WO2018090769A1

WO2018090769A1 - Route identification method and system

Info

Publication number: WO2018090769A1
Application number: PCT/CN2017/105844
Authority: WO
Inventors: 徐静
Original assignee: 北京京东尚科信息技术有限公司; 北京京东世纪贸易有限公司
Priority date: 2016-11-16
Filing date: 2017-10-12
Publication date: 2018-05-24
Also published as: CN106447271A

Abstract

A route identification method and system. The route identification method comprises: determining, by a route identification system, and according to a source node and a target node, a search area (101); and utilizing a node in the search area to identify a route, so as to obtain the route from the source node to the target node (102). The route identification method further comprises: If no route from the source node to the target node can be found in the search area, expanding the search area; and utilizing a node in the expanded search area to identify the route. The embodiment is utilized to determine, according to a source node and a target node, a search area, effectively reducing a quantity of nodes to be searched, reducing a duration of planning a route for a warehouse robot, thereby significantly increasing production efficiency.

Description

Path identification method and system

The present application is based on the application of the CN application number 201611030282.5, filed on November 16, 2016, and the priority of which is hereby incorporated by reference.

Technical field

The present disclosure relates to the field of automatic control, and in particular to a path identification method and system.

Background technique

With the rapid development of e-commerce business, the challenge from labor costs is also increasing. In order to further improve operational efficiency, the main method currently used is the selection of staff in the picking area according to the established route. However, with the expansion of operations and the increase in the area of the picking area, this method still consumes a lot of labor costs.

In order to overcome this shortcoming, there are also ways to reduce the labor cost by using storage robots. By using the warehousing robot to move the required shelves to the picking station, the labor costs are reduced. However, the storage robot cannot quickly identify the path in the storage area, thereby reducing the efficiency of the storage robot.

Summary of the invention

One technical problem solved by embodiments of the present disclosure is that the warehousing robot cannot quickly identify the path within the warehousing area, thereby reducing work efficiency.

In accordance with an aspect of one or more embodiments of the present disclosure, a method for identifying a path in a storage area is provided, comprising:

Determining the search area based on the source point and the target point;

Path recognition is performed using nodes within the search area to obtain a path from the source point to the target point.

Optionally, the search area is a rectangle, and the source point and the target point are respectively located on two vertices that are not adjacent to the search area.

Optionally, the foregoing method further includes:

If the path from the source point to the target point is not obtained in the search area, the search area is expanded, and then the nodes in the expanded search area are used for path identification.

Optionally, expanding the search area includes:

For each boundary line of the search area, determine whether the boundary line has reached the boundary of the storage area;

If the boundary line does not reach the boundary of the storage area, move the boundary line to the outside of the search area by a specified distance to An expanded search area is formed.

Optionally, using the nodes in the search area for path identification includes:

The source point is taken as the current node, and the current node is placed in the path list;

Selecting all candidate nodes that the current node can reach in the search area;

If the target points are not included in all the candidate nodes, the candidate nodes with the lowest path cost among all the candidate nodes are taken as the current node, and then the step of placing the current node in the path list is performed;

If the target point is included in all the candidate nodes, the path list is used to obtain the path from the source point to the target point.

Optionally, the path cost of the candidate node is the sum of the cost from the source point to the candidate node and the cost from the candidate node to the target point.

Optionally, selecting all candidate nodes that the current node can reach in the search area includes:

A node that the current node next hop can reach and is not included in the path list is selected as a candidate node in the search area.

In accordance with another aspect of one or more embodiments of the present disclosure, a system for identifying a path in a storage area is provided, comprising:

a region determining module, configured to determine a search region according to the source point and the target point;

The path identification module is configured to perform path identification by using nodes in the search area to obtain a path from the source point to the target point.

Optionally, the above system further includes an area adjustment module, wherein:

The area adjustment module is configured to expand the search area when the path identification module fails to obtain the path from the source point to the target point in the search area, and then instruct the path identification module to perform path identification by using the nodes in the expanded search area.

Optionally, the area adjustment module determines, for each boundary line of the search area, whether the boundary line has reached the boundary of the storage area; if the boundary line does not reach the boundary of the storage area, the boundary line is moved to the outside of the search area by a specified distance, so that Form an expanded search area.

