A collaborative picking method based on intelligent picking robots

Abstract

This invention relates to the field of power distribution network logistics management technology, and proposes a collaborative picking method based on intelligent picking robots. By constructing and updating a 3D warehouse map, the picking robots can quickly and accurately identify the location of items, thereby optimizing the picking path, reducing round-trip time during transportation, and improving warehouse picking efficiency. This method allows multiple picking robots to work collaboratively, prioritizing interactions between them, rationally arranging loading and handover paths to avoid path conflicts, and rationally scheduling robot passage by judging path width, improving passage efficiency and avoiding congestion caused by overlapping picking robots. It also reduces round-trip time during transportation. By planning handover paths, it achieves item handover and unified transportation between picking robots, reducing the number of picking robots involved in transportation and minimizing obstacles along the way.

Description

Technical Field

[0001] This invention relates to the field of power distribution network logistics management technology, and in particular to a collaborative picking method based on an intelligent picking robot. Background Technology

[0002] In the field of power distribution network logistics, sorting refers to the process of classifying, organizing, and shipping goods in a warehouse according to specific requirements. Power distribution network logistics management involves the efficient classification and organization of power equipment, components, and related materials. With the rapid development of smart grids, the demand for power distribution network logistics has increased significantly, leading to a sharp increase in warehouse sorting operations and placing higher demands on sorting efficiency, accuracy, and cost control. Traditional sorting methods mainly rely on manual labor, resulting in slow sorting speeds, high error rates, and high labor costs. Therefore, optimizing the execution of sorting tasks has become a pressing technical problem.

[0003] To optimize the execution of sorting tasks, advanced technologies such as automated sorting systems are needed. Automated sorting systems introduce picking robots, conveyor belts, and other equipment to automatically identify and sort power distribution network materials. However, in the sorting of power distribution network materials, due to the large variety of materials and the huge volume of temporary inbound and outbound shipments, the actual sorting process often faces challenges. The limited operational capacity of a single picking robot makes it difficult to meet the demands of large-scale, high-efficiency sorting. Furthermore, using multiple picking robots can lead to problems such as uneven task allocation, mechanical collisions, and path conflicts.

[0004] Based on this, the present invention proposes a collaborative picking method based on intelligent picking robots to reduce labor costs, improve work efficiency, and prevent problems such as uneven task allocation, mechanical collisions, and path conflicts when multiple picking robots are operating. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies and provide a collaborative picking method based on intelligent picking robots to reduce labor costs, improve work efficiency, and prevent problems such as uneven task allocation, mechanical collisions, and path conflicts when multiple picking robots are operating.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A collaborative picking method based on an intelligent picking robot includes the following steps:

[0008] Step 1: Obtain the item information and point cloud data corresponding to each item in the warehouse, and construct a 3D warehouse map based on the item information and point cloud data;

[0009] Step 2: Monitor objects within the warehouse and update the 3D warehouse map;

[0010] Step 3: Obtain the spatial location of the picking robot and map the spatial location of the picking robot onto the 3D warehouse map to obtain a real-time navigation map;

[0011] Step 4: After receiving the sorting task, extract the sorting items from the sorting task and determine the loading location of each sorting item according to the 3D warehouse map;

[0012] Step 5: Based on the loading location of each sorted item, plan the path for the picking robot to load the items.

[0013] Preferably, the specific steps in step 5 are as follows:

[0014] Step 5.1: Take the movement path from one loading position to another as the first path, and form a closed path by enclosing the first path;

[0015] Step 5.2: Extract the sorting area from the sorting task, and set the start and end points of the closed path based on the sorting area; obtain the unassigned picking robot closest to the start point of the closed path, and plan the preparation path of the unassigned picking robot based on the spatial position of the unassigned picking robot and the position of the start point of the closed path, i.e., the unassigned picking robot moves from its current position to the start point of the closed path; obtain the processing delay, the picking robot's moving speed, and the preparation path distance; where the processing delay refers to the difference between the planning start time (the time when the sorting task is received) and the planning end time (the time when the unassigned picking robot is about to start moving), i.e., processing delay = planning start time - planning end time; calculate the preparation time of the unassigned picking robot using the preparation path distance and the picking robot's moving speed;

