Harvesting operation truck cooperative scheduling method and device

Abstract

This application relates to the field of transportation scheduling technology, and in particular to a method and apparatus for the coordinated scheduling of transport vehicles in harvesting operations. The method includes: determining a target transport vehicle based on the relative position between the transport vehicle and the harvester, its load status, and operational requirements; classifying the status of each transport vehicle into a warehouse waiting state, a relay waiting state, a coordinated unloading state, and a return trip state according to the target transport vehicle; in response to the target transport vehicle meeting a preset near-full load condition, switching the transport vehicle in the warehouse waiting state or return trip state to the relay waiting state and moving it to the target preparation position, so that when the target transport vehicle is fully loaded, it is switched to the return trip state, and the transport vehicle in the target preparation position is activated as the new target transport vehicle. This solves the problems of most related technologies that only consider single-vehicle optimization, which easily leads to resource competition, increased waiting time, and decreased overall operational efficiency when multiple vehicles are operating simultaneously.

Description

Technical Field

[0001] This application relates to the field of transportation scheduling technology, and in particular to a method and apparatus for the coordinated scheduling of transport vehicles in harvesting operations. Background Technology

[0002] In related technologies, during agricultural harvesting operations, harvesters and transport vehicles typically need to work together to achieve continuous collection and transfer of crops. With the development of automation technology, transport vehicles operating in single-vehicle mode can autonomously complete path travel and material transportation according to preset tasks, thereby reducing manual intervention and improving operational efficiency to a certain extent.

[0003] However, most of the transportation vehicle scheduling mechanisms and path planning algorithms in related technologies only consider single-vehicle optimization and fail to effectively consider task allocation, path conflict avoidance, and dynamic coordination between vehicles in multi-vehicle collaborative operation scenarios. This can easily lead to problems such as resource competition, increased waiting time, and decreased overall operation efficiency when multiple vehicles are operating at the same time. Summary of the Invention

[0004] This application provides a method and apparatus for the coordinated scheduling of transport vehicles in harvesting operations, in order to solve the problems in related technologies where the scheduling and route planning of transport vehicles mostly only consider the optimization of a single vehicle, which can easily lead to resource competition, increased waiting time and decreased overall operation efficiency when multiple vehicles are operating at the same time.

[0005] The first aspect of this application provides a method for the coordinated scheduling of transport vehicles in harvesting operations, comprising the following steps: determining a target transport vehicle from the at least one transport vehicle based on the relative position, load status, and operational requirements between the at least one transport vehicle and the harvester; activating the target transport vehicle; classifying the operating status of other transport vehicles according to the transport status of the target transport vehicle, and classifying the status of each transport vehicle into a warehouse waiting state, a relay waiting state, a coordinated unloading state, and a return state based on at least one influencing factor between the target transport vehicle and the harvester; responding to the target transport vehicle meeting a preset near-full load condition, switching the transport vehicle in the warehouse waiting state or the return state to the relay waiting state, and moving it to a target preparation position, so that when the target transport vehicle is fully loaded, the target transport vehicle is switched to the return state, and the transport vehicle in the target preparation position is activated as a new target transport vehicle.

[0006] By employing the above technical means, and by identifying the target transport vehicle and clarifying its warehouse waiting status, relay waiting status, collaborative unloading status, and return status, the system can switch the target transport vehicle to the return status when it is fully loaded, and simultaneously activate the transport vehicle in the target preparation position as the new target transport vehicle. This enables refined division and orderly scheduling of multiple transport vehicles across multiple statuses, effectively improving the overall efficiency of forage harvesting operations. Through seamless connection and orderly flow between various statuses, the continuity, efficiency, and safety of operations are significantly enhanced.

[0007] Optionally, in one embodiment of this application, the method for coordinated scheduling of transport vehicles in harvesting operations further includes: generating a planned path based on environmental information of the crop area, indicating whether the transport vehicle is in the waiting state or the return state, so as to drive the transport vehicle that has completed its rotation scheduling along the planned path to the target location.

[0008] By using the above technologies, a planned path can be generated based on the environmental information of the crop area. The operation trajectory can be dynamically adjusted to plan the optimal driving route, thereby better adapting to changes in field terrain, avoiding obstacles, and effectively reducing empty driving distance and repetitive operations, thus improving overall operation efficiency and intelligence level.

[0009] Optionally, in one embodiment of this application, generating a planned path in the waiting state or the return state includes: constructing the path search problem as a multi-objective optimization problem; based on the multi-objective optimization problem, under the premise of satisfying preset basic accessibility constraints, constructing a comprehensive cost function in a weighted manner according to the travel distance of the transport vehicle, the time required to reach the target pose, and the risk of operational conflicts between the transport vehicle and the forage harvester and other transport vehicles; during the path search process, selecting the path with the minimum comprehensive cost as the planned path based on the comprehensive cost function.

[0010] By using the above technical means, based on the travel distance of the transport vehicle, the time required to reach the target position, and the risk of operational conflicts between the transport vehicle and the forage harvester and other transport vehicles, a comprehensive cost function is constructed in a weighted manner. This function can quantitatively evaluate the scheduling priority of transport vehicles by combining multiple dynamic factors, thereby achieving optimal decision-making under multi-objective constraints. This effectively shortens the material receiving response time of transport vehicles and reduces empty-run losses while ensuring operational safety.