Optionally, the path identification module includes a current node determining unit, a candidate node selecting unit, and a path acquiring unit, where:

a current node determining unit, configured to use the source point as a current node and place the current node in the path list;

a candidate node selecting unit, configured to select all candidate nodes that the current node can reach in the search area; if all the candidate nodes do not include the target point, indicating that the current node determining unit will all the candidate nodes in the middle The candidate node with the smallest path cost is taken as the current node, and the current node is placed in the path list;

The path obtaining unit is configured to obtain a path from the source point to the target point by using the path list in a case where the target point is included in all the candidate nodes.

Optionally, the candidate node selection unit selects, within the search area, a node that the current node next hop can reach and is not included in the path list as a candidate node.

In accordance with another aspect of one or more embodiments of the present disclosure, a system for identifying a path in a storage area is provided, including a memory and a processor, wherein:

a memory for storing instructions;

A processor coupled to the memory, the processor being configured to perform the method as described in any of the above embodiments based on the instructions stored in the memory.

In accordance with another aspect of one or more embodiments of the present disclosure, a computer readable storage medium is provided, wherein a computer readable storage medium stores computer instructions that are executed by a processor to implement any of the embodiments described above Methods.

Other features of the present disclosure and its advantages will be apparent from the following detailed description of exemplary embodiments.

DRAWINGS

The drawings described herein are provided to provide a further understanding of the present disclosure, which is a part of the present disclosure, and the description of the present disclosure and the description thereof are not intended to limit the disclosure. In the drawing:

FIG. 1 is an exemplary flowchart showing a path identification method in accordance with some embodiments of the present disclosure;

2 is an exemplary flowchart showing a path identification method according to further embodiments of the present disclosure;

3 is an exemplary block diagram showing search area adjustments in accordance with some embodiments of the present disclosure;

4 is an exemplary block diagram showing search area adjustments in accordance with further embodiments of the present disclosure;

FIG. 5 is an exemplary flowchart showing a path identification method according to further embodiments of the present disclosure; FIG.

6-10 are exemplary block diagrams illustrating identifying paths within a search area, in accordance with further embodiments of the present disclosure;

11 is an exemplary block diagram showing a path identification system in accordance with some embodiments of the present disclosure;

12 is an exemplary block diagram showing a path identification system in accordance with further embodiments of the present disclosure;

FIG. 13 is an exemplary block diagram showing a path recognition system according to further embodiments of the present disclosure; FIG.

FIG. 14 is an exemplary block diagram showing a path recognition system in accordance with further embodiments of the present disclosure.

detailed description

The technical solutions in the embodiments of the present disclosure are clearly and completely described in the following with reference to the accompanying drawings in the embodiments of the present disclosure. It is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present disclosure without departing from the inventive scope are the scope of the disclosure.

FIG. 1 is an exemplary flowchart showing a path identification method in accordance with some embodiments of the present disclosure, wherein:

Step 101: Determine a search area according to the source point and the target point.

For example, if the coordinates of the source point are (x1, y1) and the coordinates of the target point are (x2, y2), the source point is not the same as the target point, and there are several cases.

1) If x1<x2, y1<y2, then:

Max_x=x2,min_x=x1,max_y=y2,min_x=y1

2) If x1<x2, y1>y2, then:

Max_x=x2,min_x=x1,max_y=y1,min_x=y2

3) If x1>x2, y1>y2, then:

Max_x=x1,min_x=x2,max_y=y1,min_x=y2

4) If x1>x2, y1<y2, then:

Max_x=x1,min_x=x2,max_y=y2,min_x=y1

Wherein, the range of the search area is within a rectangle determined by [min_x, max_x] and [min_x, max_y].

Step 102: Perform path identification by using nodes in the search area to obtain a path from the source point to the target point.

Based on the path identification method provided by the above embodiment of the present disclosure, by determining the search area according to the source point and the target point, the node that needs to be searched can be effectively reduced, and the time required for the path planning of the storage robot to be reduced is reduced, thereby significantly improving the production efficiency.

2 is an exemplary flow chart showing a path identification method in accordance with further embodiments of the present disclosure, wherein:

Step 201: Determine a search area according to the source point and the target point.

Step 202: Perform path identification by using nodes in the search area.

