Stereoscopic warehouse scheduling method and device, electronic equipment and storage medium

Abstract

The invention relates to the field of stereoscopic warehouse scheduling, in particular to a stereoscopic warehouse scheduling method and device, electronic equipment and a storage medium. The method comprises the steps that task information of to-be-executed tasks corresponding to a current period is acquired, and the number of corresponding execution robots is determined according to characteristics and requirements of each to-be-executed task, so that optimization of resource allocation is facilitated, waste or insufficiency of robot resources is avoided, the overall scheduling efficiency is improved, and the scheduling efficiency is improved. According to the method, the task information and the number of the robots are acquired, the execution robot corresponding to each to-be-executed task is further determined based on the task information and the number of the robots, and a detailed execution plan is made for each execution robot, so that each task can be executed by an appropriate robot in an optimal mode, and the scheduling efficiency and accuracy are further improved. Furthermore, each execution plan is sent to the corresponding execution robot to schedule the execution robots to execute tasks according to the plans, and manual participation is not needed in the process, so that the efficiency of the scheduling process is improved.

Description

Technical Field

[0001] The present application relates to the field of high-bay warehouse scheduling, and in particular to a high-bay warehouse scheduling method, device, electronic equipment and storage medium. Background Art

[0002] A high-bay warehouse is a system of storing goods using high-rise three-dimensional shelves and pallets. With the rapid development of e-commerce, the demand for warehousing is also increasing. High-bay warehouses have significant advantages in meeting large-scale, high-speed and high-efficiency warehousing needs.

[0003] In a three-dimensional warehouse for storing vehicle parts, conventional mechanical transportation has certain limitations due to the different sizes and shapes of vehicle parts. Therefore, the current handling of items mainly relies on manual operation. In this process, the staff needs to first receive the handling task, then find the items to be transported and their target transportation location by themselves, and finally go to the location to perform the actual handling operation. However, this manual operation method requires a lot of human resources and is time-consuming, resulting in inefficient scheduling. Summary of the invention

[0004] In order to improve the efficiency of the scheduling process, the present application provides a high-bay warehouse scheduling method, device, electronic device and storage medium.

[0005] In the first aspect, the present application provides a three-dimensional warehouse scheduling method, which adopts the following technical solution: A scheduling method for a three-dimensional warehouse, comprising: Obtaining task information of tasks to be executed corresponding to the current cycle, wherein the tasks to be executed include tasks to be shipped out and tasks to be shipped in, and the task information includes sub-information of goods to be transported and sub-information of itineraries to be transported; Determine the number of execution robots corresponding to each of the tasks to be executed; Based on the task information of the tasks to be executed and the number of execution robots corresponding to each of the tasks to be executed, determining the execution robot corresponding to each of the tasks to be executed, and determining the execution plan corresponding to each of the execution robots; Each of the execution plans is sent to a corresponding execution robot to schedule the execution robot to execute the corresponding execution plan.

[0006] By adopting the above technical solution, the task information of the tasks to be executed corresponding to the current cycle is obtained, including the specific details of the tasks to be shipped out and the tasks to be shipped in. According to the characteristics and requirements of each task to be executed, the corresponding number of execution robots is determined, which helps to optimize resource allocation and avoid waste or shortage of robot resources, thereby improving the overall scheduling efficiency. Then, based on the task information and the number of robots, the execution robot corresponding to each task to be executed is further determined, and a detailed execution plan is formulated for each execution robot, thereby ensuring that each task can be executed by the appropriate robot in the best way, further improving the scheduling efficiency and accuracy. Furthermore, each execution plan is sent to the corresponding execution robot to schedule them to execute the task according to the plan, without the need for human intervention in this process, thereby improving the efficiency of the scheduling process.

[0007] In a possible implementation, the sub-information of the cargo to be transported includes the shape of the cargo and the weight of the cargo, and the weight of the cargo includes the total weight of the cargo and the density distribution of the cargo. The process of determining the number of execution robots corresponding to each task to be executed, and the process of determining the number of execution robots corresponding to each task to be executed, includes: Determine a grab point corresponding to each cargo to be transported based on the cargo weight and the cargo shape; Based on the grasping points corresponding to each cargo to be transported, the number of execution robots corresponding to the task to be executed is determined.

[0008] By adopting the above technical solution, by considering the weight of the goods (including the total weight of the goods and the density distribution of the goods) and the shape of the goods, the key grasping points of each cargo to be transported during the handling process are determined, so that by accurately calculating the grasping points, it is ensured that the robot can grasp and move the goods smoothly and accurately during the handling process to avoid the risk of damage or falling of the goods, and based on the grasping points corresponding to each cargo to be transported, the number of executing robots corresponding to each task to be executed is determined, thereby achieving optimal allocation of resources. By reasonably allocating the number of robots, it can be ensured that each task can be executed in a timely and effective manner, while avoiding the waste or shortage of robot resources.

[0009] In a possible implementation, determining a grabbing point corresponding to each cargo to be transported based on the cargo weight and the cargo shape includes: Based on the weight of the cargo, the cargo to be transported corresponding to the task to be executed is divided into first cargo and second cargo, the first cargo being cargo with uniform cargo density distribution and the second cargo being cargo with uneven cargo density distribution; Determine a first grabbing point corresponding to each of the first transported goods based on the shape of each of the first transported goods, and determine a second grabbing point corresponding to each of the second transported goods based on the shape of each of the second transported goods and the weight of the goods corresponding to the second transported goods; Based on the first grabbing point and the second grabbing point, a grabbing point corresponding to each cargo to be transported is determined.

[0010] By adopting the above technical solution, the goods to be transported are divided into first transport goods (uniform density distribution) and second transport goods (uneven density distribution) by considering the weight of the goods and the distribution of the density of the goods. For the first transport goods (uniform density distribution), the grabbing points are determined based on the shape of the goods. Since the weight of these goods is evenly distributed, the selection of grabbing points mainly depends on the shape factor to ensure stability and balance during transportation. For the second transport goods (uneven density distribution), the grabbing points are determined by comprehensively considering the shape and weight of the goods, thereby reducing the occurrence of instability or tilting during transportation due to uneven weight distribution. Based on the number of first grabbing points and second grabbing points corresponding to the task to be performed, the final grabbing point of each cargo to be transported is determined.

[0011] In a possible implementation, based on the cargo shape of each second transport cargo and the cargo weight corresponding to the second transport cargo, a second grabbing point corresponding to each second transport cargo is determined, and the process of determining the second grabbing point corresponding to each second transport cargo includes: Establishing a three-dimensional cargo model corresponding to the second transport cargo; Based on the cargo shape and density distribution corresponding to the second transport cargo, determine the cargo centroid of the second transport cargo, determine a plurality of cargo areas corresponding to the second transport cargo, and mark the cargo centroid on the cargo three-dimensional model to obtain a target three-dimensional model; Based on the plurality of cargo areas and the cargo centroid, analyzing the force equilibrium state of the second transported cargo to obtain a possible grasping point group corresponding to the target three-dimensional model; A force analysis is performed on the target three-dimensional model based on the possible grasping point group to determine a second grasping point corresponding to the second transported cargo.

