CN115108231A

CN115108231A - Method and apparatus for controlling transfer robot

Info

Publication number: CN115108231A
Application number: CN202110305475.1A
Authority: CN
Inventors: 吕俊龙; 梁璐
Original assignee: Lingdong Technology Beijing Co Ltd
Current assignee: Lingdong Technology Beijing Co Ltd
Priority date: 2021-03-19
Filing date: 2021-03-19
Publication date: 2022-09-27
Also published as: WO2022193762A1

Abstract

The invention relates to the field of intelligent logistics. The present invention provides a method for controlling a transfer robot, the method including the steps of: s1: acquiring a scheduling task and/or a working scene of a transfer robot; and S2: and matching the operation mode of the transfer robot with the scheduling task and/or the working scene. The present invention also provides an apparatus for controlling a transfer robot, a scheduling system, and a computer program product. The control strategy of the invention enables the transfer robot to adapt to complicated and changeable task conditions more intelligently, thereby advantageously improving the flexibility of the whole scheduling system and particularly meeting diversified application requirements in a business super retail scene.

Description

Method and apparatus for controlling transfer robot

Technical Field

The present invention relates to a method for controlling a transfer robot, an apparatus for controlling a transfer robot, a scheduling system, and a computer program product.

Background

With the rise of the fields of electronic commerce, modern factories and the like, the intelligent warehousing system is increasingly used for sorting, carrying, storing and the like of articles. Currently, in the field of intelligent warehouse logistics, in order to reduce the burden of manual sorting personnel and improve the sorting operation efficiency, the sorting and seeding of materials are generally completed through the cooperation of an autonomous Mobile Robot (English: AMR) and a person.

Common picking approaches known in the art are "car-to-person" or "goods-to-person". In the 'vehicle-to-person' picking mode, the AMR reaches a preset storage point position based on the picking task content, and after a manual picker puts specified goods into a goods platform of the AMR, the AMR transports the goods to a working platform. In the "goods-to-person" picking mode, the AMR performs the handling operation and transports the goods to the sorting workstation, where they are sorted manually in unison by a human picker.

However, these solutions have several limitations. In particular, none of the above-described picking schemes dynamically adjusts the operating mode according to environmental conditions or task status, so that it is not possible to comply and adapt to real-time changing operating environments. Furthermore, the fixed deployment of manpower at a specific picking location or sorting station is mostly required in conventional picking mode, which results in a less flexible overall sorting system, in some cases even implying higher time costs and waste of labor resources. Therefore, especially for the super retail business scene which cannot realize unmanned management, the currently adopted AMR control scheme still cannot meet the requirements of large human flow, scattered goods, complex scene and high safety requirement.

Disclosure of Invention

It is an object of the present invention to provide a method for controlling a transfer robot, an apparatus for controlling a transfer robot, a scheduling system and a computer program product that solve at least some of the problems of the prior art.

According to a first aspect of the present invention, there is provided a method for controlling a transfer robot, the method comprising the steps of:

s1: acquiring a scheduling task and/or a working scene of a transfer robot; and

s2: matching the operation mode of the transfer robot to the scheduled tasks and/or work scenarios.

The invention comprises in particular the following technical concepts: on the one hand, the method according to the invention enables, for example, an optimal operating mode of the handling robot for different task types or task phases, respectively, so that the behavior of the handling robot meets diverse application requirements. On the other hand, the task completion quality and the success rate of the transfer robot are closely related to the working scene, and particularly, the damage risk of the transfer robot in a specific scene can be reduced by dynamically switching the operation mode according to the working scene, so that the reliability of the whole scheme is ensured. Compared with the traditional AMR which always deals with all conversion conditions in a single operation mode, the control strategy of the invention improves the flexibility of the whole dispatching system, so that the transfer robot can be more intelligently adapted to complex and changeable task scenes.

Optionally, the work scenario comprises a retail scenario.

Optionally, the step S2 includes: and/or determining the operation mode according to the task attribute of the scheduling task and/or the environment attribute of the working scene, and enabling the transfer robot to work according to the determined operation mode.