[0016] Step 5.3: Obtain the distance of each first path in the closed path, and determine the starting point and ending point of each first path in sequence according to the connection order, and number each first path, and calculate the time period of the unassigned picking robot passing through the first path in sequence according to the number; determine the first path;

[0017] Step 5.4: Based on the final number of retained first paths, select several connected first paths as second paths; determine the number of picking robots to perform the sorting operation based on the number of second paths;

[0018] Step 5.5: Based on the start and end points of the first path, determine the start and end points of the second path; according to the end point of the second path, plan the handover path for the picking robots; obtain the unassigned picking robot closest to the start point of the second path, move the unassigned picking robot to the start point of the second path, and then pass through each loading position along the second path in sequence until it reaches the end point of the second path. Then, move along the handover path to the handover position, collect the items, and transport them to the sorting area by a single picking robot.

[0019] Preferably, the specific steps of step 5.3 are as follows:

[0020] Step 5.3.1: Calculate the time t1 for the unassigned picking robot to move to the starting point of the first path by summing the preparation time and the planning end time of the unassigned picking robot; calculate the movement time of the unassigned picking robot on the first path by multiplying the distance of the first path by the movement speed of the picking robot; and calculate the time t2 for the unassigned picking robot to move to the end point of the first path by summing the movement time and the time t1.

[0021] Step 5.3.1-1: Obtain the assigned picking robots that traverse the first path and perform other sorting tasks between time t1 and t2;

[0022] Steps 5.3.1-11: If no assigned picking robot is found, retain the first path;

[0023] Step 5.3.1-12: If an assigned picking robot is obtained, determine whether there is an intersection between the assigned picking robot and the unassigned picking robot on the first path;

[0024] Step 5.3.1-121: If there is an intersection, obtain the width of the first path and determine whether the width of the first path is greater than twice the width of the picking robot;

[0025] If the width of the first path is more than twice the width of the picking robot, that is, two picking robots are allowed to pass side by side, then the first path is retained;

[0026] If the width of the first path is less than or equal to twice the width of the picking robot, meaning only a single picking robot is allowed to pass, then the first path is deleted.

[0027] Step 5.3.1-122: If there is no intersection, retain the first path;

[0028] Step 5.3.2: While retaining the first path, use the following method:

[0029] The time t1 at which the unassigned picking robot is moved to the end of the first path of the previous number is taken as the time t3 at the start of the first path of the current number.

[0030] The travel time of the unassigned picking robot on the first path is calculated by multiplying the distance of the first path with the current number and the speed of the picking robot. Based on the sum of the travel time and time t3, the time t4 for the unassigned picking robot to reach the end of the first path is calculated.

[0031] Step 5.3.2-1: Obtain the assigned picking robots that traverse the first path and perform other sorting tasks between time t3 and t4;

[0032] Use steps 5.3.1-11 to 5.3.1-122 to determine whether to retain the first path;

[0033] Step 5.3.3: In the case of deleting the first path, use the following method:

[0034] Obtain the unassigned picking robot closest to the starting point of the next numbered first path. Based on the spatial location of the unassigned picking robot and the starting point of the first path, plan the preparation path for the unassigned picking robot, i.e., move the unassigned picking robot from its current position to the starting point of the first path. Calculate the preparation time for the unassigned picking robot by the distance of the preparation path and the moving speed of the picking robot.

[0035] Use steps 5.3.1 to 5.3.1-122 to determine whether to retain the first path;

[0036] After traversing all first paths in the closed path, the retained first path is obtained.

[0037] Preferably, in step 5.5, based on the endpoint position of the second path, there are several carrier positions on the second path that are close to and near the sorting area, and the handover path of the picking robot is planned based on the endpoint position of the second path.

[0038] Preferably, the handover path is the path with the shortest sum of time for passing through several handover positions of the loading and picking robots along the second path.

[0039] Preferably, in step 1, the item information is obtained through electronic tags of the power distribution network materials, and the power distribution network material information is loaded onto the three-dimensional warehouse map.