[0012] By adopting the above technical solution, by establishing a three-dimensional model, determining the centroid and area division of the cargo, and conducting force balance state analysis and force analysis, it is possible to take into account the shape and weight distribution of the cargo while also considering the force balance state during the handling process, thereby ensuring the stability and safety of the handling operation.

[0013] In a possible implementation, the sub-information of the to-be-transported trip includes the transport start and end locations and the departure time, and based on the task information of the to-be-transported tasks and the number of execution robots corresponding to each of the to-be-transported tasks, determining the execution robot corresponding to each of the to-be-transported tasks includes: Obtain robot information corresponding to each robot, the robot information including a current busy state and a maximum load capacity, the current busy state being the busy state of the robot corresponding to each moment in the current cycle, the busy state being busy or idle; Determine the transportation time period corresponding to the task to be executed based on the transportation start and end positions and the departure time corresponding to the task to be executed; Filter out from the multiple robots a robot whose current busy state is idle during the transportation time period as an available robot corresponding to the task to be performed; Based on the sub-information of the cargo to be transported corresponding to each of the tasks to be executed, the number of executing robots and the maximum carrying capacity of the corresponding available robots, the executing robot corresponding to each of the tasks to be executed is determined from the available robots.

[0014] By adopting the above technical solutions, through comprehensive acquisition of robot information, determination of task transportation time period, screening of available robots, and task allocation based on task requirements and robot capabilities, accurate matching of tasks to be executed and robot resources is achieved, which not only improves the utilization rate and handling efficiency of robot resources, but also ensures the stability and safety of task execution.

[0015] In a possible implementation, based on the sub-information of the goods to be transported corresponding to each of the tasks to be executed, the number of executing robots, and the maximum load capacity of the corresponding available robots, the executing robot corresponding to each of the tasks to be executed is determined from the available robots. The process of determining the executing robot corresponding to each of the tasks to be executed includes: Determine the coordinate points of each grabbing point and the center of mass of each cargo to be transported in the three-dimensional model of the cargo, and establish a grabbing vector corresponding to each grabbing point based on the coordinate points corresponding to each grabbing point, wherein the grabbing vector is a vector pointing from the center of mass to the grabbing point; Acquire a direction vector, and determine a gripping angle corresponding to each gripping point based on the direction vector and each gripping vector, so as to obtain an angle matrix corresponding to each cargo to be transported; Calculate the vertical distance between the grab point and the center of mass of each cargo to be transported, and establish a distance matrix corresponding to each cargo to be transported based on each vertical distance of each cargo to be transported; Determine the lifting force corresponding to each grabbing point of each cargo to be transported based on the cargo sub-information, the distance matrix, and the angle matrix corresponding to each cargo to be transported; Based on the lifting force corresponding to each grasping point and the maximum load capacity of the available robots corresponding to the task to be performed, a robot that meets the number of executing robots is determined from the multiple available robots corresponding to the task to be performed to serve as the executing robot corresponding to the task to be performed.

[0016] By adopting the above technical solution, by comprehensively considering factors such as the physical properties of the goods, the positional relationship of the grasping points, the grasping angle and the lifting force, an accurate match between the tasks to be executed and the robot resources is achieved, which not only improves the utilization rate and handling efficiency of the robot resources, but also ensures the stability and safety of task execution.

[0017] In a possible implementation, the cargo to be transported sub-information includes cargo location, and the determining of the execution plan corresponding to each execution robot includes: Obtaining the transportation start time of each cargo to be transported corresponding to the execution robot, and sorting the cargo to be transported in chronological order to obtain a transportation sequence; Determining a transportation position sequence corresponding to the execution robot based on the transportation sequence; Obtaining a three-dimensional map model of the current stereoscopic warehouse, and marking the transport position sequence on the three-dimensional map model; Generate an optimal dispatch route based on the transportation location on the three-dimensional map model; Based on the optimal scheduling route and the transportation start time of each cargo to be transported, an execution plan corresponding to the execution robot is determined.

[0018] By adopting the above technical solution, by comprehensively considering the transportation priority, location information, warehouse environment and mobility of the robot, not only the robot's handling efficiency and accuracy are improved, but also the warehouse logistics process is optimized and the operating costs are reduced.

[0019] In a second aspect, the present application provides a three-dimensional warehouse scheduling device, which adopts the following technical solution: A three-dimensional warehouse scheduling device, comprising: An acquisition module, used to acquire task information of tasks to be executed corresponding to the current cycle, wherein the tasks to be executed include tasks to be shipped out and tasks to be shipped in, and the task information includes sub-information of goods to be transported and sub-information of itineraries to be transported; A number determination module, used to determine the number of execution robots corresponding to each task to be executed; A plan determination module, used to determine the execution robot corresponding to each of the tasks to be executed, and determine the execution plan corresponding to each of the execution robots based on the task information of the tasks to be executed and the number of execution robots corresponding to each of the tasks to be executed; The sending module is used to send each of the execution plans to the corresponding execution robot to schedule the execution robot to execute the corresponding execution plan.

[0020] In a third aspect, the present application provides an electronic device, which adopts the following technical solution: An electronic device, comprising: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the high-bay warehouse scheduling method described in the first aspect above.

[0021] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium includes: a computer program that can be loaded by a processor and execute the high-bay warehouse scheduling method described in the first aspect.

[0022] In summary, this application includes the following beneficial technical effects: By obtaining the task information of the tasks to be executed corresponding to the current cycle, including the specific details of the tasks to be shipped out and the tasks to be shipped in, the corresponding number of execution robots is determined according to the characteristics and requirements of each task to be executed, which helps to optimize resource allocation and avoid waste or shortage of robot resources, thereby improving the overall scheduling efficiency. Then, based on the task information and the number of robots, the execution robot corresponding to each task to be executed is further determined, and a detailed execution plan is formulated for each execution robot, thereby ensuring that each task can be executed by the appropriate robot in the best way, further improving the scheduling efficiency and accuracy. Furthermore, each execution plan is sent to the corresponding execution robot to schedule them to execute the task according to the plan, without the need for human intervention in this process, thereby improving the efficiency of the scheduling process. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is a schematic diagram of a scenario provided by an embodiment of the present application; Figure 2 It is a flowchart of a stereoscopic warehouse scheduling method provided in an embodiment of the present application; Figure 3 It is a block diagram of a stereoscopic warehouse scheduling device provided in an embodiment of the present application; Figure 4 It is a schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The following is combined with Figure 1-4 This application is described in further detail.