The following technical advantages are achieved in particular: each scheduling task or working scene can be assigned a predefined operation mode, so that the scheduling task or working scene can be directly operated according to the specified operation mode when the scheduling task is received or the determined working scene is reached, and the calculation overhead is favorably reduced. By determining the operation mode according to the task attribute or the environment attribute, the operation mode of the transfer robot can be more accurately matched with the dynamically changing task requirement, and the flexibility of the whole scheme is improved.

Optionally, the operation modes include a first operation mode in which the transfer robot is caused to operate autonomously and a second operation mode in which the transfer robot is caused to operate in cooperation with a person, which are switchably implemented.

The following technical advantages are achieved in particular here: the autonomous working mode of the transfer robot is not suitable for all task stages or working scenes, and it is often advantageous to adopt a working mode matched with personnel for tasks with complicated processes or scenes with more variable factors.

Optionally, in a second operating mode, the handling robot is moved together with the person along a uniform trajectory, in particular in a man-in-the-vehicle mode or a person-in-the-vehicle mode; and/or in the second operating mode, the handling robot and the person are moved along independent paths, in particular according to a person approaching vehicle finding mode or a vehicle approaching vehicle finding mode.

Here, the man-in-the-car mode is understood as a transfer robot traveling following a person. The vehicle-carrying-person mode is understood to be a mode in which a person is guided to travel by a transfer robot. The human car finding mode is understood as follows: and the personnel go to the nearest position where the transfer robot stops, pick corresponding commodities according to the tasks in the scheduling task of the transfer robot, drive the transfer robot to the next position after picking is finished, and travel along the predefined path and go to the next nearest position where the transfer robot stops. The vehicle nearby finding mode is understood as follows: the transfer robot travels along a predefined path and stops at the nearest person on the predefined path.

The following technical advantages are achieved in particular: since the transfer robot moves with the human being, rather than having only one moving and the other fixed in position as in prior picking strategies, the flexibility of the overall control scheme may be increased. After the corresponding task is completed for one work location (e.g., a pallet), neither the personnel nor the transfer robot need to be left in place, but rather both are allowed to proceed to the next work location, thereby advantageously avoiding redundancy in personnel deployment.

Optionally, the work scene includes an unmanned scene in which the transfer robot is switched into the first operation mode and a human-computer interaction scene in which the transfer robot is switched into the second operation mode.

The following technical advantages are achieved in particular here: in an unmanned scenario, a handling robot operating on the basis of an autonomous mode may be advantageous, since human influences need not be taken into account in particular in path planning and goods picking, as a result of which computational and time expenditure may be reduced to some extent. In a similar to super retail environment, there are more uncertainties in the path planning, at least, and thus higher demands on the path planning and the safety level of the handling robot, in which case a mode of operation in cooperation with or supervised by humans is advantageous.

Further, it is also possible to take into consideration the reliability of the sensor of the transfer robot itself, the grade model of the transfer robot, and the like when switching the operation mode.

Optionally, the step S2 includes: according to the personnel density or the people flow in the working scene, the following operation modes of the transfer robot are selected in the aspect of cargo picking: the sorting mode is carried out while the picking is carried out or the sorting mode is carried out after the picking is carried out.

The following technical advantages are achieved in particular here: when the personnel density or the flow of people in the environment is large, in order to enable customers in the working scene to be interfered by the operation of the transfer robot as little as possible, the first-sorting-and-then-sorting mode can be selected preferentially, and therefore the stay time of the transfer robot in a specific area can be saved. When the environment has less personnel, the split charging can be completed when picking the goods, so that the subsequent secondary sorting or packaging expenses are saved.

Optionally, the step S2 includes: generating a human-vehicle pairing result according to the number of the personnel allocated to the scheduling task and/or the working scene, and selecting the following operation modes of the transfer robot based on the human-vehicle pairing result: one-person-one-vehicle mode, one-person-multiple-vehicle mode, or multiple-person-multiple-vehicle mode. Here, by selecting the operation mode based on the human-vehicle pairing ratio, the work efficiency can be maximized.

Optionally, the step S2 includes: obstacle characteristics in a work scene of the transfer robot are acquired, and an operation mode of the transfer robot is matched with the obstacle characteristics.