[0040] Preferably, in step 2, if an object moves, point cloud data of the object before and after the movement are obtained, and the point cloud data before the movement is replaced with the point cloud data after the movement to realize real-time updating of the 3D warehouse map. The object is a shelf or an obstacle.

[0041] Preferably, in step 4, there are usually multiple items to be sorted. In order to speed up the sorting efficiency, a picking robot needs to reduce the round-trip time of item transportation and can transport multiple items at once.

[0042] Preferably, in step 1, LiDAR is used to acquire point cloud data of each corner of the warehouse to construct a three-dimensional warehouse map.

[0043] The present invention discloses a collaborative picking method based on an intelligent picking robot, which has the following beneficial effects.

[0044] This invention enables picking robots to quickly and accurately identify item locations by constructing and updating a 3D warehouse map, thereby optimizing picking paths, reducing round-trip time during transportation, and improving warehouse picking efficiency. This method allows multiple picking robots to work collaboratively, prioritizing interactions between them, rationally arranging loading and handover paths to avoid path conflicts, and optimizing robot passage by judging path width, thus improving passage efficiency and preventing congestion caused by overlapping picking robots. It also reduces round-trip time during transportation and, through planned handover paths, achieves item handover and unified transportation between picking robots, reducing the number of picking robots involved in transportation and minimizing obstacles along the way. Attached Figure Description

[0045] Figure 1 This is a flowchart of the collaborative picking method based on an intelligent picking robot according to the present invention.

[0046] Figure 2 This is a schematic diagram of the distribution of picking robots in an embodiment of the present invention.

[0047] Figure 3 This is a schematic diagram of closed path combinations in an embodiment of the present invention.

[0048] Figure 4 This is a distribution diagram of the picking robots assigned at a certain time t1 to t2 in an embodiment of the present invention.

[0049] Figure 5 This is a distribution diagram of the picking robots assigned at a certain time t3 to t4 in an embodiment of the present invention.

[0050] Figure 6 This is a distribution diagram of the picking robots assigned at a certain time t5 to t6 in an embodiment of the present invention.

[0051] Figure 7 This is a schematic diagram of closed path combinations in an embodiment of the present invention.

[0052] Figure 8 This is a schematic diagram of the handover path in an embodiment of the present invention. Detailed Implementation

[0053] To illustrate the possible application scenarios, technical principles, implementable specific solutions, and achievable objectives and effects of this application in detail, the following description, in conjunction with the listed specific embodiments and accompanying drawings, provides a detailed explanation. The embodiments described herein are merely illustrative of the technical solutions of this application and are therefore intended to limit the scope of protection of this application.

[0054] In this document, the term "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The term "embodiment" appearing in various places throughout the specification does not necessarily refer to the same embodiment, nor does it specifically limit its independence or connection with other embodiments. In principle, in this application, as long as there are no technical contradictions or conflicts, the technical features mentioned in each embodiment can be combined in any way to form corresponding implementable technical solutions.

[0055] Unless otherwise defined, the technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the use of related terms herein is merely for the purpose of describing particular embodiments and is not intended to limit this application.

[0056] In the description of this application, the term "and / or" is used to describe the logical relationship between objects, indicating that three relationships can exist. For example, A and / or B means: A exists, B exists, and A and B exist simultaneously. Additionally, the character " / " in this document generally indicates that the preceding and following objects have an "or" logical relationship.

[0057] Unless otherwise specified, the use of terms such as “comprising,” “including,” “having,” or other similar expressions in this application is intended to cover non-exclusive inclusion, which does not exclude the presence of additional elements in a process, method, or product that includes the stated elements, such that a process, method, or product that includes a list of elements may include not only those defined elements but also other elements not expressly listed, or elements inherent to such a process, method, or product.

[0058] Unless otherwise expressly specified or limited, the terms "installation," "connection," "linking," "fixing," and "setting," as used in the description of the embodiments of this application, should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral setting; it can be a mechanical connection, an electrical connection, or a communication connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be the internal connection of two components or the interaction between two components. For those skilled in the art to which this application pertains, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0059] Example

[0060] Please refer to Figure 1 A collaborative picking method based on an intelligent picking robot includes the following steps:

[0061] Step 1: Obtain the item information and point cloud data corresponding to each item in the warehouse, and construct a 3D warehouse map based on the item information and point cloud data;

[0062] As a priority, in this implementation, step 1 uses LiDAR to acquire point cloud data of every corner of the warehouse to construct a 3D warehouse map. In step 1, item information is obtained through electronic tags from the power distribution network materials, and the power distribution network material information is loaded onto the 3D warehouse map.

