking can be done in one and the same picking position in particular.
  • the distribution of the positions of the goods in the same batch of orders can be seen through the correspondence between the goods and the picking positions, and picking can be realized especially for the goods arranged in the same area.
  • the combined operation mode significantly reduces the situation that the transfer robot travels back and forth to the same picking area multiple times, and improves the work efficiency.
  • the handling robot can be directly operated in a sequential operation mode, thus saving data processing overhead.
  • the step S2 includes: acquiring a target usage scenario of an order included in the scheduling task, and selecting the following operation modes of the handling robot according to the target usage scenario: a partition operation mode or a classification operation mode.
  • Partial orders are efficiently merged using partition information in the scene, which allows for faster sorting of items in a specific partition.
  • an apparatus for controlling a handling robot the apparatus being used for performing the method according to the first aspect of the present invention, the apparatus comprising:
  • the communication unit is configured to be able to obtain the scheduling tasks and/or work scenarios of the handling robot;
  • processor being configured to be able to match the operation mode of the handling robot to the scheduled task and/or work scenario.
  • a handling robot comprising the apparatus according to the second aspect of the present invention.
  • a scheduling system comprising the device according to the second aspect of the present invention.
  • a computer program product comprising a computer program which, when executed by a computer, implements the method according to the first aspect of the present invention.
  • FIG. 1 shows a flowchart of a method for controlling a handling robot according to an exemplary embodiment of the present invention
  • Figure 2 shows a flow chart of one step of the method for controlling a handling robot according to the present invention
  • Figure 3 shows a flow chart of one step of the method for controlling a handling robot according to the present invention
  • FIG. 4 shows a block diagram of an apparatus for controlling a handling robot according to an exemplary embodiment of the present invention
  • FIG. 5 shows a schematic diagram of a handling robot according to an exemplary embodiment of the present invention.
  • FIG. 6 shows a block diagram of a scheduling system according to an exemplary embodiment of the present invention.
  • FIG. 1 shows a flowchart of a method for controlling a handling robot according to an exemplary embodiment of the present invention.
  • a scheduled task is acquired.
  • the scheduling task may include, for example, a picking work order, and the picking work order refers to a task list formed by the goods to be picked in a certain order.
  • step S12 the environmental sensor data of the work scene associated with the scheduled task is acquired.
  • Such environmental sensor data may be detected by lidar, radar, video sensors, ultrasonic sensors, and/or infrared sensors, among others.
  • an electronic map of the work scene is created based on the acquired sensor data.
  • Such an electronic map can in particular be a three-dimensional map with scene depth data and includes, for example, the following information: cargo location, charging point location, traversable area location, shelf location and sorting location.
  • the packing location, the unloading point location, the checkout location, and the weighing location can be marked in the electronic map in particular.
  • the electronic map can also be partitioned based on the sales attributes of commodities (bulk or packaged) and commodity categories (such as food, fresh food, daily necessities, etc.), and the shelf positions can be marked accordingly according to the partitions.
  • the cargo information contained in the scheduling task can be matched to the electronic map, so as to plan an optimal route for the handling robot by means of the electronic map in the subsequent task execution stage.
  • step S21 it is checked whether the scheduled tasks and/or work scenarios contain pre-stored operation modes.
  • predefined modes of operation may be recorded for at least part of an order or sub-order, specific task segments, task types and/or work scenarios.
  • step S22 the transfer robot is made to work directly according to the pre-stored operation mode.
  • the corresponding operation mode may be determined according to the attribute of the scheduled task and/or the environmental attribute of the work scene in step S23.
  • task attributes may include, for example, task type (eg, guiding, picking, packing, handling, displaying, etc.), task stage, task difficulty, task quantity, task location, and/or task scope.
  • the environmental attributes may include, for example, the type of work scene, the area of the work scene, the density of people, the characteristics of obstacles, and the like.
  • the transfer robot may be operated according to the determined operation mode in step S24.
  • step S25 is optionally also provided. For example, it can be determined in step S25 whether there is a state change of a scheduled task or a work scene.
  • step S26 the transfer robot is made to continue to work according to the current operation mode.
  • step S21 If a state change occurs, it is possible to return to step S21 to check again there whether updated operating mode information is stored for the current state change.
  • the handling robot has completed the first task phase or the first sorting area picking task, so it can be checked whether the operating mode needs to be adapted when switching from the first task phase to the second task phase, so that the The operation mode of the handling robot is dynamically adapted to the state change of the scheduling task.
  • Figure 2 shows a flowchart of one step of the method for controlling a handling robot according to the invention.
  • the method step S23 in FIG. 1 exemplarily includes sub-steps S201 - S210 to further illustrate how to influence the selection of the operation mode of the handling robot by scheduling tasks and/or work scenarios from the perspective of improving safety.
  • step S201 it is determined whether the working scene of the transport robot involves an unmanned scene.
  • an unmanned scenario is understood to be, for example, a scenario in which there is no or less human intervention in at least part of the working area or task phase of the handling robot.
  • unmanned scenarios may include spare parts factories in manufacturing, automated production workshops, smart logistics warehouses, and so on.
  • non-unmanned scenarios or human-computer interaction scenarios can include shopping malls, supermarkets, exhibitions, catering distribution stations and other occasions that have more contact with the public.
  • a first operation mode of the transfer robot in which the transfer robot is made to work autonomously may be selected in step S202. It should be noted here that the unmanned scene does not mean that the entire operating environment of the handling robot is completely free of human activities. Some operating areas involve unmanned scenarios.
  • the second operation mode of the transfer robot is selected in step S203. In this second operating mode, the handling robot is made to work in cooperation with the person.