The following technical advantages are achieved in particular: through the adaptability of the obstacle avoidance strategy and the characteristics of the obstacles, the damage of the carrying robot to the obstacles is reduced, meanwhile, the motion trail or the braking strategy can be planned more pertinently, and the probability of task execution interruption caused by obstacle avoidance failure is reduced.

In particular, when a static obstacle is involved, the transfer robot is caused to execute an active obstacle avoidance strategy, in particular a 360 ° obstacle avoidance or low obstacle avoidance strategy, for the static obstacle, when a moving obstacle is involved, the transfer robot is caused to execute an obstacle avoidance strategy that decelerates, in particular, until it stops, and when the obstacle involves a person, the obstacle avoidance strategy of the transfer robot is determined from the person density and/or the person height. Therefore, the collision risk between the transfer robot and the obstacle can be reduced reasonably, and the safety is improved.

Optionally, the step S1 includes: an electronic map, in particular a three-dimensional map, of the work situation of the handling robot is created on the basis of the sensor data, wherein different types of information are marked in the electronic map and/or information is marked in different ways, in particular for different work situations. This makes it possible to provide the transfer robot with the required information for the switched operating scenario, so that the transfer robot is better adapted to the changing operating scenario.

Optionally, in case the work scenario is a retail scenario, a goods location, an unloading point location, a weighing area location, a packing point location, a checkout location, a shelf location, a charging pile location and/or a passage location are marked in the electronic map.

Optionally, in a case where the work scene is a retail scene, the correspondence between the goods and the shelves is marked in the electronic map.

Optionally, in the case that the work scenario is a retail scenario, the shelf locations are labeled in the electronic map in sections according to item categories and/or item sales attributes, wherein the item sales attributes include, inter alia, bulk sales and bulk sales.

The following technical advantages are achieved in particular here: unlike electronic maps of the conventional logistics manufacturing industry, which only need to mark simple shelf numbers and passable areas, in the retail environment such as business and super, pre-processing flows (such as weighing, packaging, code scanning settlement and the like) before commodity sale and sale properties of commodities need to be considered before the commodities are delivered. By marking the special information in the electronic map, the transfer robot can plan the route more efficiently, and the time efficiency is improved.

Optionally, the step S2 includes: acquiring the goods repetition rate and/or the corresponding relation between the goods and the picking position in the order contained in the scheduling task, and selecting the following operation modes of the transfer robot according to the goods repetition rate and/or the corresponding relation: a merge mode of operation or a sequential mode of operation.

In the merge operation mode, for example, the same kind of goods in the scheduling tasks are merged and/or the goods at the same picking position are merged, so that the transfer robot works according to the merged scheduling tasks. In the in-order operation mode, the transfer robot is caused to work in the order of the initial order in the scheduling task.

The following technical advantages are achieved in particular here: the goods type distribution in the same batch of orders can be seen through the goods repetition rate, and particularly, the picking can be completed at the same picking position at one time for the goods of the same type. In addition, the distribution of the goods positions in the same batch of orders can be seen through the corresponding relation between the goods and the picking positions, and particularly the goods arranged in the same area can be picked together. Therefore, the condition that the transfer robot moves to and fro the same picking area for multiple times is obviously reduced in a combined operation mode, and the working efficiency is improved. On the other hand, if the goods repetition rate in the order is low or the position part is uniform, the transfer robot can be directly operated in the sequential operation mode, thereby saving the data processing overhead.

Optionally, the step S2 includes: acquiring a target use scene of an order contained in a scheduling task, and selecting the following operation modes of the transfer robot according to the target use scene: a partition mode of operation or a sort mode of operation.

The following technical advantages are achieved in particular here: according to the target use scene of goods, efficiency maximization cannot be achieved according to the original order sequence, under special conditions, all orders can be broken up and disordered, and partial orders are effectively combined based on the partition information of the goods in the target use scene, so that the goods sorting in a specific partition can be completed more quickly.

According to a second aspect of the present invention, there is provided an apparatus for controlling a transfer robot, the apparatus being configured to perform the method according to the first aspect of the present invention, the apparatus comprising:

a communication unit configured to be able to acquire a scheduling task and/or a work scene of a transfer robot; and

a processor configured to enable matching of an operation mode of a transfer robot to the scheduled tasks and/or work scenarios.