[0063] Step 2: Monitor objects within the warehouse and update the 3D warehouse map;

[0064] As a priority, in this implementation, in step 2, if an object moves, the point cloud data before and after the object moves is obtained, and the point cloud data before the object moves is replaced with the point cloud data after the object moves, so as to realize the real-time update of the 3D warehouse map. The objects are shelves and obstacles.

[0065] Step 3: Obtain the spatial location of the picking robot and map it onto the 3D warehouse map to obtain a real-time navigation map; each picking robot is equipped with a positioning device, and any existing technology that can meet the positioning accuracy requirement can be selected;

[0066] Step 4: After receiving the sorting task, extract the sorting items from the sorting task and determine the loading location of each sorting item according to the 3D warehouse map;

[0067] As a priority, in this implementation, there are usually multiple items to be sorted in the sorting task in step 4. In order to speed up the sorting efficiency, the picking robot needs to reduce the round-trip time of the items and can transport multiple items at once.

[0068] Specifically, when the warehouse receives the first sorting task, the system automatically extracts the list of items to be sorted from the first sorting task (the sorting items are A, B, C, D, E, and F). Based on the 3D warehouse map, the system quickly determines the loading position of each sorting item (A(Xa, Ya), B(Xb, Yb), C(Xc, Yc), D(Xd, Yd), E(Xe, Ye), and F(Xf, Yf)). To improve sorting efficiency, multiple items need to be loaded so that the picking robot can transport multiple items to the sorting area (Xn, Yn) at one time, thereby reducing the round-trip time for transporting items.

[0069] Step 5: Based on the loading location of each sorted item, plan the path for the picking robot to load the items.

[0070] As a preferred option, in this implementation, the specific steps in step 5 are as follows:

[0071] Step 5.1: Take the movement path from one loading position to another as the first path, and form a closed path by enclosing the first path;

[0072] As an example, in this embodiment, based on the loading location of each item, a movement path is planned from one loading location to another loading location with the shortest distance, i.e., the first path. The specific steps are as follows:

[0073] Choose any item as the starting point; in this example, we take A as the starting point, combined with... Figure 2 Using the following formula, calculate the moving distance from A to B, C, D, E, and F respectively, and obtain the items B and C that are closest to A;

[0074] S = |(Xa-Xi)+(Ya-Yi)|, where S represents the distance A moves to B, C, D, E, and F respectively, and Xi represents the loading position of B, C, D, E, or F;

[0075] Based on the calculated closest items B and C to A, the movement distances from B to C, D, E, and F are calculated using S = |(Xb-Xi)+(Yb-Yi)|. Similarly, the movement distances from C to B, D, E, and F are calculated using S = |(Xc-Xi)+(Yc-Yi)|, yielding the closest item D to B and C. Likewise, based on the closest item D to B and C, the movement distances from D to E and F are calculated using S = |(Xd-Xi)+(Yd-Yi)|, yielding the closest item E to D. Therefore, the resulting closed path combinations include... Figure 3 and Figure 7 Two options are available; choose either one as the planned route. This embodiment selects... Figure 2 The closed path is used as the planned route;

[0076] Step 5.2: Extract the sorting area from the sorting task, and set the start and end points of the closed path based on the sorting area; obtain the unassigned picking robot closest to the start point of the closed path, and plan the preparation path of the unassigned picking robot based on the spatial position of the unassigned picking robot and the position of the start point of the closed path, i.e., the unassigned picking robot moves from its current position to the start point of the closed path; obtain the processing delay, the picking robot's moving speed, and the preparation path distance; where the processing delay refers to the difference between the planning start time (the time when the sorting task is received) and the planning end time (the time when the unassigned picking robot is about to start moving), i.e., processing delay = planning start time - planning end time; calculate the preparation time of the unassigned picking robot using the preparation path distance and the picking robot's moving speed;