In step 203, it is determined whether a path from the source point to the target point can be obtained. If the path from the source point to the target point can be obtained, the process ends; if the path from the source point to the target point is not obtained in the search area, step 204 is performed.

In step 204, the search area is expanded, and then returns to step 202 to perform path identification using the nodes in the expanded search area.

Optionally, expanding the search area may include:

For each boundary line of the search area, it is judged whether the boundary line has reached the boundary of the storage area. If the boundary line does not reach the boundary of the storage area, the boundary line is moved outside the search area by a specified distance to form an expanded search area. If the boundary line has reached the boundary of the storage area, it will not be adjusted.

Dynamically adjust the search area to get the path from the source point to the target point.

FIG. 3 is an exemplary block diagram showing search area adjustments in accordance with some embodiments of the present disclosure. As shown in FIG. 3, if the path from the source point to the target point is not obtained in the search area 31, the search area 31 is enlarged to continue the path identification in the expanded search area 32.

4 is an exemplary block diagram showing search area adjustments in accordance with further embodiments of the present disclosure. As shown in FIG. 4, the path from the source point to the target point is not obtained in the search area 41. When the search area 41 is enlarged, since one boundary line 411 of the search area 41 is already located at the boundary of the storage area, it is no longer The boundary line is adjusted so that the expanded search area 42 overlaps with the boundary of the original search area 41.

For the present disclosure, path identification can be performed using various path identification schemes within the selected search area, and an achievable example is given below. Those skilled in the art will appreciate that the present disclosure is not limited thereto.

FIG. 5 is an exemplary flowchart showing a path identification method according to further embodiments of the present disclosure, in which:

In step 501, the source point is taken as the current node.

In step 502, the current node is placed in the path list.

Step 503: Select all candidate nodes that the current node can reach in the search area.

The node that the current node next hop can reach and is not included in the path list is selected as the candidate node in the search area.

In step 504, it is determined whether a target point is included in all candidate nodes. If the target point is not included in all the candidate nodes, step 505 is performed; if all the candidate nodes include the target point, step 506 is performed.

Step 505, taking the candidate node with the smallest path cost among all candidate nodes as the current node, and then executing Step 502.

Step 506, using the path list to obtain a path from the source point to the target point.

The following describes the identification path in the search area by a specific example.

6-10 are exemplary block diagrams illustrating identifying paths within a search area, in accordance with further embodiments of the present disclosure.

As shown in FIG. 6, the source point is at A1 and the target point is at D4, thereby determining the search area 6. Here F=G+H is used to determine the path cost of each node (displayed in the upper left corner of the corresponding node), where G is the cost from the source point to the current point (displayed in the lower left corner of the corresponding node), H is from the current The cost of the point to the target point (displayed in the lower right corner of the corresponding node).

Put A1 in the path list. The path list is now {A1}.

Starting from A1, the nodes reachable in the search area are A2, B2, and B1. Obviously, since only nodes in the search area are considered, the processing efficiency can be effectively improved.

Here, the cost of the lateral movement is 10, the cost of the vertical movement is 12, the cost of the oblique movement is 14, and the cost H of the current point to the target point is the cost of reaching the target point by going up and down.

By calculating the cost of A2, B2, and B1, it can be seen that the F value of B2 is the smallest, so B2 is placed in the path list. At this point, the path list is {A1, B2}.

As shown in FIG. 7, starting from B2, nodes reachable in the search area (excluding obstacles A3, C3, C2, and A1 in the path list) are B3, A2, B1, and C1.

By calculating the cost of A2, B1, B3, and C1, it can be seen that the F value of B3 is the smallest, so B3 is placed in the path list. At this point, the path list is {A1, B2, B3}.

As shown in FIG. 8, starting from B3, nodes reachable in the search area (excluding obstacles A3, C3, C2, and A1, B2 in the path list) are A4, B4, C4, and A2.

By calculating the cost of A4, B4, C4, and A2, it can be seen that the F value of C4 is the smallest, so C4 is placed in the path list. At this point, the path list is {A1, B2, B3, C4}.

As shown in FIG. 9, starting from C4, nodes reachable in the search area (excluding obstacle C3, and B3 in the path list) are B4, D4, and D3, and since D4 is the target point, it can be based on the path list. The path A1-B2-B3-C4-D4 is obtained as shown in FIG.