  • obstacles in the surrounding environment of the handling robot are detected in step S204.
  • step S205 it is determined whether a static obstacle is involved.
  • Static obstacles can be, for example, goods, tools, outer packaging, shelves, etc. located in the moving path of the handling robot.
  • Dynamic obstacles can be other handling robots, pickers and customers, for example.
  • step S206 the handling robot is made to execute an active obstacle avoidance strategy.
  • a detour path can be calculated for a handling robot to avoid obstacles based on 360° environment perception technology.
  • the handling robot can be made to perform low obstacle avoidance or leap obstacle avoidance based on the special structure or contour of the static obstacle.
  • the transfer robot is made to perform deceleration and obstacle avoidance in step S207.
  • the handling robot can be made to decelerate to zero for a short period of time and wait for the obstacle to leave.
  • a detour route can also be planned for the handling robot to avoid stagnant crowds.
  • step S208 the density of people in the vicinity of a specific work area (for example, a picking rack) may also be detected. If there are many people gathered near the target rack, the operation mode of "pick first and then sort" of the transfer robot can be selected in step S209, so as to reduce the working time at this position, so as to avoid, for example, when the transfer robot performs the picking task Affect the shopping experience of customers.
  • a specific work area for example, a picking rack
  • the operation mode of "picking while sorting" may be selected in step S210, so as to save the cost of subsequent sorting or packing.
  • a person-vehicle pairing result based on the number of pickers allocated for the dispatch task and/or the work scene associated with the dispatch task, and use the person-vehicle pairing result Select one of the following operating modes: one-person-one-car mode, one-person multi-car mode, or multi-person multi-car mode.
  • the handling robot can independently plan the route and let the picker follow the handling robot, thus eliminating the need for the person to calculate the route by himself. Or the error-prone link of sending routes to people through dispatch centers.
  • it can also be considered to make the handling robot follow the person to move according to a predetermined trajectory. This operation mode is especially advantageous when the goods in the scheduling task are scattered, the path planning is complex, or there are many variable factors in the work scene.
  • the handling robot and the personnel can be moved along independent trajectories, and according to the personnel The nearest car mode and/or the car nearest man mode to dispatch handling robots and personnel accordingly.
  • Figure 3 shows a flow chart of one step of the method for controlling a handling robot according to the invention.
  • the method step S23 in FIG. 1 exemplarily includes sub-steps S211 - S219 , in order to further illustrate how to influence the selection of the operation mode of the handling robot by scheduling tasks and work scenarios from the perspective of improving work efficiency.
  • step S211 the repetition rate of goods in each order included in the scheduling task is obtained.
  • step S212 the correspondence between the goods included in the scheduling task and the picking positions is acquired.
  • the location distribution of the goods included in the scheduling task in the electronic map can be obtained.
  • step S213 it is determined whether the repetition rate of the goods or the unevenness of the position distribution of the goods in the electronic map is lower than a threshold.
  • a threshold As an example, other metrics can also be set to arrive at the best solution taking into account cargo duplication rates or location distribution.
  • the handling robot can be made to perform the sequential operation mode in step S215. In the sequential operation mode, make the handling robot work in the order of the initial order in the scheduling task.
  • step S214 the goods of the corresponding category or the orders of the corresponding area may be merged to execute the merge operation mode.
  • the target usage scenario of the order included in the scheduling task may also be acquired in step S216 and judged in step S217 whether the target usage scenario involves a shopping mall or a supermarket.
  • the partition mode of operation may be performed in step S218.
  • all initial orders can be dismantled and scrambled first, and some orders can be effectively merged based on the partition information of the goods in the target usage scenario, so that the sorting of goods in a specific partition of the target scenario can be completed more quickly.
  • the class-by-class operation mode may be performed in step S219. For example, items of the same category can be sorted first, thereby reducing the number of repeated trips to the picking area.
  • FIG. 4 shows a block diagram of an apparatus for controlling a handling robot according to an exemplary embodiment of the present invention.
  • the device 1 comprises a communication unit 10 and a processor 20 which are communicatively coupled to each other.
  • the communication unit 10 is configured to be able to acquire scheduling tasks and/or work scenarios of the handling robot.
  • the processor 20 is configured to be able to match the operation mode of the handling robot to the scheduled task and/or work scenario.
  • the processor includes, for example, an analysis and processing module 21, a storage module 22, and a control module 23.
  • the analysis and processing module 21 extracts the task attribute of the scheduled task and the environmental attribute of the work scene and associates them with the corresponding operation mode. These operations Patterns may be predefined and stored in the storage module 22, for example.
  • the control module 23 can control the various actuators of the transport robot (eg, travel mechanism, transport mechanism, display mechanism, etc.) according to the operation mode.
  • FIG. 5 shows a schematic diagram of a handling robot according to an exemplary embodiment of the present invention.
  • a handling robot 100 is shown on the left in FIG. 5 , which includes the device 1 in FIG. 4 .
  • the transfer robot 100 further includes, for example, a display screen 110 , a path planning mechanism 120 and a tracking mechanism 130 .
  • the control module 23 (not shown) in the device 1 can send trigger signals to the respective actuators 110, 120, 130 of the handling robot 100 to activate or deactivate the corresponding functions .
  • the device 1 controls the route planning mechanism 120 to be switched on. If it is determined with the aid of the device 1 that the robot 100 should follow the picker to the target position, the device 1 controls the tracking mechanism 130 to be turned on so as to calculate the relative distance and bearing based on the interaction with the communication unit worn by the person, so as to achieve the purpose of intelligent following.
  • the display contents 111 , 112 of the display screen 110 can also be controlled by means of the operating mode determined by the device 1 .