[0077] Step 5.3: Obtain the distance of each first path in the closed path, and determine the starting point and ending point of each first path in sequence according to the connection order, and number each first path, and calculate the time period of the unassigned picking robot passing through the first path in sequence according to the number; determine the first path;

[0078] As a preferred option, in this implementation, the specific steps of step 5.3 are as follows:

[0079] Step 5.3.1: Calculate the time t1 for the unassigned picking robot to move to the starting point of the first path by summing the preparation time and the planning end time of the unassigned picking robot; calculate the movement time of the unassigned picking robot on the first path by multiplying the distance of the first path by the movement speed of the picking robot; and calculate the time t2 for the unassigned picking robot to move to the end point of the first path by summing the movement time and the time t1.

[0080] Step 5.3.1-1: Obtain the assigned picking robots that traverse the first path and perform other sorting tasks between time t1 and t2;

[0081] Steps 5.3.1-11: If no assigned picking robot is found, retain the first path;

[0082] Step 5.3.1-12: If an assigned picking robot is obtained, determine whether there is an intersection between the assigned picking robot and the unassigned picking robot on the first path;

[0083] Step 5.3.1-121: If there is an intersection, obtain the width of the first path and determine whether the width of the first path is greater than twice the width of the picking robot;

[0084] If the width of the first path is more than twice the width of the picking robot, that is, two picking robots are allowed to pass side by side, then the first path is retained;

[0085] If the width of the first path is less than or equal to twice the width of the picking robot, meaning only a single picking robot is allowed to pass, then the first path is deleted.

[0086] Step 5.3.1-122: If there is no intersection, retain the first path;

[0087] Step 5.3.2: While retaining the first path, use the following method:

[0088] The time t1 at which the unassigned picking robot is moved to the end of the first path of the previous number is taken as the time t3 at the start of the first path of the current number.

[0089] The travel time of the unassigned picking robot on the first path is calculated by multiplying the distance of the first path with the current number and the speed of the picking robot. Based on the sum of the travel time and time t3, the time t4 for the unassigned picking robot to reach the end of the first path is calculated.

[0090] Step 5.3.2-1: Obtain the assigned picking robots that traverse the first path and perform other sorting tasks between time t3 and t4;

[0091] Use steps 5.3.1-11 to 5.3.1-122 to determine whether to retain the first path;

[0092] Step 5.3.3: In the case of deleting the first path, use the following method:

[0093] Obtain the unassigned picking robot closest to the starting point of the next numbered first path. Based on the spatial location of the unassigned picking robot and the starting point of the first path, plan the preparation path for the unassigned picking robot, i.e., move the unassigned picking robot from its current position to the starting point of the first path. Calculate the preparation time for the unassigned picking robot by the distance of the preparation path and the moving speed of the picking robot.

[0094] Use steps 5.3.1 to 5.3.1-122 to determine whether to retain the first path;

[0095] After traversing all first paths in the closed path, the retained first path is obtained.

[0096] As an example, in this embodiment, such as Figure 4 The diagram shows the distribution of picking robots assigned at a certain time t1 to t2. If there are no assigned picking robots for the first path EF at time t1 to t2, then the first path EF is retained.

[0097] To determine whether to retain the first path DE, follow these steps:

[0098] Obtain the assigned picking robots that traverse the first path DE between times t3 and t4, such as... Figure 5 As shown, Figure 5 This represents the distribution of picking robots assigned at a certain time t3 to t4; (The rest of the text appears to be a mix of characters and symbols, possibly from different sources.) Figure 5 It can be seen that during time t3 to t4, there are assigned picking robots on the first path DE. The question is to determine whether there is an intersection between the assigned and unassigned picking robots on this first path DE (the calculation formula can be: assuming the initial position of the assigned picking robot is x01 and its velocity vector is v01, and the initial position of the unassigned picking robot is x02 and its velocity vector is v01).

[0099] v02; x01+v01*t=x02+v02*t, find the intersection time t. If the intersection time t is within t3~t4, then an intersection exists; otherwise, no intersection exists.