[0011] Optionally, in one embodiment of this application, the comprehensive cost function is: , in, 、 、 These are the weighting coefficients corresponding to each cost item; Indicates that the transport vehicle is at the node n Empty running costs at the location; Indicates that the transport vehicle is at the node n Obstacles at the location incur penalties; Indicates the penalty for late arrival of the transport vehicle at the target position; Indicates that the transport vehicle is at the node n The cost of fuel consumption at that location.

[0012] By employing the above technical means and introducing factors such as empty-running costs, obstacle penalty costs, and late arrival time penalties, a comprehensive cost function can be quantitatively constructed. This allows for a comprehensive evaluation of the overall costs of different transport vehicle scheduling schemes. Consequently, in the multi-objective optimization of route planning and vehicle scheduling, the transport vehicle with the optimal overall cost can be dynamically selected as the receiving vehicle, achieving a balance between operational efficiency, time constraints, and safety.

[0013] Optionally, in one embodiment of this application, the step of classifying the operating states of other transport vehicles according to the transport status of the target transport vehicle, and classifying the state of each transport vehicle into a warehouse waiting state, a relay waiting state, a collaborative unloading state, and a return trip state based on at least one influencing factor between the target transport vehicle and the harvester, includes: constructing a transport vehicle operating state discrimination function, wherein the operating state of the transport vehicle is mapped to the warehouse waiting state, the relay waiting state, the collaborative unloading state, or the return trip state, and the transport vehicle operating state discrimination function is: , in, These represent the warehouse waiting status, relay waiting status, collaborative unloading status, and return status, respectively. This represents the current load capacity of the transport vehicle; This refers to the maximum load capacity of the transport vehicle; Forage harvester and the first i The Euclidean distance between the transport vehicles. The distance threshold for coordinated unloading operations.

[0014] By using the above technical means, a discriminant function for the operating status of transport vehicles can be constructed based on the current load, maximum load, Euclidean distance, etc. This allows for the quantitative determination of the state category of the transport vehicle, thereby providing accurate state input for subsequent scheduling decisions and ensuring accurate identification and orderly conversion of the state of each vehicle during the switching process of the target transport vehicle.

[0015] A second aspect of this application provides a collaborative scheduling device for transport vehicles in harvesting operations, comprising: a determination module, configured to determine a target transport vehicle from the at least one transport vehicle based on the relative position between the at least one transport vehicle and the harvester, load status, and operational requirements; a division module, configured to activate the target transport vehicle and divide the operating status of other transport vehicles according to the transport status of the target transport vehicle, so as to divide the status of each transport vehicle into a warehouse waiting state, a relay waiting state, a collaborative unloading state, and a return state based on at least one influencing factor between the target transport vehicle and the harvester; and a scheduling module, configured to, in response to the target transport vehicle meeting a preset near-full load condition, switch the transport vehicle in the warehouse waiting state or the return state to the relay waiting state and move it to a target preparation position, so as to switch the target transport vehicle to the return state when the target transport vehicle is fully loaded and activate the transport vehicle in the target preparation position as a new target transport vehicle.

[0016] Optionally, in one embodiment of this application, the collaborative scheduling device for transport vehicles in harvesting operations further includes: a generation module, used to generate a planned path based on environmental information of the crop area, indicating whether the transport vehicle is in the waiting state or the return state, so as to drive the transport vehicle that has completed its rotation scheduling along the planned path to the target location.

[0017] Optionally, in one embodiment of this application, the generation module includes: a first construction unit, configured to construct the path search problem as a multi-objective optimization problem; a second construction unit, configured to construct a comprehensive cost function based on the multi-objective optimization problem, under the premise of satisfying preset basic reachability constraints, according to the travel distance of the transport vehicle, the time required to reach the target pose, and the risk of operational conflicts between the transport vehicle and the forage harvester and other transport vehicles, through a weighted method; and a selection unit, configured to select the path with the minimum comprehensive cost as the planned path based on the comprehensive cost function during the path search process.

[0018] Optionally, in one embodiment of this application, the comprehensive cost function is: , in, 、 、 These are the weighting coefficients corresponding to each cost item; Indicates that the transport vehicle is at the node n Empty running costs at the location; Indicates that the transport vehicle is at the node n Obstacles at the location incur penalties; Indicates the penalty for late arrival of the transport vehicle at the target position; Indicates that the transport vehicle is at the noden The cost of fuel consumption at that location.

[0019] Optionally, in one embodiment of this application, the partitioning module includes: a third construction unit, configured to construct a transport vehicle operation status discrimination function, wherein the transport vehicle operation status is mapped to the warehouse waiting state, the relay waiting state, the collaborative unloading state, or the return trip state, and the transport vehicle operation status discrimination function is: , in, These represent the warehouse waiting status, relay waiting status, collaborative unloading status, and return status, respectively. This represents the current load capacity of the transport vehicle; This refers to the maximum load capacity of the transport vehicle; Forage harvester and the first i The Euclidean distance between the transport vehicles. The distance threshold for coordinated unloading operations.

[0020] A third aspect of this application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for coordinated scheduling of transport vehicles in harvesting operations as described in the above embodiments.

[0021] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for the coordinated scheduling of transport vehicles in a harvesting operation.