  • the display contents 111, 112 of the display screen 110 of the handling robot 100 are shown on the right side of Fig. 5 for two different operating modes. If the picking mode of the handling robot 100 for assisting the personnel is determined by means of the device 1 , a content 111 can be displayed in the display screen 110 , in which, for example, the status of the goods in the corresponding order in the scheduling task can be displayed, so that the picker can After the picking is completed, click Confirm, perform out-of-stock registration, etc.
  • a content 112 can be displayed on the display screen 110 , where the customer can query the product, for example by providing the corresponding shelf number or shelf area. If the customer clicks on the demand that needs to be guided on the display screen 110, the handling robot can also guide the customer to inquire about the location of the product.
  • FIG. 6 shows a block diagram of a scheduling system according to an exemplary embodiment of the present invention.
  • the scheduling system 300 includes the device 1 in FIG. 4 .
  • the dispatch system 300 is arranged in a warehouse and is used to dispatch dispatch tasks and dispatch instructions to the handling robots 101, 102 and pickers 200 in the warehouse.
  • a goods placement area 600 including a plurality of shelves 601 , 602 is also arranged in the warehouse.
  • the plurality of handling robots 101 , 102 and the personnel 200 move in the warehouse according to appropriate trajectories, respectively.
  • the dispatching system 300 generates a human-vehicle pairing result according to the number of personnel and the number of handling robots allocated to the current warehouse, and, for example, determines a "one-person-multiple-vehicle" mode here.
  • the picker 200 moves along a designated route within a predetermined area, and multiple handling robots 101 and 102 are dispatched to multiple locations to be picked.
  • the picker 200 goes to the nearest docked handling robot. position, and select the corresponding goods according to the scheduling task of the handling robot.
  • the transfer robot drives to the next picking position, while the picker 200 goes to the next closest position where the transfer robot is parked or ends the picking.
  • the implementation of this "one person, multiple vehicles" mode is exemplarily shown, wherein the picker 200 moves in the warehouse, for example, in a counterclockwise direction.
  • the picker 200 comes to the rack 602 where the transfer robot 101 is parked to pick.