[0100] Depend on Figure 5 It can be seen that the assigned picking robot and the unassigned picking robot have an intersection on the first path DE, and the width of the first path DE only allows a single picking robot to pass. Therefore, the first path DE is deleted.

[0101] To determine whether to retain the first path CD, follow these steps:

[0102] Obtain the unassigned picking robot 2 that is closest to the starting point of the first path CD. Based on the spatial position of the unassigned picking robot 2 and the starting point D of the first path CD, plan the preparation path for the unassigned picking robot (i.e., the unassigned picking robot moves from its current position to the starting point of the first path). Calculate the preparation time of the unassigned picking robot 2 by using the preparation path distance and the picking robot's moving speed.

[0103] The time t5 for the unassigned picking robot 2 to move to the starting point of the first path is calculated by summing the preparation time and the planning end time of the unassigned picking robot 2.

[0104] The travel time of the unassigned picking robot 2 on the first path CD is calculated by multiplying the distance of the first path CD by the speed of the picking robot. Based on the sum of the travel time and time t5, the time t6 for the unassigned picking robot 2 to reach the end of the first path CD is calculated.

[0105] Obtain the assigned picking robots that traverse the first path CD between times t5 and t6, such as... Figure 6 As shown, Figure 6 This represents the distribution of picking robots assigned at a certain time t5 to t6; (The rest of the text appears to be a fragment and requires further context for accurate translation.) Figure 6 It is known that during time t5 to t6, there are assigned picking robots on the first path CD. The question is whether there is an intersection between the assigned and unassigned picking robots on this first path CD (the deduction steps are the same as above, and will not be repeated here). Figure 6 It can be seen that there is no intersection between the assigned picking robot and the unassigned picking robot on the first path CD, so the first path CD is retained;

[0106] Next, determine whether to retain the first path BC and the first path AB in sequence. The steps are the same as above and will not be listed one by one. In this embodiment, the first paths AB, BC, CD, and EF are retained, where the first paths AB, BC, and CD are connected.

[0107] Step 5.4: Based on the final number of retained first paths, select several connected first paths as second paths; determine the number of picking robots to perform the sorting operation based on the number of second paths;

[0108] The first path to be connected is taken as the second path (that is, there are two second paths, second path 1 is composed of the first paths AB, BC, and CD, and second path 2 is composed of the first path EF); the number of picking robots to perform the sorting operation is determined by the number of second paths (that is, two picking robots (the first picking robot and the second picking robot) are used to complete the sorting operation together).

[0109] Step 5.5: Based on the start and end points of the first path, determine the start and end points of the second path; according to the end point of the second path, plan the handover path for the picking robots; obtain the unassigned picking robot closest to the start point of the second path, move the unassigned picking robot to the start point of the second path, and then pass through each loading position along the second path in sequence until it reaches the end point of the second path. Then, move along the handover path to the handover position, collect the items, and transport them to the sorting area by a single picking robot.

[0110] As a preferred embodiment, in step 5.5, based on the endpoint of the second path, several carrier positions on the second path that are close to and near the sorting area are identified, and a handover path for the picking robot is planned based on the endpoint of the second path. In this embodiment, the handover path is the path with the shortest sum of time for passing through several handover positions of the picking robot loaded along the second path.

[0111] As an example, obtain the endpoints of the two second paths (i.e., A and D of second path 1, and E and F of second path 2). Use the starting point of the first path as the starting point of the second path (i.e., D and F), and the ending point of the first path as the ending point of the second path (i.e., A and E). Based on the carrier positions at A and E, determine the handover position. Specifically, since there is an intersection between assigned and unassigned picking robots on the first path DE, and the width of the first path only allows a single picking robot to pass, a handover cannot be achieved on the first path DE, and a route change is required. When D is close to the sorting area, the shortest route is as follows: Figure 8 As shown, since one route already has an assigned picking robot and its width only allows a single picking robot to pass, a handover cannot be achieved on that route. The other route, although it also has an assigned picking robot, has a width that allows two picking robots to pass side-by-side, thus a handover can be achieved on that route. The handover location is on this route. This route is used as the handover path for the first picking robot, resulting in handover path 1. The handover path for the second picking robot is the shortest route from E to this route, as shown below. Figure 8 As shown, handover path 2 is obtained;