[0022] A fifth aspect of this application provides a computer program product, including a computer program that, when executed, is used to implement the above-described method for the coordinated scheduling of transport vehicles in harvesting operations.

[0023] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0024] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart illustrating a method for the coordinated scheduling of transport vehicles in a harvesting operation, according to an embodiment of this application. Figure 2 This is a schematic diagram illustrating the principle of a transport vehicle collaborative mode in a forage harvesting operation according to one embodiment of this application; Figure 3A flowchart illustrating the coordinated scheduling of a transport vehicle and a forage harvester according to one embodiment of this application; Figure 4 This is a flowchart illustrating a method for the coordinated scheduling of transport vehicles in a harvesting operation according to an embodiment of this application. Figure 5 This is a block diagram of a collaborative scheduling device for transport vehicles in harvesting operations according to an embodiment of this application; Figure 6 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application.

[0025] Figure label: 10-Coordinated scheduling device for transport vehicles during harvesting operations; 100-Determination module, 200-Division module, 300-Scheduling module; 601-Memory, 602-Processor, 603-Communication interface. Detailed Implementation

[0026] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0027] The following description, with reference to the accompanying drawings, describes a method and apparatus for the coordinated scheduling of transport vehicles in harvesting operations according to embodiments of this application.

[0028] With the rapid development of agricultural mechanization, harvesting operations have gradually become automated. However, due to the special structure of harvesters, they need to work in coordination with transport vehicles to complete the entire process from harvesting to transportation. Because of the harvester's unique structure and operating method, the coordinated operation between the harvester and the transport vehicle is crucial to completing the entire process. Nevertheless, in actual field operations, the complexity of the working environment and the coordination issues between vehicles remain key factors restricting operational efficiency.

[0029] In related technologies, most transport vehicles still rely on manual driving or semi-automatic path following to coordinate with harvesters for unloading. This method requires drivers to maintain high-intensity operation for extended periods, leading to fatigue accumulation and reduced operational efficiency. Furthermore, these technologies rely too heavily on operator experience and real-time judgment, lacking intelligent scheduling and path planning, making them prone to errors and inconsistent scheduling, thus affecting the entire operation process. In addition, the transport vehicle scheduling mechanisms and path planning algorithms in these technologies mostly only consider single-vehicle optimization, failing to effectively account for multi-vehicle collaborative operations. This results in gaps in the unloading process, affecting the continuity of forage harvester operations and increasing operating time and energy consumption.

[0030] To address at least one of the aforementioned technical problems, this application provides a collaborative scheduling method for transport vehicles in harvesting operations, aiming to optimize the state division, rotation scheduling, and path planning of transport vehicles, thereby improving the overall efficiency of harvesting operations. In particular, in complex scenarios where multiple transport vehicles are working collaboratively, it effectively improves the continuity, efficiency, and safety of the operation.

[0031] Specifically, Figure 1 This is a flowchart illustrating a method for the coordinated scheduling of transport vehicles in a harvesting operation, as provided in an embodiment of this application.

[0032] like Figure 1 As shown, the collaborative scheduling method for transport vehicles in this harvesting operation includes the following steps: In step S101, a target transport vehicle is determined from at least one transport vehicle based on the relative position between at least one transport vehicle and the harvester, the load status, and the operational requirements.

[0033] It can be explained that operational requirements may include, but are not limited to, the unloading needs and urgency of the harvester, as well as the task priority and time constraints of the transport vehicles. Based on the operational requirements, the corresponding tasks of the harvesters and transport vehicles that need to be prioritized can be determined. Load status can include the current load and remaining load of the transport vehicles. Based on the load status, the unloading capacity of each transport vehicle can be determined, and then, combined with the unloading needs of the harvester, the required number of transport vehicles can be determined. Relative position can be the Euclidean distance or path distance between the transport vehicle and the harvester. The transport vehicle with the smaller relative position can be identified as the target transport vehicle for priority execution of the cooperative unloading task with the harvester. In this way, the time for the transport vehicle to reach the harvester can be shortened, the waiting time for the harvester to unload can be reduced, thereby improving the overall operational continuity and transportation efficiency.

[0034] Specifically, during harvesting operations, multiple transport vehicles need to coordinate with the harvester to complete the unloading operation. To ensure the efficiency and continuity of the unloading operation, a target transport vehicle can be selected, ensuring that at any given time, only this target transport vehicle is cooperating with the forage harvester to perform the unloading operation, while other transport vehicles are not unloading. Determining the target transport vehicle is the core step of the entire collaborative scheduling method, as it determines the efficiency of the unloading operation.

[0035] The relative position can be determined by the Euclidean distance between the transport vehicle and the harvester. The smaller this distance, the more suitable the transport vehicle is as the target transport vehicle, enabling it to coordinate with the harvester for unloading operations more quickly. When selecting a target transport vehicle, the relative position between the transport vehicle and the harvester must first be considered to determine which transport vehicle is most suitable as the target transport vehicle.

[0036] The load condition of the harvester is also a crucial factor to consider when selecting a target transport vehicle. When a transport vehicle's load is close to its maximum, it is suitable as a target transport vehicle and can be prioritized for unloading tasks or docking with the harvester. Simultaneously, monitoring the load of each transport vehicle ensures that it enters operational status at the appropriate time, preventing unloading operations from being performed empty or being too heavily loaded to complete the task.

