A method and system for cooperative scheduling control of unmanned loaders

Abstract

The application discloses a kind of unmanned loader cooperative scheduling control method and system, the method includes: step 101, the environmental data of loading site is acquired in real time, constructs the dynamic environment map of loading site, and labels obstacle, the position of each unmanned loader, material pile and dynamic target;Step 102, global task is decomposed into subtask, and subtask is distributed to each unmanned loader, when unmanned loader fails or subtask changes, reassign subtask;Step 103, the global path of each unmanned loader is generated, when monitoring obstacle and / or dynamic target, avoid collision by the way of local re-planning;Step 104, multiple unmanned loaders are queued, and time synchronization error function, path following error function and direction coordination error function are set, and the cooperative control between unmanned loader is carried out.

Description

Technical Field

[0001] This invention belongs to the field of collaborative scheduling technology for unmanned loaders, and more specifically, relates to a collaborative scheduling control method and system for unmanned loaders. Background Technology

[0002] Traditional loader operations rely on manual operation, which has significant limitations. Specifically, operational efficiency is constrained by the driver's experience and physical limitations, manual operation carries high safety risks, and there is a continuous pressure of labor costs. Existing unmanned loader technologies employ a discrete, independent operation mode, lacking clustered intelligent collaborative scheduling capabilities, making it difficult to cope with dynamic operational demands under complex conditions. In multi-machine collaborative operation scenarios, existing systems suffer from three major technical problems: first, the lack of a global task allocation mechanism leads to uneven equipment load; second, frequent conflicts in local motion planning cause path interference; and third, insufficient equipment resource utilization results in wasted capacity. Furthermore, existing scheduling systems generally exhibit a technical shortcoming of delayed decision-making response when facing dynamic environmental disturbances.

[0003] Therefore, there is an urgent need for a technical solution that can solve the above technical problems. Summary of the Invention

[0004] To address the above technical problems, this invention proposes a collaborative scheduling and control method for unmanned loaders, comprising:

[0005] Step 101: Acquire environmental data of the loading site in real time, construct a dynamic environmental map of the loading site, and mark obstacles, the location of each unmanned loader, material piles, and dynamic targets.

[0006] Step 102: Decompose the global task into subtasks and assign the subtasks to each unmanned loader. When an unmanned loader malfunctions or a subtask changes, the subtasks are reassigned.

[0007] Step 103: Generate a global path for each unmanned loader. When obstacles and / or dynamic targets are detected, avoid collisions through local replanning.

[0008] Step 104: Form a formation of multiple unmanned loaders and set time synchronization error function, path following error function and direction coordination error function to perform collaborative control between the unmanned loaders.

[0009] Furthermore, it also includes: setting up a remote monitoring interface, through which users can obtain abnormal alarms of the unmanned loader, and through the manual takeover entry on the remote monitoring interface to take over the unmanned loader.

[0010] Furthermore, step 103 also includes ensuring that the paths of multiple unmanned loaders are conflict-free through spatiotemporal corridors or distributed negotiation.

[0011] Furthermore, it also includes: real-time monitoring of the health status of each unmanned loader, wherein the health status includes: vibration, battery temperature and hydraulic pressure of the unmanned loader.

[0012] Furthermore, this also includes: adjusting the motor power of the unmanned loader according to the task intensity of the sub-tasks; and planning the charging timing of the unmanned loader in combination with electricity price periods and task queues.

[0013] Furthermore, the time synchronization error function includes:

[0014] ,

[0015] in, For time synchronization error, The number of unmanned loaders, For the first The operation progress timestamp of an unmanned loader For the first The operation progress timestamp of an unmanned loader The first adjustment factor for time synchronization error. This is the second adjustment factor for time synchronization error.

[0016] Furthermore, the path following error function includes:

[0017] ,

[0018] in, This is the path following error. For the first The location of the unmanned loader For the first The location of the unmanned loader This is the first adjustment factor for the path following error. This is the second adjustment factor for the path following error. This is the third adjustment factor for the path following error.

[0019] Furthermore, the orientation coordination error function includes:

[0020] ,

[0021] in, For directional coordination error, For the first The heading angle of an unmanned loader For the first An unmanned loader, The first adjustment factor for directional coordination error. This is the second adjustment factor for directional coordination error.

[0022] Furthermore, set a target time. By continuously adjusting the task execution sequence of each unmanned loader, minimize;

[0023] The path of each unmanned loader is dynamically adjusted through a path planning algorithm, so that... and minimize.