[0112] Since there are two handover paths 2, a reasonable handover path 2 is selected by calculating the time it takes for the first and second picking robots to move to the handover position. For example, if the first and second picking robots complete loading simultaneously (i.e., arrive at the destination simultaneously and begin transportation), the first picking robot takes 1 second to move from D to handover position 1 and 2 seconds to move to handover position 2. The second picking robot takes 2 seconds to move from E to handover position 1 and 2.5 seconds to move to handover position 2. The time difference ΔT1 = 2 - 1 = 1, and the time difference ΔT2 = 2.5 - 2 = 0.5. Since ΔT1 > ΔT2, handover position 2 is selected as the final handover position, thus determining the final handover path (this handover path passes through the final handover position). The unassigned picking robot closest to the starting point of the second path is obtained, and it is moved to the starting point of the second path. Figure 2 In this embodiment, picking robots 1 and 3 plan a third path based on the spatial location of unassigned picking robots and the starting point of the second path. Picking robot 1 moves from its current position to the starting point of the second path 1—A, and picking robot 3 moves from its current position to the starting point of the second path 2—F. Then, picking robot 1 travels along the second path 1 sequentially through A, B, C, and D, and picking robot 3 travels along the second path 2 sequentially through F and E. Finally, they move along the handover path to the handover position, where picking robot 1 hands over the items to picking robot 3, which then transports them to the sorting area. Upon arrival at the sorting area, the items are placed there. As an option, in this embodiment, to avoid unassigned picking robots on the loading path, sorting tasks can be assigned to unassigned picking robots on the loading path first.

[0113] The above are merely preferred embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Substitutions may include replacements of some structures, devices, or method steps, or may be complete technical solutions. Equivalent substitutions or modifications made to the technical solutions and inventive concepts of the present invention should all be covered within the scope of protection of the present invention.

Claims

1. A collaborative picking method based on an intelligent picking robot, characterized in that, Includes the following steps: Step 1: Obtain the item information and point cloud data corresponding to each item in the warehouse, and construct a 3D warehouse map based on the item information and point cloud data; Step 2: Monitor objects within the warehouse and update the 3D warehouse map; Step 3: Obtain the spatial location of the picking robot and map the spatial location of the picking robot onto the 3D warehouse map to obtain a real-time navigation map; Step 4: After receiving the sorting task, extract the sorting items from the sorting task and determine the loading location of each sorting item according to the 3D warehouse map; Step 5: Based on the loading location of each sorted item, plan the path for the picking robot to load the items; The specific steps in step 5 are as follows: Step 5.1: Take the movement path from one loading position to another as the first path, and form a closed path by enclosing the first path; Step 5.2: Extract the sorting area from the sorting task, and set the start and end points of the closed path based on the sorting area; Find the unassigned picking robot closest to the starting point of the closed path. Based on the spatial location of the unassigned picking robot and the starting point of the closed path, plan the preparation path for the unassigned picking robot, i.e., move the unassigned picking robot from its current position to the starting point of the closed path. Obtain the processing delay, the picking robot's moving speed, and the preparation path distance. The processing delay refers to the difference between the planning start time (the time when the sorting task is received) and the planning end time (the time when the unassigned picking robot is about to start moving), i.e., processing delay = planning start time - planning end time. Calculate the preparation time of the unassigned picking robot using the preparation path distance and the picking robot's moving speed. Step 5.3: Obtain the distance of each first path in the closed path, and determine the starting point and ending point of each first path in sequence according to the connection order, and number each first path, and calculate the time period of the unassigned picking robot passing through the first path in sequence according to the number; determine the first path; Step 5.4: Based on the final number of retained first paths, select several connected first paths as second paths; determine the number of picking robots to perform the sorting operation based on the number of second paths; Step 5.5: Based on the start and end points of the first path, determine the start and end points of the second path; according to the end point of the second path, plan the handover path for the picking robots; obtain the unassigned picking robot closest to the start point of the second path, move the unassigned picking robot to the start point of the second path, and then pass through each loading position along the second path in sequence until it reaches the end point of the second path. Then, move along the handover path to the handover position, collect the items, and transport them to the sorting area by a single picking robot.