[0037] In addition to considering relative position and load status, operational requirements are also a crucial factor in determining the target transport vehicle. During operations, certain work areas may experience higher demands, requiring transport vehicles to quickly complete unloading within those areas. By dynamically scheduling transport vehicles based on operational requirements, suitable transport vehicles can be prioritized when the harvester needs them, thus meeting the unloading needs of the work area.

[0038] As one possible approach, embodiments of this application can mathematically model the relative positions between the transport vehicle and the forage harvester, as well as the load state of the transport vehicle, to quantify the spatial relationship and operational capabilities between them. For example, embodiments of this application can model any transport vehicle... ( The distance between the transport vehicle and the forage harvester is determined by calculating the Euclidean distance, which is calculated using the following formula:

[0039]

[0040]

[0041] in: This shows the current position of the forage harvester. For the first i Current location of the transport vehicle; Let be the Euclidean distance between the two.

[0042]

[0043] in, The target transport vehicle identifier (whether it has been selected as the current unloading transport vehicle); The distance threshold for coordinated unloading operations.

[0044] When the Euclidean distance between the transport vehicle and the harvester And the target transport vehicle markings When, it indicates that the transport vehicle has been selected as the target transport vehicle; when And the target transport vehicle logo When this occurs, it indicates that the transport vehicle does not meet the operating conditions and will be subject to subsequent tasks.

[0045] The embodiments of this application select target transport vehicles based on relative position, load status and operational requirements. They can simultaneously consider the spatial proximity, operational capabilities and task urgency of the transport vehicles to achieve efficient docking between harvesters and transport vehicles and improve the efficiency of multi-transport vehicle collaborative operations.

[0046] In step S102, the target transport vehicle is activated, and the operating status of other transport vehicles is divided according to the transport status of the target transport vehicle. Based on at least one influencing factor between the target transport vehicle and the harvester, the status of each transport vehicle is divided into warehouse waiting status, relay waiting status, collaborative unloading status, and return trip status.

[0047] In the embodiments of this application, activating the target transport vehicle can send a control command to the target transport vehicle to execute a collaborative unloading task, so that it can start to perform collaborative operations with the harvester.

[0048] As can be seen, the operating status can include, but is not limited to, warehouse waiting status, relay waiting status, collaborative unloading status, and return trip status. Activating the target transport vehicle indicates that the target transport vehicle has entered the collaborative unloading status.

[0049] In forage harvesting operations, to ensure the continuity of unloading, in addition to activating the target transport vehicle, it is also necessary to classify the operating status of other transport vehicles based on the status of the activated target transport vehicle. This process can be accomplished by considering factors such as the relative position between the transport vehicle and the harvester, the load status, and operational requirements, to ensure that each transport vehicle participates in the operation or waits at the appropriate time, thereby maximizing operational efficiency. Among these factors, the relative position between the transport vehicle and the harvester is a crucial factor in classifying the status. In this embodiment, the Euclidean distance between each transport vehicle and the harvester can be calculated to determine whether it is close to the working area, thereby determining whether the transport vehicle can enter the collaborative unloading state or whether it is still in the warehouse waiting state. The load status of the transport vehicle is also an important factor in determining its status. Transport vehicles with zero load need to wait for new tasks or take over from the target transport vehicle; conversely, transport vehicles with a load close to the maximum value will return to complete the return task after unloading.

[0050] For example, embodiments of this application can classify the operating state of a transport vehicle based on the relative position between the transport vehicle and the harvester, its load status, and operational requirements. When the load of the transport vehicle is zero and it is far from the work area, the transport vehicle can be classified as a waiting state, ready to enter the collaborative unloading state at any time. When the load of the transport vehicle is zero and it is close to the work area, the transport vehicle can be classified as a relay preparation state, ready to start unloading operations. When the load of the transport vehicle is less than the maximum load and the distance to the harvester is within the work range, the transport vehicle can be classified as a collaborative unloading state, starting to perform the unloading task together with the harvester. When the load of the transport vehicle reaches its maximum value, the transport vehicle completes the unloading task and begins to return, at which point the transport vehicle can be classified as a return trip state.

[0051] Optionally, in one embodiment of this application, the operating states of other transport vehicles are classified according to the transport status of the target transport vehicle. Based on at least one influencing factor between the target transport vehicle and the harvester, the state of each transport vehicle is divided into a warehouse waiting state, a relay waiting state, a collaborative unloading state, and a return trip state. This includes: constructing a transport vehicle operating state discrimination function, wherein the operating state of the transport vehicle is mapped to a warehouse waiting state, a relay waiting state, a collaborative unloading state, or a return trip state, and the transport vehicle operating state discrimination function is: , in, These represent the warehouse waiting status, relay waiting status, collaborative unloading status, and return status, respectively. This represents the current load capacity of the transport vehicle; This refers to the maximum load capacity of the transport vehicle; Forage harvester and the first i The Euclidean distance between the transport vehicles. The distance threshold for coordinated unloading operations.

[0052] Understandable, It can be represented as ,when The transport vehicle was determined to be in a warehouse waiting state; when The transport vehicle was determined to be in a relay waiting state; when The transport vehicle is determined to be in a collaborative unloading state; when The transport vehicle was determined to be in a return trip status.