  • the handling robots 101 and 102 move according to the trajectories specified by the scheduling task, respectively, and the picker 200 continues to move counterclockwise. Therefore, at the moment shown on the right side of FIG.
  • the transfer robot 101 has left the area near the picker 200 , and at the same time, the transfer robot 102 is "closest" to the picker 200 at the current moment, so the picker 200 goes to the transfer robot 102 Picking is performed at the docked rack 601 .
  • the operation mode of "one person with multiple vehicles” or “multiple people with multiple vehicles” can also be implemented accordingly.

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Abstract

本发明涉及智能物流领域。本发明提供一种用于控制搬运机器人的方法，所述方法包括以下步骤：S1：获取搬运机器人的调度任务和/或工作场景；以及S2：使搬运机器人的操作模式匹配于所述调度任务和/或工作场景。本发明还提供一种用于控制搬运机器人的设备、一种搬运机器人、一种调度系统和一种计算机程序产品。本发明的控制策略使搬运机器人更智能地适应复杂多变的任务条件，有利地提高了整个调度系统的柔性，尤其能够满足在商超零售场景中的多元化应用需求。

Description

用于控制搬运机器人的方法和设备 技术领域
本发明涉及一种用于控制搬运机器人的方法、一种用于控制搬运机器人的设备、一种搬运机器人、一种调度系统和一种计算机程序产品。
背景技术
随着电子商务、现代化工厂等领域的兴起，越来越多地使用智能化仓储系统来完成物品的拣选、搬运、存储等。目前在智能仓储物流领域，为了减轻人工拣选员的负担并提高拣选作业效率，一般通过自主移动机器人(英：AMR，Automated Mobile Robot)与人的协作来完成物料的拣选与播种。
现有技术中已知的常见拣选方式为“车到人”或“货到人”。在“车到人”的拣选模式中，AMR基于拣货任务内容到达预定仓储点位，在人工拣选员将指定货物放入AMR的货物平台后，再由AMR将货物运至工作平台。在“货到人”的拣选模式中，由AMR完成搬运作业并将货物运送至分拣工作站，在那里由人工拣选员统一进行手工分拣。
然而，这些方案均存在诸多局限性。特别是，上述拣选方案均无法根据环境条件或任务状态动态地调整操作模式，使得无法顺应和适配实时变化的操作环境。此外，在常规拣选模式中大多需要在特定拣选位置或分拣站固定部署人力，这导致整个分拣系统的柔性较差，在某些情况下甚至意味着更高的时间成本和劳动力资源浪费。因此，尤其对于无法实现无人化管理的商超零售场景来说，目前采用的上述AMR控制方案仍无法应对人流量大、货物零散、场景复杂、安全要求高的需求。
发明内容
本发明的目的在于提供一种用于控制搬运机器人的方法、一种用于控制搬运机器人的设备、一种搬运机器人、一种调度系统和一种计算机程序 产品，以至少解决现有技术中的部分问题。
根据本发明的第一方面，提供一种用于控制搬运机器人的方法，所述方法包括以下步骤：
S1：获取搬运机器人的调度任务和/或工作场景；以及
S2：使搬运机器人的操作模式匹配于所述调度任务和/或工作场景。
本发明尤其包括以下技术构思：一方面，根据本发明的方法例如能够分别针对不同任务类型或任务阶段实现搬运机器人的最佳操作模式，从而使搬运机器人的行为满足多样化的应用需求。另一方面，搬运机器人的任务完成质量及成功率与其所在的工作场景紧密关联，通过根据工作场景动态切换操作模式尤其能够减小搬运机器人在特定场景下的受损风险，从而确保了整个方案的可靠性。相比于始终以单一操作模式应对所有变换条件的传统AMR，本发明的控制策略提高了整个调度系统的柔性，使搬运机器人更智能地适应复杂多变的任务场景。
可选地，所述工作场景包括零售场景。
可选地，所述步骤S2包括：使搬运机器人按照调度任务和/或工作场景中指定的操作模式工作，和/或，根据调度任务的任务属性和/或工作场景的环境属性确定操作模式，使搬运机器人按照所确定的操作模式工作。
在此尤其实现以下技术优点：可以为每个调度任务或工作场景分配预定义的操作模式，从而在接收到调度任务时或到达确定工作场景时即可直接按照规定的操作模式工作，有利地降低了计算开销。通过根据任务属性或环境属性确定操作模式，可以使搬运机器人的操作模式更精确地匹配于动态变化的任务要求，提高了整个方案的灵活性。
可选地，所述操作模式包括可切换实施的第一操作模式和第二操作模式，在第一操作模式中，使搬运机器人自主地工作，在第二操作模式中，使搬运机器人以与人员配合的方式工作。
在此，尤其实现以下技术优点：并非对于所有任务阶段或工作场景都适用搬运机器人的自主工作模式，往往对于工序较复杂的任务或可变因素较多的场景而言，采取与人员配合的工作方式会是有利的，在这种情况下，通过在第一和第二操作模式之间灵活切换可以确保整个任务进程的流畅性，在提高工作效率与作业完成度之间达到了最佳平衡。
可选地，在第二操作模式中使搬运机器人与人员一起沿统一轨迹运动、尤其按照人带车模式或车带人模式工作；和/或，在第二操作模式中使搬运机器人与人员分别沿独立轨迹运动、尤其按照人就近找车模式或车就近找人模式工作。