[0024] This invention also proposes a collaborative scheduling and control system for unmanned loaders, comprising:

[0025] The environmental modeling module is used to acquire environmental data of the loading site in real time, build a dynamic environmental map of the loading site, and mark obstacles, the location of each unmanned loader, material piles and dynamic targets.

[0026] The task allocation module is used to break down global tasks into subtasks and assign subtasks to each unmanned loader. When an unmanned loader malfunctions or a subtask changes, the subtasks are reassigned.

[0027] The path planning module is used to generate a global path for each unmanned loader. When obstacles and / or dynamic targets are detected, collisions are avoided through local replanning.

[0028] The collaboration module is used to group multiple unmanned loaders together and set time synchronization error function, path following error function and direction coordination error function to perform collaborative control between unmanned loaders.

[0029] In summary, the technical solutions conceived by this invention have the following beneficial effects compared with the prior art:

[0030] This invention constructs a closed-loop collaborative framework covering the entire process of "environmental perception → task allocation → path planning → collaborative control → real-time communication → safety monitoring → energy management," breaking through the traditional independent operation mode and improving the working efficiency of unmanned loaders. Attached Figure Description

[0031] Figure 1 This is a flowchart of the method in Embodiment 1 of the present invention;

[0032] Figure 2 This is a system structure diagram of Embodiment 2 of the present invention. Detailed Implementation

[0033] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0034] The method provided by this invention can be implemented in a terminal environment that may include one or more of the following components: a processor, a storage medium, and a display screen. The storage medium stores at least one instruction, which is loaded and executed by the processor to implement the method described in the following embodiments.

[0035] A processor may include one or more processing cores. The processor uses various interfaces and lines to connect various parts of the terminal, and performs various functions and processes data by running or executing instructions, programs, code sets or instruction sets stored in the storage medium, and by calling data stored in the storage medium.

[0036] Storage media can include random access memory (RAM) or read-only memory (ROM). Storage media can be used to store instructions, programs, code, code sets, or instructions.

[0037] The display screen is used to show the user interface of each application.

[0038] In addition, those skilled in the art will understand that the structure of the terminal described above does not constitute a limitation on the terminal. The terminal may include more or fewer components, or combine certain components, or have different component arrangements. For example, the terminal may also include radio frequency circuits, input units, sensors, audio circuits, power supplies, and other components, which will not be described in detail here.

[0039] Example 1

[0040] like Figure 1 This embodiment proposes a collaborative scheduling and control method for unmanned loaders. The unmanned loader is an automated mechanical device used in automated mines, construction sites, logistics warehouses, and other locations. By integrating sensors, artificial intelligence, and control algorithms, it can complete loading, transportation, and unloading tasks without human intervention. This includes:

[0041] Step 101: Acquire environmental data of the loading site in real time, construct a dynamic environmental map of the loading site, and mark obstacles, the location of each unmanned loader, material piles, and dynamic targets.

[0042] Preferably, environmental data is acquired in real time through sensors such as LiDAR, cameras, millimeter-wave radar, and IMU. Visual semantic segmentation and LiDAR point cloud are used to construct a dynamic environmental map of the loading site. Furthermore, the data from multiple sensors are fused to improve positioning accuracy and ensure the real-time performance and reliability of the dynamic environmental map.

[0043] Preferably, SLAM technology is used to generate high-precision maps, marking obstacles, loader positions, material piles, and dynamic targets (such as other vehicles).

[0044] Step 102: Decompose the global task into subtasks and assign the subtasks to each unmanned loader. When an unmanned loader malfunctions or a subtask changes, the subtasks are reassigned.

[0045] Preferably, the global task (such as "loading and transporting 100 tons of sand and gravel") is broken down into sub-tasks (such as area division and transportation frequency), and tasks are dynamically allocated using an algorithm based on machine status (location, power, load capacity), task priority, and environmental constraints.

[0046] Step 103: Generate a global path for each unmanned loader. When obstacles and / or dynamic targets are detected, avoid collisions through local replanning.

[0047] Preferably, an initial optimal path is planned for each unmanned loader, and obstacles are monitored in real time, with local replanning used to avoid collisions.

[0048] Specifically, step 103 also includes: ensuring that the paths of multiple unmanned loaders are not conflicting through spatiotemporal corridors or distributed negotiation.

[0049] Step 104: Form a formation of multiple unmanned loaders and set time synchronization error function, path following error function and direction coordination error function to perform collaborative control between the unmanned loaders.