According to a third aspect of the present invention, there is provided a transfer robot comprising the apparatus according to the second aspect of the present invention.

According to a fourth aspect of the present invention there is provided a scheduling system comprising apparatus according to the second aspect of the present invention.

According to a fifth aspect of the invention, there is provided a computer program product comprising a computer program which, when executed by a computer, implements the method according to the first aspect of the invention.

Drawings

The principles, features and advantages of the present invention will be better understood by describing the invention in more detail below with reference to the accompanying drawings. The drawings include:

fig. 1 shows a flowchart of a method for controlling a transfer robot according to an exemplary embodiment of the present invention;

fig. 2 shows a flowchart of one step of a method for controlling a transfer robot according to the present invention;

fig. 3 shows a flowchart of one step of a method for controlling a transfer robot according to the present invention;

fig. 4 shows a block diagram of an apparatus for controlling a transfer robot according to an exemplary embodiment of the present invention;

fig. 5 shows a schematic view of a transfer robot according to an exemplary embodiment of the present invention; and

fig. 6 shows a block diagram of a scheduling system according to an exemplary embodiment of the present invention.

Detailed Description

In order to make the technical problems, technical solutions and advantageous effects of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings and exemplary embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the scope of the invention.

Fig. 1 shows a flowchart of a method for controlling a transfer robot according to an exemplary embodiment of the present invention.

In step S11, a scheduling task is acquired. Here, the scheduling task may include, for example, a picking order, which is a task order in which the items to be picked are formed in a certain order.

In step S12, environmental sensor data of a work scene associated with the scheduled task is acquired. Such environmental sensor data may be detected by a lidar, radar, video sensor, ultrasonic sensor, and/or infrared sensor, among others.

In step S13, an electronic map of the work scene is created based on the acquired sensor data. Such an electronic map may in particular be a three-dimensional map with scene depth data and comprise, for example, the following information: goods position, fill electric pile position, accessible region position, goods shelves position and letter sorting position. In the case of a work scenario involving a retailer superscenario, in particular, a packing position, an unloading point position, a checkout position, a weighing position can also be marked in the electronic map. Meanwhile, in a retail store outdoor scene, the electronic map can be partitioned based on the commodity sale attribute (bulk or whole) and the commodity category (such as food, fresh food, daily necessities and the like), and the shelf position is marked according to the partition. In this case, for example, the cargo information contained in the scheduling task can be matched to an electronic map in order to plan an optimal route for the handling robot by means of the electronic map in the subsequent task execution phase.

In step S21, it is checked whether a pre-stored operation mode is included in the scheduling task and/or the work scene. As an example, predefined operational modes may be recorded for at least a portion of the orders or sub-orders, specific task links, task types, and/or work scenarios.

If there is a pre-stored operation mode available, the transfer robot is directly operated in accordance with the pre-stored operation mode in step S22.

If no operation mode is specified in the scheduled task or the work scenario, a corresponding operation mode may be determined according to the attributes of the scheduled task and/or the environmental attributes of the work scenario in step S23. Here, the task attributes may include, for example: task type (e.g., lead, pick, sort, carry, show, etc.), task stage, task ease, number of tasks, task location, and/or task involvement. The environmental attributes may include, for example: work scene type, work scene area, personnel density, obstacle characteristics, and the like.

After the operation mode is determined, the transfer robot may be operated in the determined operation mode in step S24.

Next, step S25 is optionally further provided. For example, it may be determined in step S25 that: whether there is a change in the status of the scheduled task or the work scenario.

If it is determined that the state change has not occurred, the transfer robot is caused to continue operating in the current operation mode in step S26.

If a state change occurs, it is possible to return again to step S21 to check there again whether updated operating mode information is stored for the current state change. For example, the transfer robot has completed a picking task in the first task phase or the first picking zone, whereby it can be checked whether an adaptive adjustment of the operation mode is required when switching from the first task phase to the second task phase, so that the operation mode of the transfer robot is dynamically adapted to the state change of the scheduled task.

Fig. 2 shows a flowchart of one step of a method for controlling a transfer robot according to the present invention.