在此，人带车模式理解为搬运机器人跟随人员行进。车带人模式理解为由搬运机器人引导人员行进。人就近找车模式理解为：人员前往最近的、停靠有搬运机器人的位置，并按照该搬运机器人的调度任务中的任务子拣选对应商品，完成拣选后该搬运机器人驶向下一位置，人员沿着预定义路径行进并前往下一个最近的、停靠有搬运机器人的位置。车就近找人模式则理解为：搬运机器人沿预定义路径行驶并停靠该预定义路径上的最近人员处。
在此尤其实现以下技术优点：由于搬运机器人与人员共同运动，而不是如现有拣选策略中那样只有一方运动，而另一方固定位置，因此可以提高整个控制方案的灵活性。当针对一个工作位置(例如货架)完成相应任务之后，人员和搬运机器人都不必滞留在原地，而是允许双方都可以向下一工作位置前进，从而有利避免出现人员部署方面的冗余。
可选地，所述工作场景包括无人化场景和人机交互场景，在无人化场景中使搬运机器人切换到第一操作模式中，在人机交互场景中使搬运机器人切换到第二操作模式中。
在此，尤其实现以下技术优点：在无人化场景中，基于自主模式工作的搬运机器人会是有利的，因为在路径规划和货物拣运时尤其不需要考虑人为影响因素，由此可以在一定程度上减少计算和时间开销。在类似于商超零售环境中，至少在路径规划方面存在较多不确定因素，由此对于搬运机器人的路径规划以及安全等级提出更高要求，在这种情况下，与人协作或受人监督的操作模式是有利的。
此外，还可以在切换操作模式时将搬运机器人自身传感器的可靠性、搬运机器人的等级型号等因素考虑在内。
可选地，所述步骤S2包括：根据工作场景中的人员密度或人流量，在货物拣选方面选择搬运机器人的以下操作模式：边拣边分模式或先拣后分模式。
在此，尤其实现以下技术优点：当环境中的人员密度或人流量较大时，为了使工作场景中的顾客尽可能少地受到搬运机器人作业的干扰，可以优先选择先拣后分模式，由此可以节省搬运机器人在特定区域的停留时间。当环境中只有较少人员时，可以在拣货的同时就完成分装，以便节省后续的二次分拣或打包开销。
可选地，所述步骤S2包括：根据为调度任务和/或工作场景分配的人员数量生成人车配对结果，基于人车配对结果选择搬运机器人的以下操作模式：一人一车模式、一人多车模式或多人多车模式。在此，通过基于人车配对比例选择操作模式，能够实现工作效率最大化。
可选地，所述步骤S2包括：获取搬运机器人的工作场景中的障碍物特性，使搬运机器人的操作模式匹配于所述障碍物特性。
在此尤其实现以下技术优点：通过避障策略与障碍物特性的适配性，不仅降低了搬运机器人对障碍物造成的伤害，同时能够更有针对性地规划运动轨迹或制动策略，降低了避障失败造成任务执行中断的概率。
尤其其中，在涉及静止障碍物的情况下，使搬运机器人针对静止障碍物执行主动避障策略、尤其360°避障或低矮避障策略，在涉及移动障碍物的情况下，使搬运机器人执行减速、尤其减速直至停止的避障策略，在障碍物涉及人员的情况下，根据人员密度和/或人员身高确定搬运机器人的避障策略。由此可以合理化降低搬运机器人与障碍物的碰撞风险，提高了安全性。
可选地，所述步骤S1包括：基于传感器数据创建搬运机器人的工作场景的电子地图、尤其三维地图，其中，尤其针对不同的工作场景，在电子地图中标注不同类型的信息和/或以不同方式标注信息。由此使得能够针对切换的工作场景为搬运机器人提供所需的信息，从而使搬运机器人更好地适应于变化的工作场景。
可选地，在所述工作场景是零售场景的情况下，在电子地图中标注出商品位置、卸载点位置、称重区位置、打包点位置、结账位置、货架位置、充电桩位置和/或通道位置。
可选地，在所述工作场景是零售场景的情况下，在电子地图中标注出商品与货架的对应关系。
可选地，在所述工作场景是零售场景的情况下，在电子地图中按照商品类别和/或商品贩卖属性分区地标注货架位置，其中，所述商品贩卖属性尤其包括散装销售和整装销售。
在此，尤其实现以下技术优点：不同于在常规物流制造业的电子地图中只需标注出简单的货架编号和可通行区域，在商超等零售环境中尤其还需要在交付商品之前考虑到商品出售前的预处理流程(例如称重、打包、扫码结算等)以及商品的贩卖属性。通过在电子地图中标注这些特殊信息，能够使搬运机器人更高效地规划路径，提高时间效率。
可选地，所述步骤S2包括：获取调度任务包含的订单中的货物重复率和/或货物与拣选位置的对应关系，根据所述货物重复率和/或对应关系选择搬运机器人的以下操作模式：合并操作模式或按序操作模式。
在合并操作模式中，例如对调度任务中的相同类别的货物进行合并和/或对相同拣选位置处的货物进行合并，使搬运机器人按照合并后的调度任务工作。在按序操作模式中，使搬运机器人按照调度任务中的初始订单顺序工作。
在此，尤其实现以下技术优点：通过货物重复率可以看出同一批次订单中的货物类别分布，对于同一类别的货物，尤其可以在同一拣选位置一次性完成拣选。此外，通过货物与拣选位置的对应关系可以看出同一批次订单中的货物位置分布情况，对于布置在同一区域的货物尤其可以一起实现拣选。由此，以合并的操作方式显著降低了搬运机器人多次往返于同一拣选区域的情况，提高了工作效率。另一方面，如果订单中的货物重复率较低或位置部分较均匀，则可以使搬运机器人直接以按序操作模式工作，从而节省了数据处理开销。
可选地，所述步骤S2包括：获取调度任务包含的订单的目标使用场景，根据所述目标使用场景选择搬运机器人的以下操作模式：分区操作模式或分类操作模式。
在此，尤其实现以下技术优点：视货物的目标使用场景而定，按照原始订单顺序并不能够实现效率最大化，在特殊情况下，可以先将所有订单拆散并打乱，并基于货物在目标使用场景中的分区信息有效合并部分订单，由此可以更快速地完成特定分区中的商品分拣。
根据本发明的第二方面，提供一种用于控制搬运机器人的设备，所述设备用于执行根据本发明的第一方面所述的方法，所述设备包括：
通信单元，所述通信单元配置成能够获取搬运机器人的调度任务和/或工作场景；以及
处理器，所述处理器配置成能够使搬运机器人的操作模式匹配于所述调度任务和/或工作场景。
根据本发明的第三方面，提供一种搬运机器人，所述搬运机器人包括根据本发明的第二方面所述的设备。
根据本发明的第四方面，提供一种调度系统，所述调度系统包括根据本发明的第二方面所述的设备。