[0050] After step 104, which involves coordinated control of multiple unmanned loaders, the efficiency of the unmanned loaders is greatly improved, as shown in the table below:

[0051]

[0052] (Taking three unmanned loaders working together as an example)

[0053] Preferably, loading, turning, and unloading actions are coordinated to ensure operational continuity.

[0054] When multiple unmanned loaders operate together in the same area, resource competition can be avoided by arranging action sequences.

[0055] Specifically, this also includes: adjusting the motor power of the unmanned loader according to the task intensity of the sub-tasks; and planning the charging time of the unmanned loader in combination with the electricity price period and task queue.

[0056] Specifically, this also includes: real-time monitoring of the health status of each unmanned loader, wherein the health status includes: vibration, battery temperature and hydraulic pressure of the unmanned loader.

[0057] Preferably, when the unmanned loader encounters an emergency, it triggers emergency braking, clears the path, or switches to the backup control system.

[0058] Specifically, it also includes: setting up a remote monitoring interface, through which users can obtain abnormal alarms of the unmanned loader, and through the manual takeover entry on the remote monitoring interface to take over the unmanned loader.

[0059] Specifically, the time synchronization error function includes:

[0060] ,

[0061] in, For time synchronization error, The number of unmanned loaders, For the first The operation progress timestamp of an unmanned loader For the first The operation progress timestamp of an unmanned loader The first adjustment factor for time synchronization error. This is the second adjustment factor for time synchronization error.

[0062] Specifically, the path following error function includes:

[0063] ,

[0064] in, This is the path following error. For the first The location of the unmanned loader For the first The location of the unmanned loader This is the first adjustment factor for the path following error. This is the second adjustment factor for the path following error. This is the third adjustment factor for the path following error.

[0065] Specifically, the direction coordination error function includes:

[0066] ,

[0067] in, For directional coordination error, For the first The heading angle of an unmanned loader For the first An unmanned loader, The first adjustment factor for directional coordination error. This is the second adjustment factor for directional coordination error.

[0068] Specifically, a target time is set, and the task execution sequence of each unmanned loader is continuously adjusted to achieve the desired result. minimize;

[0069] The path of each unmanned loader is dynamically adjusted through path planning algorithms (such as A*, DWA, or RRT) to enable... and minimize.

[0070] Preferably, a hybrid topology is adopted, utilizing 5G / dedicated wireless networks to achieve low-latency information transmission between the remote end (remote monitoring interface) and the unmanned loader;

[0071] Standardized message format for transmitting key information such as location, status, and task progress;

[0072] The NTP or PTP protocol is used to ensure that the timestamps of multiple unmanned loaders are consistent, thus avoiding coordination errors.

[0073] Preferably, performance evaluation is performed when multiple unmanned loaders work together: record indicators such as task completion time, energy consumption, and number of conflicts, and optimize parameters through offline simulation (such as digital twins).

[0074] Preferably, task allocation and path planning models are iteratively improved based on historical data (such as online machine learning).

[0075] Example 2

[0076] like Figure 2 As shown, this embodiment proposes a collaborative scheduling and control system for unmanned loaders, including:

[0077] The environmental modeling module is used to acquire environmental data of the loading site in real time, build a dynamic environmental map of the loading site, and mark obstacles, the location of each unmanned loader, material piles and dynamic targets.

[0078] The task allocation module is used to break down global tasks into subtasks and assign subtasks to each unmanned loader. When an unmanned loader malfunctions or a subtask changes, the subtasks are reassigned.

[0079] The path planning module is used to generate a global path for each unmanned loader. When obstacles and / or dynamic targets are detected, collisions are avoided through local replanning.

[0080] Specifically, the path planning module also includes ensuring that the paths of multiple unmanned loaders do not conflict through spatiotemporal corridors or distributed negotiation.

[0081] The collaboration module is used to group multiple unmanned loaders together and set time synchronization error function, path following error function and direction coordination error function to perform collaborative control between unmanned loaders.

[0082] Specifically, this also includes: adjusting the motor power of the unmanned loader according to the task intensity of the sub-tasks; and planning the charging time of the unmanned loader in combination with the electricity price period and task queue.

[0083] Specifically, this also includes: real-time monitoring of the health status of each unmanned loader, wherein the health status includes: vibration, battery temperature and hydraulic pressure of the unmanned loader.

[0084] Specifically, it also includes: setting up a remote monitoring interface, through which users can obtain abnormal alarms of the unmanned loader, and through the manual takeover entry on the remote monitoring interface to take over the unmanned loader.