[0053] Transport vehicle operation status discrimination function The system can dynamically update based on the real-time relative position and load status of the transport vehicles. When the status of a transport vehicle changes, the dispatching system can automatically trigger the corresponding control strategy to ensure that each transport vehicle is always in the most suitable operating state. The control strategy will be described in detail below.

[0054] Through the above methods, the embodiments of this application can realize the division of the operating status of transport vehicles based on relative position, load status and operation requirements, providing a unified status judgment basis for subsequent collaborative scheduling and rotation control.

[0055] In step S103, in response to the target transport vehicle meeting the preset near full load condition, the transport vehicle in the warehouse waiting state or return state is switched to the relay waiting state and moved to the target preparation position, so that when the target transport vehicle is fully loaded, the target transport vehicle is switched to the return state and the transport vehicle in the target preparation position is activated as the new target transport vehicle.

[0056] In the embodiments of this application, the preset near-full load condition can be a certain threshold where the current load of the target transport vehicle reaches the maximum load of the transport vehicle; it can be expressed as the current load of the target transport vehicle. At that time, among them The coefficient can be 0.8 or 0.9, and it can be dynamically adjusted according to the type of transport vehicle, the operating environment, or the scheduling strategy to adapt to the transportation needs under different operating scenarios.

[0057] The control strategy described above will be explained in detail here. When the preset near-full load condition is met, it indicates that the remaining loading capacity of the current target transport vehicle is small and it is close to full load. At this time, the corresponding control strategy can be triggered.

[0058] Specifically, when the current target transport vehicle's load capacity Reaching the threshold At this time, the rotation scheduling control strategy for transport vehicles can be triggered. This threshold sets the time when the target transport vehicle transitions from the collaborative unloading state ( Switch to return trip mode. The conditions are as follows. Additionally, another transport vehicle (is waiting in the warehouse) or return status ) will be in relay waiting state ( Positioning preparation begins. At this point, the new target transport vehicle will gradually approach the work area to ensure a seamless transition of operations.

[0059] When the current target transport vehicle's load reaches its maximum load. At that time, the current target transport vehicle will exit the collaborative unloading state ( Switch to return trip mode. Meanwhile, it will be in a relay waiting state ( ); The transport vehicle is switched to the new target transport vehicle and guided into the collaborative unloading state. ), and begin a new unloading task.

[0060] As a specific example, the collaborative scheduling mode of the harvester and transport vehicle in this application embodiment can be as follows: Figure 2 As shown, firstly, transport vehicle 1 is identified as the target transport vehicle and approaches the harvester. Then, transport vehicle 1 enters the coordinated unloading state. When the load of transport vehicle 1 reaches its maximum load... At that time, transport vehicle 1 entered the return trip mode. The vehicle 1 drives toward the transport truck; at this time, the transport vehicle 2 is identified as the new target transport vehicle and approaches the harvester. This process is repeated, continuously filtering and activating new target transport vehicles until the harvester and the transport vehicle complete the harvesting operation in the work area.

[0061] like Figure 3 As shown in the embodiment of this application, taking two transport vehicles as an example, the coordinated scheduling process of transport vehicles in harvesting operations can be further illustrated, which may include the following steps: S301, Initialize the transport vehicle status.

[0062] Vehicle 1 is identified as the target vehicle. Vehicle 1 is located on S305, and vehicle 2 is located on S303.

[0063] S302, determine whether to trigger transport wheel rotation scheduling.

[0064] If transport vehicle 1 ≥ When the rotation scheduling is triggered, transport vehicle 1 continues on S305, while transport vehicle 2 enters S304; If transport vehicle 1 does not meet the requirements ≥ Transport vehicle 1 and transport vehicle 2 are not moving.

[0065] S303, Warehouse waiting stage: Ready to enter the collaborative unloading state at any time.

[0066] S304, Relay Waiting Stage: Preparing to begin unloading operations.

[0067] S305, Cooperative unloading stage: Performs unloading tasks together with the harvester.

[0068] When the transport vehicle 1 is loaded ≥ At that time, transport vehicle 1 entered S306, and transport vehicle 2 entered S305.

[0069] S306, Return Phase: Complete unloading and begin the return journey.

[0070] S307, Determine whether the harvesting operation is complete.

[0071] If: Transport vehicle 2 enters S306, the process ends.

[0072] If not: Transport vehicle 1 enters S301 and continues the operation cycle.

[0073] The above-mentioned rotation scheduling mechanism can ensure that the harvester does not need to wait during the entire unloading process, guarantee the continuity of the harvester unloading process, avoid operation interruption or waiting, thereby reducing ineffective waiting time, shortening the overall operation cycle, and improving transportation scheduling efficiency and operation efficiency.

[0074] Optionally, in one embodiment of this application, the method for coordinated scheduling of transport vehicles in harvesting operations further includes: generating a planned path that is in a waiting state or a return state based on environmental information of the crop area, so as to drive the transport vehicles that have completed the rotation scheduling along the planned path to the target location.

[0075] Environmental information includes, but is not limited to, topographic information, road and traffic conditions, obstacle distribution, crop distribution, and soil conditions.

[0076] The planned path in this application embodiment can be optimized based on environmental information, such as avoiding obstacles, low-traffic areas and dangerous sections, and combined with road width and traffic capacity to generate a safe and optimal driving path, thereby guiding the transport vehicle to move efficiently and safely during non-operation phases or return trips.