Obviously, because of the path planning in the search area, it can effectively reduce the unnecessary branches of the search. Reduce the time of the planning path and increase production efficiency.

11 is an exemplary block diagram showing a path identification system in accordance with some embodiments of the present disclosure. As shown in FIG. 11, the system includes a region determining module 1101 and a path identifying module 1102, wherein:

The area determination module 1101 is configured to determine a search area based on the source point and the target point.

The path identification module 1102 is configured to perform path identification using nodes within the search area to obtain a path from the source point to the target point.

According to the path recognition system provided by the above embodiment of the present disclosure, by determining the search area according to the source point and the target point, the node that needs to be searched can be effectively reduced, and the time required for the path planning of the storage robot to be reduced is reduced, thereby significantly improving the production efficiency.

FIG. 12 is an exemplary block diagram showing a path recognition system in accordance with further embodiments of the present disclosure. Compared with the embodiment shown in FIG. 11, in the embodiment shown in FIG. 12, in addition to the area determining module 1201 and the path identifying module 1202, an area adjusting module 1203 is further included. among them:

The area adjustment module 1203 is configured to expand the search area when the path identification module 1202 fails to obtain the path from the source point to the target point in the search area, and then instruct the path identification module 1202 to perform the path using the nodes in the expanded search area. Identification.

Optionally, the area adjustment module 1203 determines, for each boundary line of the search area, whether the boundary line has reached the boundary of the storage area. If the boundary line does not reach the boundary of the storage area, the boundary line is moved outside the search area by a specified distance to form an expanded search area.

FIG. 13 is an exemplary block diagram showing a path recognition system in accordance with further embodiments of the present disclosure. The path identification module 1202 may include a current node determining unit 1301, a candidate node selecting unit 1302, and a path obtaining unit 1303, where:

The current node determining unit 1301 is configured to use the source point as the current node and the current node in the path list.

The candidate node selecting unit 1302 is configured to select all the candidate nodes that the current node can reach in the search area; if the target points are not included in all the candidate nodes, the current node determining unit 1301 is the candidate node that minimizes the path cost among all the candidate nodes. As the current node, place the current node in the path list.

Optionally, the candidate node selection unit 1302 selects, in the search area, that the current node next hop can arrive, Nodes not included in the path list are included as candidate nodes.

The path obtaining unit 1303 is configured to obtain a path from the source point to the target point using the path list in a case where the target point is included in all the candidate nodes.

Alternatively, the functional unit modules described above may be implemented as a general purpose processor, a Programmable Logic Controller (PLC), and a Digital Signal Processor (Digital Signal Processor) for performing the functions described in the present disclosure. Processor, referred to as DSP), Application Specific Integrated Circuit (ASIC), Field-Programmable Gate Array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices , discrete hardware components, or any suitable combination thereof.

FIG. 14 is an exemplary block diagram showing a path recognition system in accordance with further embodiments of the present disclosure. As shown in FIG. 14, the system can include a memory 1401 and a processor 1402. among them:

The memory 1401 is used to store instructions.

The processor 1402 is coupled to a memory 1401 that is configured to perform the methods involved in implementing any of the above-described embodiments of Figures 1, 2, and 5 based on instructions stored in the memory.

In addition, the system also includes a communication interface 1403 for information interaction with other devices. At the same time, the device further includes a bus 1404, and the processor 1402, the communication interface 1403, and the memory 1401 complete communication with each other through the bus 1404.

The memory 1401 in the foregoing FIG. 14 may include a high speed RAM memory, and may further include a non-volatile memory (Non-Volatile Memory, NVM for short), such as at least one disk storage. The memory 1401 can also be a memory array. The memory 1401 may also be partitioned, and the blocks may be combined into a virtual volume according to certain rules.

Furthermore, processor 1402 in FIG. 14 above may be a central processing unit CPU, or may be an application specific integrated circuit ASIC, or one or more integrated circuits configured to implement embodiments of the present disclosure.

The present disclosure also provides a computer readable storage medium storing computer instructions that, when executed by a processor, implement the methods of any of the embodiments of FIGS. 1, 2, and 5.

By implementing the present disclosure, it is possible to effectively reduce the nodes that need to be searched, and reduce the time required for the storage robot to perform path planning, thereby significantly improving production efficiency. As the storage area increases, the advantages of the present disclosure will become more apparent.