[0025] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0026] In a high-rise warehouse for storing vehicle parts, a plurality of high-rise cabinets with a multi-layer structure are generally used to store vehicle parts. The height of each layer and the size of the compartments of each layer in each high-rise cabinet are different, and can be used to store vehicle parts of different sizes. Specifically, a track for the movement of robots is installed on the top of the high-rise warehouse, and each robot is installed on the track on the top of the warehouse. One robot can correspond to at least two manipulators for grabbing objects. When a robot is not being dispatched, the robot stops in a target area that does not affect the movement of the robot. In the process of dispatching vehicle parts, the robot suspended on the top of the warehouse can move to the position of the vehicle part to be dispatched, grab and move the vehicle part to be dispatched, and carry the vehicle part to be dispatched to the corresponding dispatching position, thereby realizing the mobilization of the vehicle part to be dispatched. Among them, refer to Figure 1 Each robot is connected to an electronic device, which can obtain the current position and scheduling task information of each robot in real time. At the same time, the electronic device can also send the scheduling task to the corresponding robot so that the robot can act according to the scheduling task.

[0027] The present application embodiment provides a method for scheduling a three-dimensional warehouse, such as Figure 2 As shown, the method provided in the embodiment of the present application is executed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, which is not limited in the embodiment of the present application. The method includes steps S201 to S204, wherein: Step S201: Obtain task information of tasks to be executed corresponding to the current cycle.

[0028] Among them, the tasks to be executed include tasks to be shipped out and tasks to be shipped in. One task to be executed may include one or more goods to be transported. The task information includes sub-information of the goods to be transported and sub-information of the itinerary to be transported. Among them, the sub-information of the goods to be transported includes various attribute information of the goods to be transported, such as the number, name, type, size, weight, storage requirements (such as whether constant temperature, moisture-proof, etc.) of the goods, etc. The sub-information of the itinerary to be transported mainly includes the starting and ending locations of the goods transportation, the transportation start time, and the transportation arrival time.

[0029] The electronic device has a database corresponding to any stereoscopic warehouse, and the database corresponding to the current stereoscopic warehouse stores the execution tasks corresponding to any cycle and the tasks to be executed corresponding to the current cycle. Therefore, the tasks to be executed corresponding to the current cycle and the task information corresponding to the tasks to be executed can be obtained from the database corresponding to the current stereoscopic warehouse. In the scheduling management of the stereoscopic warehouse, in order to facilitate the regular processing of tasks, the time is divided into continuous time periods, and each such time period is called a cycle. For example, every 10 minutes can be set as a cycle, and the current cycle refers to the specific time period in which the task is currently being processed.

[0030] Step S202: Determine the number of execution robots corresponding to each task to be executed.

[0031] After obtaining the task information of each task to be executed, the number of robots required to execute can be determined based on the weight of the goods in the task information of the task to be executed. Specifically, for heavier goods, if the carrying capacity of a single robot is limited, multiple robots may be required to carry them together; for situations where the transportation itinerary involves multiple different areas and requires multiple transfers, multiple robots may also be arranged to complete the task in relay. More specifically, the number is determined based on the proportional relationship between the weight of the goods and the rated carrying capacity of the robot. If the weight of the goods is twice the rated carrying capacity of the robot, two robots are arranged accordingly; or a scoring evaluation is performed based on the transportation distance and complexity. When the score exceeds a certain threshold, the number of executing robots is increased accordingly. Taking the logistics stereoscopic warehouse as an example, for a batch of large-scale mechanical equipment with a total weight of 5 tons to be shipped out, and the maximum carrying capacity of a single executing robot is 2 tons, it is determined through calculation that three executing robots need to be arranged to perform the task.

[0032] Step S203: Based on the task information of the tasks to be executed and the number of execution robots corresponding to each task to be executed, determine the execution robot corresponding to each task to be executed, and determine the execution plan corresponding to each execution robot.

[0033] The execution plan includes the execution time and the execution path.

[0034] After obtaining the number of execution robots corresponding to each task to be executed, based on the number of execution robots and the sub-information of the to-be-transported itinerary corresponding to each task to be executed, the execution robots corresponding to each task to be executed are screened out from multiple robots. Specifically, for each task to be executed, based on the sub-information of the to-be-transported itinerary of the task to be executed, the transportation start and end positions and the transportation start time of the task to be executed are obtained. The transportation speed corresponding to the execution robot and the layout of the stereoscopic warehouse are obtained from the database corresponding to the current stereoscopic warehouse, and based on the transportation start and end positions of the task to be executed, the transportation distance corresponding to the task to be executed is obtained, and the transportation duration corresponding to the task to be executed is calculated using the transportation distance and the transportation speed, and the time period from the transportation start time to the starting point through the transportation duration is set as the execution time period corresponding to the task to be executed. Further, the idle state of each execution robot in the current cycle is obtained from the current stereoscopic warehouse, and the execution robots whose idle state is idle during the execution time period are screened out, and the execution robots with the number of execution robots corresponding to the task to be executed are randomly selected as the execution robots of the robots to be executed.

[0035] More specifically, based on the transportation starting and ending positions of the task to be executed, the process of obtaining the transportation distance corresponding to the task to be executed can be: according to the transportation starting and ending positions of the task to be executed and the layout of the warehouse, use the path planning algorithm (such as A algorithm, Dijkstra algorithm, etc.) to plan a feasible path from the starting position to the target position, and use the shortest feasible path as the path corresponding to the task to be executed, and use the distance of the path as the transportation distance corresponding to the task to be executed.

[0036] Furthermore, after obtaining the execution robot corresponding to each task to be executed, an execution plan corresponding to each execution robot is generated based on the execution time period and transportation distance corresponding to each task to be executed.

[0037] Step S204: Send each execution plan to the corresponding execution robot to schedule the execution robot to execute the corresponding execution plan.

[0038] After the execution plan is generated, the corresponding execution plan is accurately sent to the corresponding execution robot in a specific data format (such as an instruction data packet) according to the number of the task to be executed. Specifically, the electronic device sends the execution plan customized for each task to be executed in a JSON format data packet. After receiving the data packet, the task to be executed parses it and performs operations according to the instructions therein, thereby completing the execution process of the entire task.

[0039] The embodiment of the present application provides a scheduling method for a three-dimensional warehouse, which obtains the task information of the tasks to be executed corresponding to the current cycle, including the specific details of the tasks to be shipped out and the tasks to be shipped in, and determines the corresponding number of execution robots according to the characteristics and requirements of each task to be executed, thereby helping to optimize resource allocation and avoid waste or shortage of robot resources, thereby improving the overall scheduling efficiency. Then, based on the task information and the number of robots, the execution robot corresponding to each task to be executed is further determined, and a detailed execution plan is formulated for each execution robot, thereby ensuring that each task can be executed by the appropriate robot in the best way, further improving the scheduling efficiency and accuracy. Furthermore, each execution plan is sent to the corresponding execution robot to schedule them to execute the task according to the plan, without the need for human intervention in this process, thereby improving the efficiency of the scheduling process.

[0040] In a possible implementation of the embodiment of the present application, in the above step S202, when the sub-information of the cargo to be transported includes the shape of the cargo and the weight of the cargo, the weight of the cargo includes the total weight of the cargo and the density distribution of the cargo, The number of executing robots corresponding to each task to be executed is determined, and the process of determining the number of executing robots corresponding to each task to be executed includes: Determine the corresponding grabbing point for each cargo to be transported based on the cargo weight and cargo shape; Based on the grasping points corresponding to each cargo to be transported, the number of execution robots corresponding to the task to be performed is determined.