[0077] Understandably, after completing the rotation and scheduling of transport vehicles, it is possible to prepare for the relay. ) or return status ( The system performs route planning for the transport vehicles. Route planning not only determines the shortest path, but also ensures, through multi-objective optimization, that each transport vehicle can travel in the optimal way within the work area, thereby improving operational efficiency and reducing operational conflicts.

[0078] Specifically, in one embodiment of this application, generating a planned path in a waiting or return state includes: constructing the path search problem as a multi-objective optimization problem; based on the multi-objective optimization problem, and under the premise of satisfying preset basic accessibility constraints, constructing a comprehensive cost function in a weighted manner according to the travel distance of the transport vehicle, the time required to reach the target pose, and the risk of operational conflicts between the transport vehicle and the forage harvester and other transport vehicles; during the path search process, selecting the path with the minimum comprehensive cost as the planned path based on the comprehensive cost function.

[0079] It is evident that the multi-objective optimization problem can simultaneously consider minimizing the travel distance of the transport vehicle, minimizing the time required to reach the target pose, minimizing the risk of operational conflicts between the transport vehicle and the harvester and other transport vehicles, and satisfying the preset basic accessibility constraints.

[0080] Among them, the preset basic accessibility constraint refers to the conditional constraints used to ensure that the transport vehicle can smoothly reach the designated working position or unloading point from its current location during the collaborative operation of the transport vehicle and the harvester. This constraint may include, but is not limited to: the existence of a passable path for the transport vehicle within the crop area, the path length or time being within the allowable range, the path not being blocked by obstacles, and the terrain and road conditions meeting the vehicle passage requirements, etc.

[0081] This application embodiment can optimize the task allocation and path planning of transport vehicles based on the travel distance of the transport vehicle, the time required to reach the target position, and the risk of operational conflicts between the transport vehicle and the forage harvester and other transport vehicles, under the premise of meeting the preset basic accessibility constraints. In order to select the planned path with the shortest travel distance, the optimal arrival time and the lowest risk of operational conflicts while ensuring the continuity of harvester operation, so as to avoid conflicts between multiple transport vehicles at path intersections or in the work area, thereby improving the efficiency and safety of multi-vehicle collaborative operation.

[0082] As a concrete example, the comprehensive cost function can be expressed as: , in, 、 、 These are the weighting coefficients corresponding to each cost item; Indicates that the transport vehicle is at the node n Empty running costs at the location; Indicates that the transport vehicle is at the node n Obstacles at the location incur penalties; Indicates the penalty for late arrival of the transport vehicle at the target position; Indicates that the transport vehicle is at the node n The cost of fuel consumption at that location.

[0083] in, It is directly proportional to the distance traveled by the transport vehicle; It can be used to prevent transport vehicles from avoiding obstacles in the work area; It can be used to reduce the impact of untimely arrival of transport vehicles on the continuity of unloading; It can be used to reflect the energy consumption of transport vehicles under different loads and driving conditions.

[0084] By using a weighted cost function, the path planning process takes into account multiple optimization objectives and selects the path with the lowest cost as the vehicle's travel route. This optimizes the vehicle's route and ensures efficient and safe operation in complex working environments.

[0085] As another possible way to achieve this, such as Figure 4As shown, the collaborative scheduling method for transport vehicles in the harvesting operation of this application embodiment can be divided into the following steps: S401. Based on the relative position, load status and operational requirements between the transport vehicle and the forage harvester, a target transport vehicle is determined. The target transport vehicle will cooperate with the forage harvester in unloading operations during the harvester's operation, while the other transport vehicles are in a non-unloading state.

[0086] S402: After determining the target transport vehicle, the operating status of other transport vehicles is classified based on the status of the target transport vehicle. At the same time, based on factors such as the relative position, distance, and load between the transport vehicle and the forage harvester, the status of each transport vehicle is classified into warehouse waiting status, relay waiting status, collaborative unloading status, and return status.

[0087] S403: When the target transport vehicle is close to full load, another transport vehicle is switched from warehouse waiting or return trip to relay waiting state in advance to prepare its position; when the target transport vehicle reaches full load, it is switched to return trip state, and the transport vehicle in relay waiting state is switched to the new target transport vehicle to ensure seamless connection of unloading operations.

[0088] After completing the rotation scheduling of transport vehicles, S404 uses path search to plan routes for transport vehicles that are in a relay waiting state or return state, based on the environmental information of the work area. The route planning process weighs and integrates multiple optimization objectives (such as travel distance, arrival time, and risk of work conflict) to select the route with the lowest cost, so as to ensure the efficient and safe driving of transport vehicles in complex work environments.

[0089] In summary, the embodiments of this application can perform path planning based on the above path search to weigh various factors in a dynamic environment, thereby ensuring that when multiple transport vehicles are operating simultaneously, the various objectives of path selection can be balanced, and ensuring that the transport vehicles will not affect the operation progress due to operation conflicts or low efficiency.