As shown in fig. 2, the method step S23 in fig. 1 exemplarily comprises sub-steps S201-S210 in order to further elucidate from the point of view of improving safety how the selection of the operation mode of the handling robot is influenced by scheduling tasks and/or work scenarios.

In step S201, it is determined whether or not the work scene of the transfer robot relates to an unmanned scene. Here, an unmanned scene is understood to be, for example, the following scene: in this scenario, at least part of the working area or task phase of the transfer robot is absent or less subject to human intervention. As an example, an unmanned scene may include a spare part factory of a manufacturing industry, an automated manufacturing plant, an intelligent logistics warehouse, and the like. In contrast, the non-unmanned scene or the man-machine interaction scene may include places where there is much contact with the public, such as a shopping mall, a supermarket, an exhibition, a catering and distribution station, and the like.

If the judgment results that the unmanned scene is involved, the fact that the unmanned scene is involved is that less interference factors exist and the safety level requirement is lower. In this case, a first operation mode of the transfer robot in which the transfer robot is autonomously operated may be selected in step S202. It should be noted here that the unmanned scenario does not represent that the entire working environment of the transfer robot is completely free of human activities, and it is also possible that the unmanned scenario is involved in a partial working phase or a partial working area of the transfer robot, such as "picking", "racking", etc.

If the judgment result relates to a human-computer interaction scene, the fact that more interference factors exist is meant, and the requirement on the safety level is high. In this case, the second operation mode of the transfer robot is selected in step S203. In this second operation mode, the transfer robot is caused to operate in cooperation with the person.

Alternatively, an obstacle in the surrounding environment of the transfer robot is detected in step S204.

It is determined in step S205 whether a static obstacle is involved. The static obstacle may be, for example, goods, tools, outer packages, shelves, etc. located in the movement path of the transfer robot. The dynamic barrier may be, for example, other handling robots, pickers, customers, etc.

If a static obstacle is involved, the transfer robot is caused to execute an active obstacle avoidance strategy in step S206. As an example, a detour path may be calculated for the transfer robot based on a 360 ° environment perception technique to avoid the obstacle. As another example, the transfer robot may be caused to perform low obstacle avoidance or cross obstacle avoidance based on the particular structure or contour of the static obstacle.

If a dynamic obstacle is involved, the transfer robot is caused to perform deceleration obstacle avoidance in step S207. As an example, if it is detected that the obstacle moves at a fast speed (e.g., greater than a speed threshold), the transfer robot may be decelerated to zero for a short time and wait for the obstacle to leave. As another example, it may be further determined whether the obstacle involves a person. If the obstacle is a person, the carrying robot can be decelerated to zero when the density of the stream of people is greater than a certain threshold value or the height of the person is lower than a certain threshold value, and therefore large-scale people or children can be prevented from being collided and injured in a targeted mode. In addition, when the people flow density is larger than a certain threshold value and the speed is lower than a speed threshold value, a detour route can be planned for the carrying robot so as to avoid stagnation people.

Optionally, the density of people near a particular work area (e.g., picking rack) may also be detected in step S208. If there are more people gathering near the target shelf, a "sort-before-sort" mode of operation of the transfer robot may be selected in step S209 in order to reduce the working time at that location, for example to avoid the transfer robot affecting the customer' S shopping experience when performing a picking task.

If there are no or few people at the target shelf, a "pick and place" mode of operation may be selected in step S210 in order to save on subsequent racking or packaging overhead.

In addition to taking into account the person density in the work scenario, it is also conceivable to generate a person-vehicle pairing result as a function of the number of pickers assigned to the scheduling task and/or the work scenario associated with the scheduling task, and to select the following operating mode by means of the person-vehicle pairing result: one person-one vehicle mode, one person-multiple vehicle mode or multiple person-multiple vehicle mode.

Furthermore, depending on the complexity of the work scenario, for example, it may also be decided: whether the transfer robot and the human being move along a uniform trajectory or the transfer robot and the human being move along independent trajectories, respectively. Under the condition that the carrying robot and the personnel move along the unified track, if the experience of the picker is insufficient or the picker is not familiar with the working scene, the carrying robot can plan the route autonomously and enable the picker to follow the carrying robot, so that the error-prone link that the personnel calculate the route by themselves or send the route to the personnel through a dispatching center is omitted. Furthermore, it is also conceivable to move the handling robot following the person according to a predetermined trajectory, which is advantageous in particular in the case of more dispersed goods in the scheduling task, complicated path planning or more variable factors in the work scenario.