[0041] The grabbing point is a specific location on the cargo to be transported that is suitable for the robot to perform a grabbing operation.

[0042] Specifically, after obtaining the weight and shape of the goods to be transported, since the goods to be transported may be irregular in shape, or some regular-shaped goods to be transported cannot be lifted by only grabbing one point, the grabbing point of each of the goods to be transported can be determined. Further, after obtaining the number of grabbing points of each of the goods to be transported, the sum of the number of grabbing points of the goods to be transported corresponding to the task to be executed can be calculated as the number of execution robots corresponding to the task to be executed.

[0043] Furthermore, based on the above process, the number of execution robots corresponding to each task to be executed can be determined.

[0044] In this embodiment, based on the weight and shape of the goods, the grabbing point corresponding to each goods to be transported is determined, including: based on the weight of the goods, the goods to be transported corresponding to the task to be executed are divided into first transport goods and second transport goods, the first transport goods are transport goods with uniform cargo density distribution, and the second transport goods are transport goods with uneven cargo density distribution; based on the cargo shape of each first transport cargo, the first grabbing point corresponding to each first transport cargo is determined, and based on the cargo shape of each second transport cargo and the cargo weight corresponding to the second transport cargo, the second grabbing point corresponding to each second transport cargo is determined; based on the first grabbing point and the second grabbing point, the grabbing point corresponding to each goods to be transported is determined.

[0045] After obtaining the corresponding cargo density distribution for each item to be transported, since objects with uneven cargo density distribution have uneven cargo weight distribution, the uneven weight distribution may cause instability or tilting during transportation. Based on this, the cargo to be transported corresponding to the task to be executed can be divided into first transport cargo and second transport cargo according to whether the cargo density distribution is uniform.

[0046] After obtaining the first transport cargo with uniform cargo density distribution, the center of gravity position of the first transport cargo can be determined according to the cargo shape of the first transport cargo. Specifically, if the cargo shape is regular, the key position corresponding to the regular cargo shape is directly obtained from the database corresponding to the current stereoscopic warehouse (for example, the center of gravity of a cuboid is at the intersection of its diagonals, and the center of gravity of a cylinder is at the midpoint of the central axis), and then a position near the center of gravity, where the cargo surface is flat and convenient for the robot grasping device to contact is selected as the first grasping point. For example, for cuboid-shaped cargo, the center position of each face of the cuboid can be selected as the grasping point, as long as the robot grasping device can stably contact and apply force. If the cargo shape is irregular, the contour corresponding to the cargo shape is analyzed, and the irregular cargo shape is divided into multiple regular cargo areas (Delaunay triangulation, rectangular grid division, etc. can be used, and the embodiment of the present application is not limited to this), and the center of gravity corresponding to each cargo area is obtained, and each two centers of gravity are connected to obtain at least one center of gravity line, and the intersection of each center of gravity line with the cargo shape contour after extension is the position that can keep the cargo balanced as the first grasping point.

[0047] After obtaining the first grabbing point, the second grabbing point of each second transported cargo can be determined based on the cargo shape of each second transported cargo and the cargo weight corresponding to the second transported cargo. After obtaining the first grabbing point and the second grabbing point corresponding to each cargo to be transported, the first grabbing point and the second grabbing point corresponding to each cargo to be transported can be used as the grabbing point of the corresponding cargo to be transported.

[0048] In an embodiment, based on the cargo shape of each second transported cargo and the cargo weight corresponding to the second transported cargo, the second grasping point corresponding to each second transported cargo is determined, and the determination process of the second grasping point corresponding to each second transported cargo includes: establishing a three-dimensional cargo model corresponding to the second transported cargo; based on the cargo shape and density distribution corresponding to the second transported cargo, determining the cargo centroid of the second transported cargo, and determining multiple cargo areas corresponding to the second transported cargo, and marking the cargo centroid on the cargo three-dimensional model to obtain a target three-dimensional model; based on multiple cargo areas and the cargo centroid, analyzing the force balance state of the second transported cargo to obtain a possible grasping point group corresponding to the target three-dimensional model; performing a force analysis on the target three-dimensional model based on the possible grasping point group to determine the second grasping point corresponding to the second transported cargo.

[0049] Among them, the cargo centroid refers to the central position of the mass distribution of the second transport cargo.

[0050] Among them, the possible grasping point group is composed of potential grasping points selected from various areas of the goods. When the execution robot acts on them with a reasonable grasping force, it is highly likely that the goods can maintain force balance during grasping and transportation. Specifically, the possible grasping point group refers to a number of potential grasping points selected from various cargo areas of the goods. These potential grasping points are arranged in a specific spatial layout based on factors such as the centroid position of the goods, the shape of the goods, and the density distribution. When the execution robot operates on these points with a reasonable grasping force, it is highly likely that the goods can maintain force balance during grasping and transportation.

[0051] Specifically, the discrete point cloud data corresponding to the second transported goods are obtained from the database corresponding to the current stereoscopic warehouse, and the point cloud data are processed using 3D modeling software (such as Geomagic, Blender, etc.). The similar points are clustered and fitted into a surface through an algorithm, and then further constructed into a solid model, thereby generating a 3D model of the goods corresponding to the second transported goods.

[0052] Furthermore, the second transported cargo can be divided into a plurality of small units according to the density and volume of different parts of the second transported cargo by numerical integration, and the second transported cargo can be calculated and summed up to obtain the position of the mass center of the second transported cargo. Specifically, based on the three-dimensional cargo model corresponding to the second transported cargo, a three-dimensional coordinate system is established with any point on the cargo as the origin, the length direction of the cargo as the X-axis, the width direction of the cargo as the Y-axis, and the height direction of the cargo as the Z-axis. The second transported cargo is divided into a plurality of small units with regular shapes and uniform density distribution. Each small unit should have a known shape, size, and density. For each small unit, the center of gravity of the small unit is used as the center of mass (since the shape of the small unit is regular, the center of gravity of the small unit is known), and the coordinates of the center of mass of the small unit in the above three-dimensional coordinate system are determined, and the volume of the small unit is further calculated, and the mass of each small unit is calculated using the formula "mass = density × volume". Further, after obtaining the coordinates of the center of mass and the mass of each small unit, the mass of each small unit is multiplied by its center of mass coordinates, and then the results are summed up, and finally divided by the total mass to obtain the overall coordinates of the center of mass. More specifically, based on the first formula: 、Formula 2: 、Formula 3: , obtain the cargo center of the second transport cargo, that is, the coordinates of the cargo center of the second transport cargo in the above three-dimensional coordinate system, and mark the calculated cargo center coordinate position on the cargo three-dimensional model to obtain the target three-dimensional model. Among them, is the abscissa of the cargo’s centroid, is the mass of the ith small unit, ( , , ) is the centroid coordinate of the ith cell.