[0090] According to the collaborative scheduling method for transport vehicles in harvesting operations proposed in this application, by determining the target transport vehicle and then determining the movement status of other transport vehicles, when the target transport vehicle is fully loaded, the target transport vehicle is switched to the return trip state, and the transport vehicle in the target preparation position is activated as the new target transport vehicle. Orderly scheduling can be performed according to the state division, allowing seamless switching to the next transport vehicle when the target transport vehicle is fully loaded, avoiding time waste caused by waiting for transport vehicles and ensuring the continuity of harvesting operations. Simultaneously, in complex operation scenarios involving the collaboration of multiple transport vehicles, disordered vehicle scheduling can be transformed into ordered state machine management, precisely controlling the movement status of each transport vehicle, effectively shortening transport vehicle turnaround time, improving overall operation efficiency, and reducing the risk of collisions and operational conflicts caused by chaotic scheduling through real-time monitoring and orderly switching of vehicle states, significantly enhancing the safety of multi-vehicle collaborative operations.

[0091] Next, referring to the accompanying drawings, a coordinated scheduling device for transport vehicles in harvesting operations according to an embodiment of this application is described.

[0092] Figure 5 This is a block diagram of a collaborative scheduling device for transport vehicles in a harvesting operation according to an embodiment of this application.

[0093] like Figure 5 As shown, the collaborative scheduling device 10 for transport vehicles in this harvesting operation includes: a determination module 100, a division module 200, and a scheduling module 300.

[0094] The determination module 100 is used to determine the target transport vehicle from at least one transport vehicle based on the relative position between at least one transport vehicle and the harvester, the load status, and the operational requirements.

[0095] The segmentation module 200 is used to activate the target transport vehicle and segment the operating status of other transport vehicles according to the transport status of the target transport vehicle. Based on at least one influencing factor between the target transport vehicle and the harvester, the status of each transport vehicle is divided into warehouse waiting status, relay waiting status, collaborative unloading status, and return status.

[0096] The scheduling module 300 is used to switch the transport vehicle in the warehouse waiting state or return state to the relay waiting state in response to the target transport vehicle meeting the preset near full load condition, and move it to the target preparation position, so that when the target transport vehicle is fully loaded, the target transport vehicle is switched to the return state and the transport vehicle in the target preparation position is activated as the new target transport vehicle.

[0097] Optionally, in one embodiment of this application, the collaborative scheduling device 10 for transport vehicles in harvesting operations further includes a generation module.

[0098] The generation module is used to generate planned routes based on the environmental information of the crop area, so that the transport vehicles that have completed the rotation scheduling can travel along the planned routes to the target location.

[0099] Optionally, in one embodiment of this application, the generation module includes: a first building unit, a second building unit, and a selection unit.

[0100] The first building unit is used to transform the path search problem into a multi-objective optimization problem.

[0101] The second construction unit is used to construct a comprehensive cost function based on a multi-objective optimization problem, under the premise of satisfying the preset basic accessibility constraints, by weighting the distance traveled by the transport vehicle, the time required to reach the target pose, and the risk of operational conflicts between the transport vehicle and the forage harvester and other transport vehicles.

[0102] The selection unit is used to select the path with the minimum comprehensive cost as the planned path based on the comprehensive cost function during the path search process.

[0103] Optionally, in one embodiment of this application, the comprehensive cost function is: , in, 、 、 These are the weighting coefficients corresponding to each cost item; Indicates that the transport vehicle is at the node n Empty running costs at the location; Indicates that the transport vehicle is at the node n Obstacles at the location incur penalties; Indicates the penalty for late arrival of the transport vehicle at the target position; Indicates that the transport vehicle is at the node n The cost of fuel consumption at that location.

[0104] Optionally, in one embodiment of this application, the partitioning module 200 includes: a third building unit.

[0105] The third construction unit is used to construct the transport vehicle operation status discrimination function, wherein the transport vehicle operation status is mapped to warehouse waiting status, relay waiting status, collaborative unloading status, or return trip status, and the transport vehicle operation status discrimination function is: , in, These represent the warehouse waiting status, relay waiting status, collaborative unloading status, and return status, respectively. This represents the current load capacity of the transport vehicle; This refers to the maximum load capacity of the transport vehicle; Forage harvester and the first i The Euclidean distance between the transport vehicles. The distance threshold for coordinated unloading operations.

[0106] It should be noted that the explanation of the above-described embodiment of the method for coordinated scheduling of transport vehicles in harvesting operations also applies to the coordinated scheduling device for transport vehicles in harvesting operations in this embodiment, and will not be repeated here.

[0107] According to the collaborative scheduling device for transport vehicles in harvesting operations proposed in this application, by determining the target transport vehicle and then determining the movement status of other transport vehicles, the target transport vehicle is switched to the return state when it is fully loaded, and the transport vehicle in the target preparation position is activated as the new target transport vehicle. It can be scheduled in an orderly manner according to the division of the state, and can seamlessly switch to the next transport vehicle when the target transport vehicle is fully loaded, avoiding the time waste caused by waiting for transport vehicles and ensuring the continuity of harvesting operations. At the same time, in complex operation scenarios involving the coordination of multiple transport vehicles, it can transform disordered vehicle scheduling into orderly state machine management, accurately control the movement status of each transport vehicle, effectively shorten the turnaround time of transport vehicles, and improve the overall operation efficiency.

[0108] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include: The memory 601, the processor 602, and the computer program stored on the memory 601 and capable of running on the processor 602.

[0109] When the processor 602 executes the program, it implements the collaborative scheduling method for transport vehicles in the harvesting operation provided in the above embodiments.

[0110] Furthermore, electronic devices also include: Communication interface 603 is used for communication between memory 601 and processor 602.