If the work scene area associated with the scheduling task is large or the number of goods included in the scheduling task is large, in order to achieve higher flexibility and higher efficiency, the transfer robot and the personnel can move along independent tracks respectively, and the transfer robot and the personnel can be scheduled according to a person-near finding mode and/or a vehicle-near finding mode.

Fig. 3 shows a flowchart of one step of a method for controlling a transfer robot according to the present invention.

As shown in fig. 3, the method step S23 in fig. 1 exemplarily comprises sub-steps S211-S219 in order to further elucidate from the viewpoint of improving the work efficiency how the selection of the operation mode of the handling robot is influenced by scheduling tasks and work scenarios.

In step S211, the goods repetition rate in each order included in the scheduling task is acquired.

In step S212, the correspondence between the package and the picking position included in the scheduling task is acquired. As an example, the position distribution of the goods contained in the scheduling task in the electronic map may be acquired.

Next, in step S213, it is determined whether the cargo repetition rate or the positional distribution unevenness of the cargo in the electronic map is below a threshold. As an example, other metrics may be set to arrive at the best solution when the cargo repetition rate or location distribution is considered together.

If it is judged that the goods repetition rate is low or the goods position distribution is uniform, it may not make sense to recombine and order the initial order, and thus the transfer robot may be caused to perform the sequential operation mode in step S215 in this case. In the in-order operation mode, the transfer robot is caused to work in the order of the initial order in the scheduling task.

Otherwise, the orders of the corresponding category of goods or the corresponding area may be consolidated in step S214 to perform the consolidation operation mode.

Additionally, it is also possible to obtain the target usage scenario of the order included in the scheduling task in step S216 and determine whether the target usage scenario relates to a shopping mall or a supermarket in step S217.

If this is the case, the partition operation mode may be executed in step S218. In this case, for example, all initial orders may be broken up and down, and partial orders may be effectively merged based on the partition information of the goods in the target usage scenario, so that sorting of goods in a specific partition of the target scenario may be completed faster.

If this is not the case, the by-class operation mode may be executed in step S219. For example, items of the same category may be sorted first, thereby reducing the number of repeated trips at the picking area.

Fig. 4 shows a block diagram of an apparatus for controlling a transfer robot according to an exemplary embodiment of the present invention.

The device 1 comprises a communication unit 10 and a processor 20 coupled to each other in communication technology.

The communication unit 10 is configured to be able to acquire a scheduled task and/or a work scene of the transfer robot.

The processor 20 is configured to be able to match the operation mode of the handling robot to said scheduled tasks and/or work scenarios.

As an example, the processor comprises for example an analysis processing module 21, a storage module 22 and a control module 23, the analysis processing module 21 extracting and associating task properties of scheduling tasks and environment properties of work scenarios to respective operation modes, which may for example be predefined and stored in the storage module 22. Next, the respective actuators (e.g., the traveling mechanism, the conveying mechanism, the display mechanism, etc.) of the conveying robot may be controlled by the control module 23 in accordance with the operation mode.

Fig. 5 shows a schematic view of a transfer robot according to an exemplary embodiment of the present invention.

On the left side of fig. 5, a transfer robot 100 is shown, which includes the apparatus 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.

After the operation mode of the transfer robot 100 is determined by the apparatus 1, the control module 23 (not shown) in the apparatus 1 may issue a trigger signal to each actuator 110, 120, 130 of the transfer robot 100 so as to activate or deactivate the corresponding function.

For example, if it is determined by the apparatus 1 that the transfer robot 100 should autonomously complete route planning, the apparatus 1 controls the route planning mechanism 120 to turn on. If it is determined by means of the device 1 that the robot 100 should be made to follow the picker to the target position, the device 1 controls the tracking mechanism 130 to be switched on in order to calculate the relative distance and orientation based on the interaction with the communication unit worn by the person for intelligent following purposes.