[0053] Furthermore, the cargo area can be divided according to the density change of the second transported cargo (such as the boundary of sudden density change, etc.). Specifically, for a cargo made of two materials with different densities, it can be divided into two cargo areas according to the interface of the materials; for an object with irregular shape and gradual density change, several areas with relatively close density can be divided according to the density change gradient.

[0054] Taking the cargo centroid in the target three-dimensional model as the core reference, combined with the characteristics of each cargo area, the force balance is analyzed. Considering that the second transport cargo should be balanced after being grasped, the grasping points should be reasonably distributed around the centroid and in different cargo areas, so that the torque generated by the force applied by each grasping point can be balanced with each other. Specifically, for each cargo area, according to its shape, density and relative position to the centroid, the position with relatively flat surface, sufficient structural strength and effective contact with the grasping device of the execution robot is found as a potential grasping point. For example, in an irregularly shaped cargo with high density at one end and low density at the other end, the centroid is biased towards the end with high density. For the cargo area with high density, the position close to the centroid and with sufficient support strength at the edge of the area can be selected as a potential grasping point; for the area with low density, a suitable position that can cooperate with other grasping points to achieve torque balance is also selected. Further, several potential grasping points located at different positions of the centroid and which can reasonably distribute the grasping force so that the cargo is likely to remain balanced during transportation are combined together to form a group of possible grasping points. For example, two potential grasping points that are located on both sides of the center of mass and at a specific distance from the center of mass, and are determined after calculation based on the principles of mechanics to cooperate in grasping the goods to maintain stability, constitute a group of possible grasping points; for another example, in a complex-shaped cargo divided into three cargo areas, from different angles that are closely related to the center of mass and satisfy the mechanical equilibrium conditions, one potential grasping point is selected in each area, and a possible grasping point group containing three points is obtained.

[0055] Furthermore, using computer-aided engineering (CAE) software (such as ANSYS, etc.), the target three-dimensional model with possible grasping point group annotations is imported into the software to establish the corresponding mechanical analysis model. The material properties of the goods (such as elastic modulus, Poisson's ratio, etc., which can be determined according to the actual material of the goods), gravity acceleration and other parameters are set, and the grasping force of the execution robot is simulated as an external force acting on the possible grasping points. Then, the force conditions of the goods under different grasping point combinations are simulated and analyzed by the software, mainly observing the stress distribution, deformation degree and overall torque balance indicators of the goods. For example, for different grasping point combinations in the possible grasping point group, the stress size of each part of the goods when being grasped is calculated respectively, and it is judged whether it exceeds the bearing limit of the goods material, whether the goods will produce excessive deformation due to uneven force, and whether the overall torque is balanced. After multiple simulations, analyses and comparisons, the grasping point combinations that can make the stress distribution of the goods uniform, the deformation within the allowable range and the torque balance effect the best are selected as the final second grasping point.

[0056] A possible implementation of the embodiment of the present application, in the above embodiment, when the sub-information of the to-be-transported itinerary includes the transport start and end locations and the time of departure, based on the task information of the to-be-transported task and the number of execution robots corresponding to each to-be-transported task, determining the execution robot corresponding to each to-be-transported task includes: Get the robot information corresponding to each robot, including the current busy state and the maximum load capacity. The current busy state is the busy state of the robot corresponding to each moment in the current cycle, and the busy state is busy or idle. Determine the transportation time period corresponding to the task to be executed based on the transportation start and end locations and the departure time corresponding to the task to be executed; Filter out from multiple robots a robot whose current busy state is idle during the transportation time period as an available robot corresponding to the task to be performed; Based on the sub-information of the cargo to be transported corresponding to each task to be executed, the number of executing robots and the maximum carrying capacity of the corresponding available robots, the executing robot corresponding to each task to be executed is determined from the available robots.

[0057] Among them, the maximum load capacity refers to the maximum value of the cargo weight that the robot can safely carry under the designed and specified working conditions.

[0058] Each execution robot is equipped with a communication module, which can feed back its own status information to the electronic equipment of warehouse management in real time. For the current busy state, the execution robot sends a status mark when the state changes. After receiving the status mark, the electronic equipment records it in the state record table of the corresponding robot, marking it as "busy" or "idle", so as to update the busy state of each robot at each moment in the current cycle. And obtain the corresponding maximum load capacity of each execution robot from the database corresponding to the current stereoscopic warehouse.

[0059] Furthermore, the current busy status of all stored robots is traversed, and the status identifier of each robot in the transportation time period corresponding to the task to be executed is checked one by one. If the status identifier of a robot at all times in the entire transportation time period is "idle", the robot is filtered out and put into the set of available robots corresponding to the task to be executed.

[0060] Furthermore, in the present embodiment, based on the sub-information of the goods to be transported corresponding to each task to be executed, the number of executing robots and the corresponding maximum load capacity of the available robots, the executing robot corresponding to each task to be executed is determined from the available robots, and the determination process of the executing robot corresponding to each task to be executed includes: determining the coordinate points of each grasping point and the center of mass of each goods to be transported in the three-dimensional model of the goods, and establishing a grasping vector corresponding to each grasping point based on the coordinate points corresponding to each grasping point, the grasping vector being a vector pointing from the center of mass to the grasping point; obtaining a direction vector, and determining the grasping vector corresponding to each grasping point based on the direction vector and each grasping vector Angle, to obtain the angle matrix corresponding to each cargo to be transported; calculate the vertical distance between the grabbing point and the center of mass of each cargo to be transported, and establish the distance matrix corresponding to each cargo to be transported based on each vertical distance of each cargo to be transported; determine the lifting force corresponding to each grabbing point of each cargo to be transported based on the cargo sub-information to be transported, the distance matrix and the angle matrix corresponding to each cargo to be transported; based on the lifting force corresponding to each grabbing point and the maximum carrying capacity of the available robot corresponding to the task to be performed, determine the robot that meets the number of executing robots from the multiple available robots corresponding to the task to be performed as the executing robot corresponding to the task to be performed.

[0061] Among them, the lifting force is used to characterize the minimum force required to lift the object at each grab point on the cargo.

[0062] Specifically, the existing three-dimensional model of the cargo (established by the 3D scanning method described above) is used to determine the coordinates of the grabbing point and the center of mass in the spatial rectangular coordinate system corresponding to the model. For the center of mass coordinates, if it is an object with a regular shape and uniform density, the coordinates can be determined based on the geometric center; for irregular objects with uneven density, the center of mass coordinates can be obtained by the calculation method mentioned above, such as integrating the density distribution and shape. , for each grasping point, also obtain its coordinates in this coordinate system (N represents the Nth grasping point). Further, a grasping vector is constructed based on these coordinates. Taking the Nth grasping point as an example, its grasping vector is The representation in three-dimensional space is ( - - - ), which is the vector difference from the center of mass coordinate point to the grab point coordinate point.

[0063] Furthermore, the direction vector is (1,0,0), and the corresponding grasping vector for each grasping point is , using the vector dot product formula (Among which direction vector, is the grasping angle corresponding to the grasping point N) to calculate the angle. Get the grab angle value corresponding to each grab point. Assume that the number of grab points is n, create an n*1 matrix as the angle matrix, and fill the calculated grab angle value corresponding to each grab point into the corresponding row of the matrix in turn, so as to obtain the angle matrix corresponding to each cargo to be transported.