根据本发明的第五方面，提供一种计算机程序产品，其包括计算机程序，所述计算机程序在计算机执行时实施根据本发明的第一方面所述的方法。
附图说明
下面，通过参看附图更详细地描述本发明，可以更好地理解本发明的原理、特点和优点。附图包括：
图1示出了根据本发明的一个示例性实施例的用于控制搬运机器人的方法的流程图；
图2示出了根据本发明的用于控制搬运机器人的方法的一个步骤的流程图；
图3示出了根据本发明的用于控制搬运机器人的方法的一个步骤的流程图；
图4示出了根据本发明的一个示例性实施例的用于控制搬运机器人的设备的框图；
图5示出了根据本发明的一个示例性实施例的搬运机器人的示意图；以及
图6示出了根据本发明的一个示例性实施例的调度系统的框图。
具体实施方式
为了使本发明所要解决的技术问题、技术方案以及有益的技术效果更加清楚明白，以下将结合附图以及多个示例性实施例对本发明进行进一步详细说明。应当理解，此处所描述的具体实施例仅用于解释本发明，而不是用于限定本发明的保护范围。
图1示出了根据本发明的一个示例性实施例的用于控制搬运机器人的方法的流程图。
在步骤S11中，获取调度任务。在此，调度任务例如可以包括拣选工单，拣选工单是指待拣选货物按照一定顺序形成的任务单。
在步骤S12中，获取与调度任务关联的工作场景的环境传感器数据。这种环境传感器数据可以由激光雷达、雷达、视频传感器、超声传感器和/或红外传感器等检测。
在步骤S13中，基于所获取的传感器数据创建工作场景的电子地图。这种电子地图尤其可以是带有场景深度数据的三维地图并且例如包括以下信息：货物位置、充电桩位置、可通行区域位置、货架位置和分拣位置。在工作场景涉及零售商超场景的情况下，尤其还可以在电子地图中标注出打包位置、卸载点位置、结账位置、称重位置。同时，在零售商超场景下，尤其还可以基于商品贩卖属性(散装或整装)和商品类别(例如食品、生鲜、日用品等)对电子地图进行分区，并根据分区相应地标注出货架位置。在此，例如可以将调度任务中包含的货物信息匹配到电子地图中，以便在后续的任务执行阶段借助电子地图为搬运机器人规划最优路线。
在步骤S21中，检查调度任务和/或工作场景中是否包含预存操作模式。作为示例，可以针对至少部分订单或子订单、特定任务环节、任务类型和/或工作场景记录了预定义的操作模式。
如果存在预存操作模式可用，则在步骤S22中使搬运机器人直接按照预存操作模式工作。
如果调度任务或工作场景中未规定操作模式，则可以在步骤S23中根据调度任务的属性和/或工作场景的环境属性确定相应的操作模式。在此，任务属性例如可以包括：任务类型(例如引导、拣选、分装、搬运、展示等)、任务阶段、任务难易程度、任务数量、任务位置和/或任务涉及范围。环境属性例如可以包括：工作场景类型、工作场景面积、人员密度、障碍 物特性等。
在确定了操作模式之后，可以在步骤S24中使搬运机器人按照所确定的操作模式工作。
接下来，可选地还设置步骤S25。例如可以在步骤S25中判断：是否存在调度任务或工作场景的状态变化。
如果判断得出未发生状态变化，则在步骤S26中使搬运机器人继续按照当前的操作模式工作。
如果出现状态变化，则可以重新返回到步骤S21，以便在那里再次检查是否针对当前状态变化存储有更新的操作模式信息。例如搬运机器人已经完成了第一任务阶段或第一分拣区域的拣选任务，由此可以检查当从第一任务阶段转换到第二任务阶段时，是否需要对操作模式进行适应性调整，从而使搬运机器人的操作模式动态适配于调度任务的状态变化。
图2示出了根据本发明的用于控制搬运机器人的方法的一个步骤的流程图。
如图2所示，图1中的方法步骤S23示例性地包括子步骤S201-S210，以便进一步从提高安全性角度阐述如何通过调度任务和/或工作场景影响搬运机器人的操作模式的选择。
在步骤S201中，判断搬运机器人的工作场景是否涉及无人化场景。在此，无人化场景例如理解为如下场景：在该场景中，搬运机器人的至少部分作业区域或任务阶段不存在或较少地存在人为干预因素。作为示例，无人化场景可以包括制造业的零配件工厂、自动化生产车间、智能物流仓库等。与此相反，非无人化场景或者说人机交互场景可以包括商场、超市、展会、餐饮配送站等与公众存在较多接触的场合。
如果判断得出涉及无人化场景，则意味着存在较少干扰因素和较低的安全等级需求。在这种情况下，可以在步骤S202中选择搬运机器人的第一操作模式，在这种操作模式中，使搬运机器人自主地工作。在此应注意的是，无人化场景并不代表搬运机器人的整个作业环境都完全没有人类活动，还可能的是，在搬运机器人的诸如“拣货”、“分装”等部分作业阶段或部分作业区域涉及无人化场景。
如果判断得出涉及人机交互场景，则意味着存在较多干扰因素并且对 安全等级的需求较高。在这种情况下，在步骤S203中选择搬运机器人的第二操作模式。在该第二操作模式中，使搬运机器人以与人员配合的方式工作。
可选地，在步骤S204中检测搬运机器人的周围环境中的障碍物。
在步骤S205中判断是否涉及静态障碍物。静态障碍物例如可以是位于搬运机器人的运动路径中的货物、工具、外包装和货架等。动态障碍物例如可以是其他的搬运机器人、拣货员和顾客等。
如果涉及静态障碍物，则在步骤S206中使搬运机器人执行主动避障策略。作为示例，可以基于360°环境感知技术为搬运机器人计算绕行路径，以避开障碍物。作为另一示例，可以基于静态障碍物的特殊结构或轮廓使搬运机器人执行低矮避障或跨越避障。
如果涉及动态障碍物，则在步骤S207中使搬运机器人执行减速避障。作为示例，如果检测到障碍物以较快速度移动(例如大于速度阈值)，则可以使搬运机器人在短时间内减速到零并等待障碍物离开。作为另一示例，还可以进一步判断障碍物是否涉及人员。如果障碍物是人，则可以在人流密度大于一定阈值或身高低于一定阈值时使搬运机器人减速到零，由此可以有针对性地避免大规模人群或儿童受到碰撞伤害。此外，在人流密度大于一定阈值时且速度低于速度阈值时，也可以为搬运机器人规划绕行路线，以避开停滞人群。