Furthermore, the

display contents

111, 112 of the display screen 110 may also be controlled by means of the operation mode determined by the device 1. The

display contents

111, 112 of the display screen 110 of the transfer robot 100 are shown for two different operation modes on the right side of fig. 5. If the picking mode of the transfer robot 100 for assisting personnel is determined by means of the device 1, a content 111 can be shown in the display screen 110, in which, for example, the status of the goods in the respective order in the scheduling task can be displayed, whereby the picker can click on confirmation, stock-out registration, etc. after picking is completed. If the customer display mode of the handling robot 100 is determined by means of the device 1, a content 112 can be shown in the display 110, in which the customer can make an inquiry for goods, for which purpose, for example, the corresponding shelf number or the area in which the shelf is located can be provided. The transfer robot may also direct the customer to a query for the location of the item if the customer clicks on a demand for guidance on the display screen 110.

As shown on the left side of fig. 6, the scheduling system 300 includes the device 1 in fig. 4. Illustratively, the scheduling system 300 is arranged in a warehouse and is used to dispatch scheduling tasks and scheduling instructions to the handling

robots

101, 102 and pickers 200 in the warehouse. Also arranged in the warehouse is a goods presentation area 600 comprising a plurality of

shelves

601, 602. Under the schedule of the scheduling system 300, the plurality of

transfer robots

101, 102 and the person 200 move in the warehouse in appropriate trajectories, respectively.

As an example, the scheduling system 300 generates a human-vehicle pairing result from the number of persons allocated for the current warehouse and the number of transfer robots, and determines a "one-person-multiple-vehicle" mode here, for example. In this mode, the picker 200 moves along a prescribed route within a predetermined area, the plurality of

transfer robots

101, 102 are dispatched to a plurality of positions to be picked, and on the way along the prescribed route, the picker 200 goes to the nearest position where the transfer robot is parked, and picks the corresponding goods according to the dispatch task of the transfer robot. After picking is completed, the transfer robot moves to the next picking position, while the picker 200 proceeds to the next nearest position where the transfer robot is parked or finishes picking.

This "one person multiple car" mode of execution is exemplarily illustrated in connection with fig. 6, wherein the picker 200 is moved in the warehouse, for example, in a counter-clockwise direction. At the time shown on the left side of fig. 6, the picker 200 comes to the rack 602 at which the carrier robot 101 is parked for picking. After completion of picking, the

transfer robots

101 and 102 move in accordance with the scheduled task-specified trajectories, respectively, and the picker 200 continues to move counterclockwise. Then at the time shown on the right side of fig. 6, the transfer robot 101 has left the area near the picker 200, while the transfer robot 102 is "closest" to the picker 200 with respect to the current time, and therefore the picker 200 moves forward to the shelf 601 at which the transfer robot 102 stops to pick.

According to the other people and vehicles pairing result, the operation mode of 'one person and multiple vehicles' or 'multiple persons and multiple vehicles' can be correspondingly executed. In addition, the transfer robot can be moved according to a specific track according to needs, and the picker can be actively searched by the transfer robot during driving.

Although specific embodiments of the invention have been described herein in detail, they have been presented for purposes of illustration only and are not to be construed as limiting the scope of the invention. Various substitutions, alterations, and modifications may be devised without departing from the spirit and scope of the present invention.

Claims

1. A method for controlling a transfer robot (100), the method comprising the steps of:

s1: acquiring a scheduling task and/or a working scene of the transfer robot (100); and

s2: matching the operation mode of the transfer robot (100) to the scheduled tasks and/or work scenarios.

2. The method of claim 1, wherein the work scenario comprises a retail scenario.

3. The method according to claim 1, wherein the step S2 includes: the transfer robot (100) is caused to operate in accordance with an operation mode specified in the scheduled task and/or the work scene, and/or the operation mode is determined on the basis of a task attribute of the scheduled task and/or an environmental attribute of the work scene, and the transfer robot (100) is caused to operate in accordance with the determined operation mode.

4. A method according to any one of claims 1 to 3, wherein the operation modes comprise a first operation mode and a second operation mode which are switchably implemented, in the first operation mode the transfer robot (100) is made to work autonomously, and in the second operation mode the transfer robot (100) is made to work in cooperation with the person (200).