[0064] For each determined grab point and center of mass coordinates of the cargo to be transported, calculate the vertical distance between them. For each grab point N, if its coordinates are , the centroid coordinates are , according to the application of the distance formula between two points in space in the vertical direction (for example, in a rectangular coordinate system, the vertical distance can be calculated by taking the square root of the square of the difference between the corresponding coordinates, depending on the definition of the vertical direction and the spatial geometric relationship), the vertical distance is calculated Assume the number of grasping points is n, create an n*1 matrix as the distance matrix, and calculate the vertical distance between each grasping point and the centroid. Fill in the corresponding rows of the matrix in sequence to form a distance matrix corresponding to each cargo to be transported.

[0065] Furthermore, key information such as the weight of the cargo G is obtained from the sub-information of the cargo to be transported, and the distance matrix and angle matrix established previously are combined to perform calculations using the principles of mechanics. Specifically, according to the moment balance and force balance equations, in three-dimensional space, for each grab point N, the lifting force can be solved by establishing a set of equations. When considering the vertical force balance, ( represents the lifting force at the grabbing point N), combined with the moment balance equation , solve the lifting force corresponding to each grabbing point. The above calculation process is used for each grabbing point to determine the lifting force corresponding to each grabbing point of each cargo to be transported.

[0066] Furthermore, the lifting force values ​​corresponding to all the grabbing points of each cargo to be transported are summarized, and then the maximum load capacity of the available robots corresponding to the task to be performed is checked. For tasks that require multiple robots to perform collaboratively, the robot selection is performed according to the following logic. Specifically, suppose there are three grabbing points for a cargo to be transported, and the corresponding lifting forces are F1=200 kgf, F2=300 kgf, and F3=250 kgf, respectively, and the maximum load capacity of the available robots is 500 kgf. It is determined that two robots are needed to perform the task, that is, the lifting forces F1 and F2 are assigned to one robot, and the lifting force F3 is assigned to another robot. It is determined whether the total lifting force borne by each robot after such allocation exceeds its maximum load capacity, thereby obtaining an allocation scheme that meets the number of robots and the lifting force borne by each robot is within its maximum load capacity, and the corresponding robot is determined as the execution robot corresponding to the task to be performed.

[0067] A possible implementation manner of the embodiment of the present application, in the above embodiment, when the sub-information of the cargo to be transported includes the cargo location, determining the execution plan corresponding to each execution robot, the process of determining the execution plan corresponding to each execution robot includes: Obtain the transportation start time of each cargo to be transported corresponding to the execution robot, and sort the cargo to be transported in chronological order to obtain a transportation sequence; Determine a transportation position sequence corresponding to the execution robot based on the transportation sequence; Obtain a three-dimensional map model of the current stereoscopic warehouse, and mark the transportation location sequence on the three-dimensional map model; Generate the optimal dispatch route based on the transportation location on the 3D map model; Based on the optimal scheduling route and the transportation start time of each cargo to be transported, the execution plan corresponding to the execution robot is determined.

[0068] Specifically, the transportation start time corresponding to each cargo to be transported is extracted from the sub-information of the to-be-transported itinerary of the task to be executed, and the cargoes are sorted in chronological order, with the cargoes with the earliest transportation start time placed in front, and so on, to obtain the transportation sequence. Further, according to the determined transportation sequence, the cargo location information corresponding to each cargo is extracted from the sub-information of the cargoes to be transported. For example, in a stereoscopic warehouse, the cargo location can be represented by the shelf number, the number of layers, and the cargo location coordinates. For the first cargo in the transportation sequence, its specific location in the warehouse is obtained, such as "the second cargo location on the fifth floor of the third shelf in area A", and then the location information of other cargoes is obtained in sequence according to the order of the transportation sequence. Assuming that the locations of the three cargoes in the transportation sequence are "the second cargo location on the fifth floor of the third shelf in area A", "the fourth cargo location on the third floor of the second shelf in area B", and "the first cargo location on the fourth floor of the first shelf in area C", then the corresponding transportation location sequence is to arrange these location information in this order to form a sequence that can reflect the locations that the execution robot is to reach in sequence.

[0069] Furthermore, the three-dimensional map model of the current three-dimensional warehouse is retrieved from the database corresponding to the current three-dimensional warehouse. For each position in the transportation position sequence, the electronic device uses the annotation function of the three-dimensional map model (different modeling software has corresponding annotation tools and methods) to annotate in an appropriate manner. For example, different colored points can be used to represent different cargo locations, and annotation text can be added to the shelves and cargo locations at the corresponding positions to explain the specific location information. Among them, the three-dimensional map model can be pre-built through professional modeling software (such as SketchUp, 3dsMax, etc. combined with the actual layout data of the warehouse), and regularly updated and maintained according to changes in the warehouse layout (such as adding shelves, adjusting area divisions, etc.).

[0070] Furthermore, after obtaining the transport location, a path planning algorithm (such as A algorithm, Dijkstra algorithm, etc.) can be used to generate the optimal scheduling route. Specifically, the current position of the executing robot is set as the starting node, each position in the transport position sequence is set as the intermediate node in turn, and the last cargo transport position is set as the target node. Based on the distance information between each position in the three-dimensional map model (which can be obtained through coordinate calculation or pre-set distance parameters) and the actual traffic conditions in the warehouse (such as some channels may be temporarily inaccessible due to maintenance, so they are marked as unreachable) as heuristic information, the cost of passing through each intermediate node from the starting node to the target node is calculated (usually measured by distance, time, etc.). By continuously searching and comparing the costs of different paths, the path with the lowest cost is found as the optimal scheduling route.

[0071] Each node in the optimal scheduling route (i.e., each transportation location and the key nodes passed in the middle) is associated with the corresponding transportation start time of the goods to be transported, and the operation time and operation content are determined for each node and the corresponding goods in the order of the optimal scheduling route, so as to generate an execution plan corresponding to the execution robot. For example, after passing through several intermediate nodes, the second cargo location is reached. If the transportation start time of the second cargo is 9:30 am, the execution robot is set in the execution plan to arrive at the location at 9:30 am to grab the cargo, and then continue to the next location according to the route until the transportation task of all cargo is completed. The electronic device can present the execution plan in the form of an instruction list or a data table, which contains detailed information such as time, location, operation, etc., and send this execution plan to the corresponding execution robot so that it can perform the task according to the plan.

[0072] The above embodiment introduces a stereoscopic warehouse scheduling method from the perspective of method flow, and the following embodiment introduces a stereoscopic warehouse scheduling device from the perspective of a virtual module or a virtual unit. Please refer to the following embodiment for details.