可选地，还可以在步骤S208中检测特定作业区域(例如拣选货架)附近的人员密度。如果目标货架附近有较多人员聚集，则可以在步骤S209中选择搬运机器人的“先拣后分”的操作模式，以便减少在该位置处的作业时间，从而例如避免搬运机器人在执行拣选任务时影响顾客的购物体验。
如果目标货架处没有或只有较少人员停留，则可以在步骤S210中选择“边拣边分”的操作模式，以便节省后续的分装或打包开销。
除了将工作场景中的人员密度考虑在内，还能够想到的是，根据为调度任务和/或与调度任务关联的工作场景分配的拣货员数量生成人车配对结果，并且借助人车配对结果选择以下操作模式：一人一车模式、一人多车模式或多人多车模式。
此外，例如取决于工作场景的复杂度，还可以决定：是使搬运机器人 与人员沿统一轨迹运动还是使搬运机器人与人员分别沿独立轨迹运动。在搬运机器人与人员沿统一轨迹运动的情况下，如果拣选员的经验不足或对工作场景不够熟悉，则可以考虑由搬运机器人自主规划路线并且使拣选员跟随搬运机器人，从而省去人员自行计算路线或通过调度中心向人员发送路线的易出错环节。此外，还可以考虑使搬运机器人跟随人员按照预定轨迹运动，这种操作模式尤其在调度任务中的货物较分散、路径规划复杂或工作场景中可变因素较多的情况下是有利的。
如果与调度任务关联的工作场景面积较大或者说调度任务包含的货物数量较多，则为了实现更高的灵活性和更高效率，可以使搬运机器人与人员各自沿独立轨迹运动，并且按照人就近找车模式和/或车就近找人模式来相应地调度搬运机器人和人员。
图3示出了根据本发明的用于控制搬运机器人的方法的一个步骤的流程图。
如图3所示，图1中的方法步骤S23示例性地包括子步骤S211-S219，以便进一步从提高工作效率角度阐述如何通过调度任务和工作场景影响搬运机器人的操作模式的选择。
在步骤S211中，获取调度任务所包含的各个订单中的货物重复率。
在步骤S212中，获取调度任务中包含的货物与拣选位置的对应关系。作为示例，可以获取调度任务中包含的货物在电子地图中的位置分布。
接下来，在步骤S213中，判断货物重复率或货物在电子地图中的位置分布不均匀性是否低于阈值。作为示例，也可以设置其他衡量标准，从而在综合考虑货物重复率或位置分布的情况下得出最佳解决方案。
如果判断得出货物重复率较低或货物位置分布较为均匀，则对初始订单重新组合和排序会是没有意义的，因此在这种情况下可以在步骤S215中使搬运机器人执行按序操作模式。在按序操作模式中，使搬运机器人按照调度任务中的初始订单顺序工作。
反之，则可以在步骤S214中将相应类别的货物或者相应区域的订单合并，以执行合并操作模式。
附加地，还可以在步骤S216中获取调度任务中包含的订单的目标使用场景并在步骤S217中判断该目标使用场景是否涉及商场或超市。
如果是这种情况，则可以在步骤S218中执行分区操作模式。在此，例如可以先将所有初始订单拆散并打乱，并基于货物在目标使用场景中的分区信息有效合并部分订单，由此可以更快地完成目标场景的特定分区中的商品分拣。
如果不是这种情况，则可以在步骤S219中执行按类操作模式。例如，可以先对同一类别的货物进行分拣，由此减少在拣选区域的重复往返次数。
图4示出了根据本发明的一个示例性实施例的用于控制搬运机器人的设备的框图。
设备1包括在通信技术上彼此耦合的通信单元10和处理器20。
通信单元10配置成能够获取搬运机器人的调度任务和/或工作场景。
处理器20配置成能够使搬运机器人的操作模式匹配于所述调度任务和/或工作场景。
作为示例，处理器例如包括分析处理模块21、存储模块22和控制模块23，分析处理模块21对调度任务的任务属性以及工作场景的环境属性进行提取并将其关联到相应的操作模式，这些操作模式例如可以被预定义并且存储在存储模块22中。接下来，可以由控制模块23按照该操作模式控制搬运机器人的各个执行机构(例如行驶机构、搬运机构、显示机构等)。
图5示出了根据本发明的一个示例性实施例的搬运机器人的示意图。
在图5左侧示出搬运机器人100，其包括图4中的设备1。此外，搬运机器人100例如还包括显示屏110、路径规划机构120和跟踪机构130。在通过设备1确定了搬运机器人100的操作模式之后，设备1中的控制模块23(未示出)可以向搬运机器人100的各个执行机构110、120、130发出触发信号，以便激活或禁用相应功能。
例如，如果借助设备1确定应当使搬运机器人100自主完成路线规划，则设备1控制路线规划机构120开启。如果借助设备1确定应当使机器人100跟随拣选员到达目标位置，则设备1控制跟踪机构130开启，以便基于与人员佩戴的通信单元的交互计算出相对距离和方位，从而达到智能跟随目的。
此外，还可以借助设备1确定的操作模式来控制显示屏110的显示内容111、112。在图5右侧针对两种不同的操作模式示出搬运机器人100的 显示屏110的显示内容111、112。如果借助设备1确定搬运机器人100的用于辅助人员的拣选模式，则可以在显示屏110中示出内容111，其中例如可以显示调度任务中的相应订单中的货物状态，由此可以供拣选员在拣选完成后点击确认、进行缺货登记等。如果借助设备1确定搬运机器人100的顾客展示模式，则可以在显示屏110中示出内容112，在此可供顾客对商品进行查询，为此例如可以提供相应的货架编号或货架所在区域。如果顾客在显示屏110上点击了需要引导的需求，则搬运机器人还可以引导顾客前往查询商品位置。
图6示出了根据本发明的一个示例性实施例的调度系统的框图。
如图6左侧所示，调度系统300包括图4中的设备1。示例性地，调度系统300布置在仓库中并且用于向仓库中的搬运机器人101、102和拣货员200派发调度任务和调度指令。在仓库中还布置有包括多个货架601、602的货物摆放区600。在调度系统300的调度下，多个搬运机器人101、102和人员200分别按照适当轨迹在仓库中运动。
作为示例，调度系统300根据为当前仓库分配的人员数量和搬运机器人数量生成人车配对结果，并例如在此确定“一人多车”模式。在该模式中，拣选员200在预定区域内沿指定线路运动，多个搬运机器人101、102被调度前往多个待拣选位置，在沿指定线路行驶途中，拣选员200前往最近的停靠有搬运机器人的位置，并按照该搬运机器人的调度任务拣选对应货物。在完成拣选后，该搬运机器人驶向下一拣选位置，同时拣选员200前往下一个最近的、停靠有搬运机器人的位置或结束拣选。