5. Method according to claim 4, wherein in the second operating mode the handling robot (100) is moved together with the person (200) along a uniform trajectory, in particular working in a people-in-vehicle mode or a vehicle-in-vehicle mode; and/or in a second operating mode, the handling robot (100) and the person (200) are moved along separate paths, in particular in a person approach finding mode or a vehicle approach finding mode.

6. The method according to claim 4, wherein the work scenario includes an unmanned scenario in which the transfer robot (100) is switched into the first operation mode and a human-machine interaction scenario in which the transfer robot (100) is switched into the second operation mode.

7. The method according to any one of claims 1 to 3, wherein the step S2 includes: depending on the person density or the person traffic in the work scenario, the following operating modes of the handling robot (100) are selected in the case of goods picking: the sorting mode is carried out while the picking is carried out or the sorting mode is carried out after the picking is carried out.

8. The method according to any one of claims 1 to 3, wherein the step S2 includes: generating a human-vehicle pairing result according to the number of persons allocated for the scheduling task and/or the work scene, and selecting the following operation mode of the transfer robot (100) based on the human-vehicle pairing result: one-person-one-vehicle mode, one-person-multiple-vehicle mode, or multiple-person-multiple-vehicle mode.

9. The method according to any one of claims 1 to 3, wherein the step S2 includes: acquiring obstacle characteristics in a work scene of the transfer robot (100), matching an operation mode of the transfer robot (100) to the obstacle characteristics,

particularly, when a static obstacle is involved, the carrying robot (100) is made to execute an active obstacle avoidance strategy, particularly a 360 DEG obstacle avoidance or low obstacle avoidance strategy, for the static obstacle, when a moving obstacle is involved, the carrying robot (100) is made to execute an obstacle avoidance strategy of decelerating, particularly decelerating until stopping, and when the obstacle involves a person (200), the obstacle avoidance strategy of the carrying robot (100) is determined according to the person density and/or the person height.

10. The method according to any one of claims 1 to 3, wherein the step S1 includes: an electronic map, in particular a three-dimensional map, of a work scenario of the handling robot (100) is created on the basis of the sensor data, wherein different types of information are marked and/or information is marked in different ways in the electronic map, in particular for different work scenarios.

11. The method of claim 10, wherein in the case that the work scenario is a retail scenario, a merchandise location, an unload point location, a weighing area location, a packing point location, a checkout location, a shelf location, a charging post location, and/or a aisle location are marked in an electronic map.

12. The method of claim 10, wherein in a case where the work scene is a retail scene, a correspondence of goods to shelves is marked in an electronic map.

13. Method according to claim 10, wherein, in the case of a retail scenario, the shelf locations are labeled in sections in the electronic map according to item categories and/or item sales attributes, wherein the item sales attributes comprise in particular bulk sales and bulk sales.

14. The method according to any one of claims 1 to 3, wherein the step S2 includes: acquiring a goods repetition rate and/or a corresponding relation between goods and picking positions in an order contained in a scheduling task, and selecting the following operation modes of the transfer robot (100) according to the goods repetition rate and/or the corresponding relation: a merge mode of operation or a sequential mode of operation.

15. The method according to any one of claims 1 to 3, wherein the step S2 includes: acquiring a target use scenario of an order contained in a scheduling task, and selecting the following operation mode of the transfer robot (100) according to the target use scenario: a partition mode of operation or a sort mode of operation.

16. An apparatus (1) for controlling a handling robot (100), the apparatus (1) being adapted to perform the method according to any of claims 1-15, the apparatus (1) comprising:

a communication unit (10), the communication unit (10) being configured to be able to acquire a scheduled task and/or a working scenario of a transfer robot (100);

a processor (20), said processor (20) being configured to enable matching of an operation mode of the transfer robot (100) to said scheduled tasks and/or work scenarios.

17. A transfer robot (100), the transfer robot (100) comprising an arrangement (1) according to claim 16.

18. A scheduling system (300), the scheduling system (300) comprising a device (1) according to claim 16.

19. A computer program product comprising a computer program which, when executed by a computer, implements the method of any one of claims 1 to 15.