[0073] See also Figure 3 The stereoscopic warehouse scheduling device 30 may specifically include: an acquisition module 301, a quantity determination module 302, a plan determination module 303 and a sending module 304, wherein: A high-bay warehouse scheduling device 30, comprising: The acquisition module 301 is used to acquire the task information of the tasks to be executed corresponding to the current cycle, the tasks to be executed include tasks to be shipped out and tasks to be shipped in, and the task information includes sub-information of goods to be transported and sub-information of itineraries to be transported; A number determination module 302 is used to determine the number of execution robots corresponding to each task to be executed; A plan determination module 303 is used to determine the execution robot corresponding to each task to be executed based on the task information of the task to be executed and the number of execution robots corresponding to each task to be executed, and determine the execution plan corresponding to each execution robot; The sending module 304 is used to send each execution plan to the corresponding execution robot to schedule the execution robot to execute the corresponding execution plan.

[0074] In a possible implementation of the embodiment of the present application, when the sub-information of the cargo to be transported includes the shape of the cargo and the weight of the cargo, and the weight of the cargo includes the total weight of the cargo and the density distribution of the cargo, The number determination module 302 is used to determine the number of execution robots corresponding to each task to be executed, and the number of execution robots corresponding to each task to be executed is specifically used to: Determine the corresponding grabbing point for each cargo to be transported based on the cargo weight and cargo shape; Based on the grasping points corresponding to each cargo to be transported, the number of execution robots corresponding to the task to be performed is determined.

[0075] In a possible implementation of the embodiment of the present application, when the number determination module 302 determines the grabbing point corresponding to each cargo to be transported based on the cargo weight and cargo shape, it is specifically used to: Based on the weight of the cargo, the cargo to be transported corresponding to the task to be executed is divided into first transported cargo and second transported cargo, the first transported cargo is the transported cargo with uniform cargo density distribution, and the second transported cargo is the transported cargo with uneven cargo density distribution; Determine a first grabbing point corresponding to each first transported cargo based on the cargo shape of each first transported cargo, and determine a second grabbing point corresponding to each second transported cargo based on the cargo shape of each second transported cargo and the cargo weight corresponding to the second transported cargo; Based on the first grabbing point and the second grabbing point, a grabbing point corresponding to each cargo to be transported is determined.

[0076] In a possible implementation of the embodiment of the present application, the number determination module 302 determines the second grabbing point corresponding to each second transported cargo based on the cargo shape of each second transported cargo and the cargo weight corresponding to the second transported cargo. The determination process of the second grabbing point corresponding to each second transported cargo is specifically used to: Establishing a three-dimensional cargo model corresponding to the second transport cargo; Based on the cargo shape and density distribution corresponding to the second transport cargo, determine the cargo centroid of the second transport cargo, determine multiple cargo areas corresponding to the second transport cargo, and mark the cargo centroid on the cargo three-dimensional model to obtain a target three-dimensional model; Based on the multiple cargo areas and cargo centroids, the force balance state of the second transported cargo is analyzed to obtain a possible grasping point group corresponding to the target three-dimensional model; A force analysis is performed on the target three-dimensional model based on the possible grasping point group to determine a second grasping point corresponding to the second transported cargo.

[0077] In a possible implementation of the embodiment of the present application, when the sub-information of the to-be-transported itinerary includes the transport start and end locations and the departure time, the plan determination module 303 determines the execution robot corresponding to each to-be-transported task based on the task information of the to-be-transported task and the number of execution robots corresponding to each to-be-transported task, specifically for: Get the robot information corresponding to each robot, including the current busy state and the maximum load capacity. The current busy state is the busy state of the robot corresponding to each moment in the current cycle, and the busy state is busy or idle. Determine the transportation time period corresponding to the task to be executed based on the transportation start and end locations and the departure time corresponding to the task to be executed; Filter out from multiple robots a robot whose current busy state is idle during the transportation time period as an available robot corresponding to the task to be performed; Based on the sub-information of the cargo to be transported corresponding to each task to be executed, the number of executing robots and the maximum carrying capacity of the corresponding available robots, the executing robot corresponding to each task to be executed is determined from the available robots.

[0078] In a possible implementation of the embodiment of the present application, the plan determination module 303 determines the execution robot corresponding to each task to be executed from the available robots based on the sub-information of the goods to be transported corresponding to each task to be executed, the number of execution robots, and the maximum carrying capacity of the corresponding available robots. The determination process of the execution robot corresponding to each task to be executed is specifically used to: Determine the coordinates of each grabbing point and the center of mass of each cargo to be transported in the cargo three-dimensional model, and establish a grabbing vector corresponding to each grabbing point based on the coordinates corresponding to each grabbing point, where the grabbing vector is a vector pointing from the center of mass to the grabbing point; Obtain a direction vector, and determine a grasping angle corresponding to each grasping point based on the direction vector and each grasping vector, so as to obtain an angle matrix corresponding to each cargo to be transported; Calculate the vertical distance between the grab point and the center of mass of each cargo to be transported, and establish a distance matrix corresponding to each cargo to be transported based on each vertical distance of each cargo to be transported; Determine the lifting force corresponding to each grabbing point of each cargo to be transported based on the cargo sub-information, the distance matrix, and the angle matrix corresponding to each cargo to be transported; Based on the lifting force corresponding to each grasping point and the maximum load capacity of the available robots corresponding to the task to be performed, a robot that meets the number of executing robots is determined from multiple available robots corresponding to the task to be performed as the executing robot corresponding to the task to be performed.

[0079] In a possible implementation of the embodiment of the present application, when the sub-information of the cargo to be transported includes the cargo location, the plan determination module 303 is specifically used to determine the execution plan corresponding to each execution robot and the determination process of the execution plan corresponding to each execution robot: Obtain the transportation start time of each cargo to be transported corresponding to the execution robot, and sort the cargo to be transported in chronological order to obtain a transportation sequence; Determine a transportation position sequence corresponding to the execution robot based on the transportation sequence; Obtain a three-dimensional map model of the current stereoscopic warehouse, and mark the transportation location sequence on the three-dimensional map model; Generate the optimal dispatch route based on the transportation location on the 3D map model; Based on the optimal scheduling route and the transportation start time of each cargo to be transported, the execution plan corresponding to the execution robot is determined.

[0080] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0081] See also Figure 4 , the embodiment of the present application also introduces an electronic device from the perspective of a physical device, such as Figure 4 As shown, Figure 4 The electronic device 400 shown includes: a processor 401 and a memory 403. The processor 401 and the memory 403 are connected, such as through a bus 402. Optionally, the electronic device 400 may also include a transceiver 404. It should be noted that in actual applications, the transceiver 404 is not limited to one, and the structure of the electronic device 400 does not constitute a limitation on the embodiments of the present application.

[0082] Processor 401 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. Processor 401 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0083] The bus 402 may include a path to transmit information between the above components. The bus 402 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 402 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0084] The memory 403 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0085] The memory 403 is used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 401. The processor 401 is used to execute the application code stored in the memory 403 to implement the contents shown in the above method embodiment.

[0086] The electronic devices include but are not limited to: mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc., and can also be servers, etc. Figure 4 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0087] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding content in the aforementioned method embodiment.