结合图6示例性地示出了这种“一人多车”模式的执行方式，其中，拣选员200在仓库中例如沿逆时针运动。在图6左侧所示时刻，拣选员200来到搬运机器人101停靠的货架602处进行拣选。在完成拣选之后，搬运机器人101和102分别按照调度任务指定轨迹运动，并且拣选员200继续沿逆时针运动。于是在图6右侧所示时刻，搬运机器人101已离开拣选员200附近区域，同时就当前时刻而言，搬运机器人102相对于拣选员200是“最近的”，因此拣选员200前往搬运机器人102停靠的货架601处进行拣选。
根据其他人车配对结果，也可以相应地执行“一人多车”或“多人多 车”的操作模式。此外，也可以根据需要使搬运机器人按照特定轨迹运动，并且由搬运机器人在行驶过程中主动寻找拣选员。
尽管这里详细描述了本发明的特定实施方式，但它们仅仅是为了解释的目的而给出的，而不应认为它们对本发明的范围构成限制。在不脱离本发明精神和范围的前提下，各种替换、变更和改造可被构想出来。

Claims (19)

  1. 一种用于控制搬运机器人(100)的方法，所述方法包括以下步骤：
    S1：获取搬运机器人(100)的调度任务和/或工作场景；以及
    S2：使搬运机器人(100)的操作模式匹配于所述调度任务和/或工作场景。
  2. 根据权利要求1所述的方法，其中，所述工作场景包括零售场景。
  3. 根据权利要求1所述的方法，其中，所述步骤S2包括：使搬运机器人(100)按照调度任务和/或工作场景中指定的操作模式工作，和/或，根据调度任务的任务属性和/或工作场景的环境属性确定操作模式，使搬运机器人(100)按照所确定的操作模式工作。
  4. 根据权利要求1至3中任一项所述的方法，其中，所述操作模式包括可切换实施的第一操作模式和第二操作模式，在第一操作模式中，使搬运机器人(100)自主地工作，在第二操作模式中，使搬运机器人(100)以与人员(200)配合的方式工作。
  5. 根据权利要求4所述的方法，其中，在第二操作模式中使搬运机器人(100)与人员(200)一起沿统一轨迹运动、尤其按照人带车模式或车带人模式工作；和/或，在第二操作模式中使搬运机器人(100)与人员(200)分别沿独立轨迹运动、尤其按照人就近找车模式或车就近找人模式工作。
  6. 根据权利要求4所述的方法，其中，所述工作场景包括无人化场景和人机交互场景，在无人化场景中使搬运机器人(100)切换到第一操作模式中，在人机交互场景中使搬运机器人(100)切换到第二操作模式中。
  7. 根据权利要求1至3中任一项所述的方法，其中，所述步骤S2包括：根据工作场景中的人员密度或人流量，在货物拣选方面选择搬运机器 人(100)的以下操作模式：边拣边分模式或先拣后分模式。
  8. 根据权利要求1至3中任一项所述的方法，其中，所述步骤S2包括：根据为调度任务和/或工作场景分配的人员数量生成人车配对结果，基于人车配对结果选择搬运机器人(100)的以下操作模式：一人一车模式、一人多车模式或多人多车模式。
  9. 根据权利要求1至3中任一项所述的方法，其中，所述步骤S2包括：获取搬运机器人(100)的工作场景中的障碍物特性，使搬运机器人(100)的操作模式匹配于所述障碍物特性，
    尤其其中，在涉及静止障碍物的情况下，使搬运机器人(100)针对静止障碍物执行主动避障策略、尤其360°避障或低矮避障策略，在涉及移动障碍物的情况下，使搬运机器人(100)执行减速、尤其减速直至停止的避障策略，在障碍物涉及人员(200)的情况下，根据人员密度和/或人员身高确定搬运机器人(100)的避障策略。
  10. 根据权利要求1至3中任一项所述的方法，其中，所述步骤S1包括：基于传感器数据创建搬运机器人(100)的工作场景的电子地图、尤其三维地图，其中，尤其针对不同的工作场景，在电子地图中标注不同类型的信息和/或以不同方式标注信息。
  11. 根据权利要求10所述的方法，其中，在所述工作场景是零售场景的情况下，在电子地图中标注出商品位置、卸载点位置、称重区位置、打包点位置、结账位置、货架位置、充电桩位置和/或通道位置。
  12. 根据权利要求10所述的方法，其中，在所述工作场景是零售场景的情况下，在电子地图中标注出商品与货架的对应关系。
  13. 根据权利要求10所述的方法，其中，在所述工作场景是零售场景的情况下，在电子地图中按照商品类别和/或商品贩卖属性分区地标注货架 位置，其中，所述商品贩卖属性尤其包括散装销售和整装销售。
  14. 根据权利要求1至3中任一项所述的方法，其中，所述步骤S2包括：获取调度任务包含的订单中的货物重复率和/或货物与拣选位置的对应关系，根据所述货物重复率和/或对应关系选择搬运机器人(100)的以下操作模式：合并操作模式或按序操作模式。
  15. 根据权利要求1至3中任一项所述的方法，其中，所述步骤S2包括：获取调度任务包含的订单的目标使用场景，根据所述目标使用场景选择搬运机器人(100)的以下操作模式：分区操作模式或分类操作模式。
  16. 一种用于控制搬运机器人(100)的设备(1)，所述设备(1)用于执行根据权利要求1至15中任一项所述的方法，所述设备(1)包括：
    通信单元(10)，所述通信单元(10)配置成能够获取搬运机器人(100)的调度任务和/或工作场景；
    处理器(20)，所述处理器(20)配置成能够使搬运机器人(100)的操作模式匹配于所述调度任务和/或工作场景。
  17. 一种搬运机器人(100)，所述搬运机器人(100)包括根据权利要求16所述的设备(1)。
  18. 一种调度系统(300)，所述调度系统(300)包括根据权利要求16所述的设备(1)。
  19. 一种计算机程序产品，其包括计算机程序，所述计算机程序在计算机执行时实施根据权利要求1至15中任一项所述的方法。
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