[0111] The memory 601 is used to store computer programs that can run on the processor 602.

[0112] The memory 601 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0113] If the memory 601, processor 602, and communication interface 603 are implemented independently, then the communication interface 603, memory 601, and processor 602 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 6 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0114] Optionally, in a specific implementation, if the memory 601, processor 602, and communication interface 603 are integrated on a single chip, then the memory 601, processor 602, and communication interface 603 can communicate with each other through an internal interface.

[0115] The processor 602 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0116] This embodiment also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for the coordinated scheduling of transport vehicles in harvesting operations.

[0117] This application also provides a computer program product, including a computer program that can run computer instructions. When the computer instructions are executed by a processor, they implement the collaborative scheduling method for transport vehicles in harvesting operations provided in this application.

[0118] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0119] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0120] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0121] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0122] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, it can be implemented using any one or more of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0123] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0124] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0125] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for the coordinated scheduling of transport vehicles in harvesting operations, characterized in that, Includes the following steps: Based on the relative position between at least one transport vehicle and the harvester, the load status, and the operational requirements, a target transport vehicle is determined from the at least one transport vehicle. Activate the target transport vehicle, and classify the operating status of other transport vehicles according to the transport status of the target transport vehicle. Based on at least one influencing factor between the target transport vehicle and the harvester, classify the status of each transport vehicle into warehouse waiting status, relay waiting status, collaborative unloading status, and return trip status. In response to the target transport vehicle meeting the preset near full load condition, the transport vehicle in the warehouse waiting state or the return state is switched to the relay waiting state and moved to the target preparation position, so that when the target transport vehicle is fully loaded, the target transport vehicle is switched to the return state and the transport vehicle in the target preparation position is activated as the new target transport vehicle.

2. The method according to claim 1, characterized in that, Also includes: Based on the environmental information of the crop area, a planned route is generated for the waiting state or the return state, so that the transport vehicle that has completed the rotation scheduling can travel along the planned route to the target location.

3. The method according to claim 2, characterized in that, The generation of the planned path in the waiting state or the return state includes: The path search problem is shaped into a multi-objective optimization problem; Based on the multi-objective optimization problem, under the premise of satisfying the preset basic accessibility constraints, a comprehensive cost function is constructed by weighting the travel distance of the transport vehicle, the time required to reach the target pose, and the risk of operational conflicts between the transport vehicle and the forage harvester and other transport vehicles. During the path search process, the path with the minimum comprehensive cost is selected as the planned path based on the comprehensive cost function.

4. The method according to claim 3, characterized in that, The comprehensive cost function is: ， in, These are the weighting coefficients corresponding to each cost item; Indicates that the transport vehicle is at the node n Empty running costs at the location; Indicates that the transport vehicle is at the node n Obstacles at the location incur penalties; Indicates the penalty for late arrival of the transport vehicle at the target position; Indicates that the transport vehicle is at the node n The cost of fuel consumption at that location.

5. The method according to claim 1, characterized in that, The process of classifying the operating states of other transport vehicles based on the transport status of the target transport vehicle, and classifying the state of each transport vehicle into warehouse waiting state, relay waiting state, collaborative unloading state, and return trip state based on at least one influencing factor between the target transport vehicle and the harvester, includes: Construct a vehicle operation status discrimination function, wherein the vehicle operation status is mapped to the warehouse waiting state, the relay waiting state, the collaborative unloading state, or the return trip state, and the vehicle operation status discrimination function is: ， in, These represent the warehouse waiting status, relay waiting status, collaborative unloading status, and return status, respectively. This represents the current load capacity of the transport vehicle. This refers to the maximum load capacity of the transport vehicle; Forage harvester and the first i The Euclidean distance between the transport vehicles. The distance threshold for coordinated unloading operations.

6. A collaborative scheduling device for transport vehicles in harvesting operations, characterized in that, include: A determination module is used to determine a target transport vehicle from the at least one transport vehicle based on the relative position between at least one transport vehicle and the harvester, the load status, and the operational requirements. The segmentation module is used to activate the target transport vehicle and segment the operating status of other transport vehicles according to the transport status of the target transport vehicle. Based on at least one influencing factor between the target transport vehicle and the harvester, the status of each transport vehicle is divided into warehouse waiting status, relay waiting status, collaborative unloading status, and return status. The scheduling module is used to switch the transport vehicle in the warehouse waiting state or the return trip state to the relay waiting state in response to the target transport vehicle meeting the preset near full load condition, and move it to the target preparation position, so that when the target transport vehicle is fully loaded, the target transport vehicle is switched to the return trip state, and the transport vehicle in the target preparation position is activated as the new target transport vehicle.

7. The apparatus according to claim 6, characterized in that, Also includes: The generation module is used to generate a planned path based on the environmental information of the crop area, indicating whether the vehicle is in the waiting state or the return state, so that the transport vehicle that has completed the rotation scheduling can travel along the planned path to the target location.

8. An electronic device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and capable of running on the processor, the processor executing the program to implement the method for coordinated scheduling of transport vehicles in harvesting operations as described in any one of claims 1-5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the collaborative scheduling method for transport vehicles in harvesting operations as described in any one of claims 1-5.

10. A computer program product, comprising a computer program, characterized in that, The computer program is executed to implement the collaborative scheduling method for transport vehicles in harvesting operations as described in any one of claims 1-5.

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