Those skilled in the art will appreciate that embodiments of the present disclosure may be provided as a method, apparatus, or computer program product. Accordingly, the present disclosure may employ an entirely hardware embodiment, an entirely software embodiment, or a combination of software and hardware. A form of embodiment of the aspect. Moreover, the present disclosure may take the form of a computer program product embodied on one or more computer-usable non-transitory storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program code. .

The present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus, and computer program products according to embodiments of the present disclosure. It will be understood that each flow and/or block of the flowchart illustrations and/or FIG. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing device to produce a machine for the execution of instructions for execution by a processor of a computer or other programmable data processing device. Means for implementing the functions specified in one or more of the flow or in a block or blocks of the flow chart.

The computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device. The apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.

These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device. The instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.

The description of the present disclosure has been presented for purposes of illustration and description. Many modifications and variations will be apparent to those skilled in the art. The embodiment was chosen and described in order to best explain the principles and embodiments of the embodiments of the invention

Claims

A path identification method includes:

Determining the search area based on the source point and the target point;

Path identification is performed using nodes within the search area to obtain a path from the source point to the target point.
The method of claim 1 wherein

The search area is a rectangle, and the source point and the target point are respectively located on two vertices that are not adjacent to the search area.
The method of claim 1 further comprising:

If the path from the source point to the target point is not obtained in the search area, the search area is expanded, and then the path identification is performed using the nodes in the expanded search area.
The method of claim 3, wherein

Expanding the search area includes:

For each boundary line of the search area, in a case where the boundary line does not reach the boundary of the storage area, the boundary line is moved outside the search area by a specified distance to form an expanded search area.
A method according to any one of claims 1 to 4, wherein

Path identification using nodes within the search area includes:

Using the source point as the current node, placing the current node in the path list;

Selecting all candidate nodes that the current node can reach in the search area;

If the target point is not included in all the candidate nodes, the candidate node with the lowest path cost among all the candidate nodes is taken as the current node, and then the step of placing the current node in the path list is performed;

If the target point is included in all the candidate nodes, the path from the source point to the target point is obtained by using the path list.
The method of claim 5, wherein

The path cost of the candidate node is the sum of the cost from the source point to the candidate node and the cost from the candidate node to the target point.
The method of claim 5, wherein

Select all candidate nodes including:

A node that the current node next hop can reach and is not included in the path list is selected as a candidate node in the search area.
A path identification system comprising:

a region determining module configured to determine a search region according to the source point and the target point;

The path identification module is configured to perform path identification using a node within the search area to obtain a path from the source point to the target point.
The system of claim 8 wherein

The search area is a rectangle, and the source point and the target point are respectively located on two vertices that are not adjacent to the search area.
The system of claim 8 wherein said system further comprises:

The area adjustment module is configured to expand the search area when the path identification module fails to obtain a path from the source point to the target point in the search area, and then instruct the path identification module to utilize the expanded The nodes in the search area perform path identification.
The system of claim 10 wherein

The area adjustment module is configured to, for each boundary line of the search area, move the boundary line to a distance outside the search area to form a boundary if the boundary line does not reach the boundary of the storage area Expanded search area.
The system of any of claims 8-11, wherein the path identification module comprises:

a current node determining unit configured to use the source point as a current node and place the current node in a path list;

a candidate node selecting unit, configured to select all candidate nodes that the current node can reach in the search area; if the target points are not included in all the candidate nodes, indicating that the current node determining unit is to a candidate node with the smallest path cost among all candidate nodes as the current node, and placing the current node in the path list;

The path obtaining unit is configured to obtain a path from the source point to the target point by using the path list in a case where the target point is included in all of the candidate nodes.
The system of claim 12, wherein

The path cost of the candidate node is the sum of the cost from the source point to the candidate node and the cost from the candidate node to the target point.
The system of claim 12, wherein

The candidate node selection unit is configured to select, within the search area, a node that the current node next hop can reach and that is not included in the path list as a candidate node.
A path identification system comprising:

a memory configured to store instructions;

A processor coupled to the memory, the processor being configured to perform the method of any of claims 1-7 based on instructions stored by the memory.
A computer readable storage medium, wherein the computer readable storage medium stores computer instructions that, when executed by a processor, implement the method of any of claims 1-7.