[0088] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0089] The above are only some implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A three-dimensional warehouse scheduling method, characterized in that: include: Obtaining task information of tasks to be executed corresponding to the current cycle, wherein the tasks to be executed include tasks to be shipped out and tasks to be shipped in, and the task information includes sub-information of goods to be transported and sub-information of itineraries to be transported; Determine the number of execution robots corresponding to each of the tasks to be executed; Based on the task information of the tasks to be executed and the number of execution robots corresponding to each of the tasks to be executed, determining the execution robot corresponding to each of the tasks to be executed, and determining the execution plan corresponding to each of the execution robots; Each of the execution plans is sent to a corresponding execution robot to schedule the execution robot to execute the corresponding execution plan.

2. The high-bay warehouse scheduling method according to claim 1, characterized in that: The sub-information of the cargo to be transported includes the shape of the cargo and the weight of the cargo, and the weight of the cargo includes the total weight of the cargo and the density distribution of the cargo. The process of determining the number of execution robots corresponding to each of the tasks to be executed, and the number of execution robots corresponding to each of the tasks to be executed, includes: Determine a grab point corresponding to each cargo to be transported based on the cargo weight and the cargo shape; Based on the grasping point corresponding to each cargo to be transported, the number of execution robots corresponding to the task to be executed is determined.

3. The high-bay warehouse scheduling method according to claim 2, characterized in that: The determining of the grabbing point corresponding to each cargo to be transported based on the cargo weight and the cargo shape includes: Based on the weight of the cargo, the cargo to be transported corresponding to the task to be executed is divided into first cargo and second cargo, the first cargo being cargo with uniform cargo density distribution and the second cargo being cargo with uneven cargo density distribution; Determine a first grabbing point corresponding to each of the first transported goods based on the shape of each of the first transported goods, and determine a second grabbing point corresponding to each of the second transported goods based on the shape of each of the second transported goods and the weight of the goods corresponding to the second transported goods; Based on the first grabbing point and the second grabbing point, a grabbing point corresponding to each cargo to be transported is determined.

4. The high-bay warehouse scheduling method according to claim 3, characterized in that: The determining of the second grabbing point corresponding to each second transported cargo based on the cargo shape of each second transported cargo and the cargo weight corresponding to the second transported cargo, wherein the determining process of the second grabbing point corresponding to each second transported cargo includes: Establishing a three-dimensional cargo model corresponding to the second transport cargo; Based on the cargo shape and density distribution corresponding to the second transport cargo, determine the cargo centroid of the second transport cargo, determine a plurality of cargo areas corresponding to the second transport cargo, and mark the cargo centroid on the cargo three-dimensional model to obtain a target three-dimensional model; Based on the plurality of cargo areas and the cargo centroid, analyzing the force equilibrium state of the second transported cargo to obtain a possible grasping point group corresponding to the target three-dimensional model; A force analysis is performed on the target three-dimensional model based on the possible grasping point group to determine a second grasping point corresponding to the second transported cargo.

5. The high-bay warehouse scheduling method according to claim 4, characterized in that: The sub-information of the to-be-transported trip includes the transport start and end locations and the time of departure. Based on the task information of the to-be-transported tasks and the number of execution robots corresponding to each of the to-be-transported tasks, the execution robot corresponding to each of the to-be-transported tasks is determined, including: Obtain robot information corresponding to each robot, the robot information including a current busy state and a maximum load capacity, the current busy state being the busy state of the robot corresponding to each moment in the current cycle, the busy state being busy or idle; Determine the transportation time period corresponding to the task to be executed based on the transportation start and end positions and the departure time corresponding to the task to be executed; Filter out from the multiple robots a robot whose current busy state is idle during the transportation time period as an available robot corresponding to the task to be performed; Based on the sub-information of the to-be-transported goods corresponding to each of the to-be-executed tasks, the number of executing robots, and the maximum carrying capacity of the corresponding available robots, the executing robot corresponding to each of the to-be-executed tasks is determined from the available robots.

6. The high-bay warehouse scheduling method according to claim 5, characterized in that: Based on the sub-information of the goods to be transported corresponding to each of the tasks to be executed, the number of executing robots, and the maximum load capacity of the corresponding available robots, the executing robot corresponding to each of the tasks to be executed is determined from the available robots. The process of determining the executing robot corresponding to each of the tasks to be executed includes: Determine the coordinate points of each grabbing point and the center of mass of each cargo to be transported in the three-dimensional model of the cargo, and establish a grabbing vector corresponding to each grabbing point based on the coordinate points corresponding to each grabbing point, wherein the grabbing vector is a vector pointing from the center of mass to the grabbing point; Acquire a direction vector, and determine a gripping angle corresponding to each gripping point based on the direction vector and each gripping vector, so as to obtain an angle matrix corresponding to each cargo to be transported; Calculate the vertical distance between the grab point and the center of mass of each cargo to be transported, and establish a distance matrix corresponding to each cargo to be transported based on each vertical distance of each cargo to be transported; Determine the lifting force corresponding to each grabbing point of each cargo to be transported based on the cargo sub-information, the distance matrix, and the angle matrix corresponding to each cargo to be transported; Based on the lifting force corresponding to each grasping point and the maximum load capacity of the available robots corresponding to the task to be performed, a robot that meets the number of executing robots is determined from the multiple available robots corresponding to the task to be performed to serve as the executing robot corresponding to the task to be performed.

7. The high-bay warehouse scheduling method according to any one of claims 1 to 6, characterized in that: The sub-information of the goods to be transported includes the location of the goods. The process of determining the execution plan corresponding to each execution robot includes: Obtaining the transportation start time of each cargo to be transported corresponding to the execution robot, and sorting the cargo to be transported in chronological order to obtain a transportation sequence; Determining a transportation position sequence corresponding to the execution robot based on the transportation sequence; Obtaining a three-dimensional map model of the current stereoscopic warehouse, and marking the transport position sequence on the three-dimensional map model; Generate an optimal dispatch route based on the transportation location on the three-dimensional map model; Based on the optimal scheduling route and the transportation start time of each cargo to be transported, an execution plan corresponding to the execution robot is determined.

8. A three-dimensional warehouse scheduling device, characterized in that: include: An acquisition module, used to acquire task information of tasks to be executed corresponding to the current cycle, wherein the tasks to be executed include tasks to be shipped out and tasks to be shipped in, and the task information includes sub-information of goods to be transported and sub-information of itineraries to be transported; A number determination module, used to determine the number of execution robots corresponding to each task to be executed; A plan determination module, used to determine the execution robot corresponding to each of the tasks to be executed, and determine the execution plan corresponding to each of the execution robots based on the task information of the tasks to be executed and the number of execution robots corresponding to each of the tasks to be executed; The sending module is used to send each of the execution plans to the corresponding execution robot to schedule the execution robot to execute the corresponding execution plan.

9. An electronic device, characterized in that: The electronic device includes: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the high-bay warehouse scheduling method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed in a computer, the computer is caused to execute the high-bay warehouse scheduling method according to any one of claims 1 to 7.

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