2. The collaborative picking method based on an intelligent picking robot as described in claim 1, characterized in that, The specific steps of step 5.3 are as follows: Step 5.3.1: Calculate the time t1 for the unassigned picking robot to move to the starting point of the first path by summing the preparation time and the planning end time of the unassigned picking robot; calculate the movement time of the unassigned picking robot on the first path by multiplying the distance of the first path by the movement speed of the picking robot; and calculate the time t2 for the unassigned picking robot to move to the end point of the first path by summing the movement time and the time t1. Step 5.3.1-1: Obtain the assigned picking robots that traverse the first path and perform other sorting tasks between time t1 and t2; Steps 5.3.1-11: If no assigned picking robot is found, retain the first path; Step 5.3.1-12: If an assigned picking robot is obtained, determine whether there is an intersection between the assigned picking robot and the unassigned picking robot on the first path; Step 5.3.1-121: If there is an intersection, obtain the width of the first path and determine whether the width of the first path is greater than twice the width of the picking robot; If the width of the first path is more than twice the width of the picking robot, that is, two picking robots are allowed to pass side by side, then the first path is retained; If the width of the first path is less than or equal to twice the width of the picking robot, meaning only a single picking robot is allowed to pass, then the first path is deleted. Step 5.3.1-122: If there is no intersection, retain the first path; Step 5.3.2: While retaining the first path, use the following method: The time t1 at which the unassigned picking robot is moved to the end of the first path of the previous number is taken as the time t3 at the start of the first path of the current number. The travel time of the unassigned picking robot on the first path is calculated by multiplying the distance of the first path with the current number and the speed of the picking robot. Based on the sum of the travel time and time t3, the time t4 for the unassigned picking robot to reach the end of the first path is calculated. Step 5.3.2-1: Obtain the assigned picking robots that traverse the first path and perform other sorting tasks between time t3 and t4; Use steps 5.3.1-11 to 5.3.1-122 to determine whether to retain the first path; Step 5.3.3: In the case of deleting the first path, use the following method: Obtain the unassigned picking robot closest to the starting point of the next numbered first path. Based on the spatial location of the unassigned picking robot and the starting point of the first path, plan the preparation path for the unassigned picking robot, i.e., move the unassigned picking robot from its current position to the starting point of the first path. Calculate the preparation time for the unassigned picking robot by the distance of the preparation path and the moving speed of the picking robot. Use steps 5.3.1 to 5.3.1-122 to determine whether to retain the first path; After traversing all first paths in the closed path, the retained first path is obtained.

3. The collaborative picking method based on an intelligent picking robot as described in claim 1, characterized in that, In step 5.5, based on the endpoint position of the second path, several carrier positions that are close to and near the sorting area on the second path are identified, and the handover path of the picking robot is planned based on the endpoint position of the second path.

4. The collaborative picking method based on an intelligent picking robot as described in claim 3, characterized in that, The handover path is the path with the shortest sum of time for passing through several handover positions of the loading and picking robots along the second path.

5. The collaborative picking method based on an intelligent picking robot as described in claim 1, characterized in that, In step 1, the information of the items is obtained through electronic tags of the power distribution network materials, and the information of the power distribution network materials is loaded into the three-dimensional warehouse map.

6. The collaborative picking method based on an intelligent picking robot as described in claim 1, characterized in that, In step 2, if an object moves, point cloud data of the object before and after the movement are obtained, and the point cloud data before the movement is replaced with the point cloud data after the movement to realize real-time updating of the 3D warehouse map. The object is a shelf or an obstacle.

7. The collaborative picking method based on an intelligent picking robot as described in claim 1, characterized in that, In step 4, there are usually multiple items to be sorted. To speed up the sorting process, a picking robot needs to reduce the round-trip time for transporting items and can transport multiple items at once.

8. The collaborative picking method based on an intelligent picking robot as described in claim 1, characterized in that, In step 1, LiDAR is used to acquire point cloud data of every corner of the warehouse to construct a 3D warehouse map.

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