[0085] Specifically, the time synchronization error function includes:

[0086] ,

[0087] in, For time synchronization error, The number of unmanned loaders, For the first The operation progress timestamp of an unmanned loader For the first The operation progress timestamp of an unmanned loader The first adjustment factor for time synchronization error. This is the second adjustment factor for time synchronization error.

[0088] Specifically, the path following error function includes:

[0089] ,

[0090] in, This is the path following error. For the first The location of the unmanned loader For the first The location of the unmanned loader This is the first adjustment factor for the path following error. This is the second adjustment factor for the path following error. This is the third adjustment factor for the path following error.

[0091] Specifically, the direction coordination error function includes:

[0092] ,

[0093] in, For directional coordination error, For the first The heading angle of an unmanned loader For the first An unmanned loader, The first adjustment factor for directional coordination error. This is the second adjustment factor for directional coordination error.

[0094] Specifically, set a target time. By continuously adjusting the task execution sequence of each unmanned loader, minimize;

[0095] The path of each unmanned loader is dynamically adjusted through a path planning algorithm, so that... and minimize.

[0096] Example 3

[0097] This invention also proposes a storage medium for storing multiple instructions, which are used to implement the aforementioned collaborative scheduling and control method for unmanned loaders.

[0098] Optionally, in this embodiment, the storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals.

[0099] Optionally, in this embodiment, the storage medium is configured to store program code for performing the following steps: Step 101, acquire environmental data of the loading site in real time, construct a dynamic environmental map of the loading site, and mark obstacles, the location of each unmanned loader, material piles and dynamic targets.

[0100] Step 102: Decompose the global task into subtasks and assign the subtasks to each unmanned loader. When an unmanned loader malfunctions or a subtask changes, the subtasks are reassigned.

[0101] Step 103: Generate a global path for each unmanned loader. When obstacles and / or dynamic targets are detected, avoid collisions through local replanning.

[0102] Specifically, step 103 also includes: ensuring that the paths of multiple unmanned loaders are not conflicting through spatiotemporal corridors or distributed negotiation.

[0103] Step 104: Form a formation of multiple unmanned loaders and set time synchronization error function, path following error function and direction coordination error function to perform collaborative control between the unmanned loaders.

[0104] Specifically, this also includes: adjusting the motor power of the unmanned loader according to the task intensity of the sub-tasks; and planning the charging time of the unmanned loader in combination with the electricity price period and task queue.

[0105] Specifically, this also includes: real-time monitoring of the health status of each unmanned loader, wherein the health status includes: vibration, battery temperature and hydraulic pressure of the unmanned loader.

[0106] Specifically, it also includes: setting up a remote monitoring interface, through which users can obtain abnormal alarms of the unmanned loader, and through the manual takeover entry on the remote monitoring interface to take over the unmanned loader.

[0107] Specifically, the time synchronization error function includes:

[0108] ,

[0109] in, For time synchronization error, The number of unmanned loaders, For the first The operation progress timestamp of an unmanned loader For the first The operation progress timestamp of an unmanned loader The first adjustment factor for time synchronization error. This is the second adjustment factor for time synchronization error.

[0110] Specifically, the path following error function includes:

[0111] ,

[0112] in, This is the path following error. For the first The location of the unmanned loader For the first The location of the unmanned loader This is the first adjustment factor for the path following error. This is the second adjustment factor for the path following error. This is the third adjustment factor for the path following error.

[0113] Specifically, the direction coordination error function includes:

[0114] ,

[0115] in, For directional coordination error, For the first The heading angle of an unmanned loader For the first An unmanned loader, The first adjustment factor for directional coordination error. This is the second adjustment factor for directional coordination error.

[0116] Specifically, set a target time. By continuously adjusting the task execution sequence of each unmanned loader, minimize;

[0117] The path of each unmanned loader is dynamically adjusted through a path planning algorithm, so that... and minimize.

[0118] Example 4

[0119] This invention also proposes an electronic device, including a processor and a storage medium connected to the processor. The storage medium stores multiple instructions, which can be loaded and executed by the processor to enable the processor to execute the aforementioned unmanned loader collaborative scheduling and control method.

[0120] Specifically, the electronic device in this embodiment can be a computer terminal, which may include one or more processors and a storage medium.

[0121] The storage medium can be used to store software programs and modules, such as the collaborative scheduling and control method for an unmanned loader in this embodiment of the invention. The corresponding program instructions / modules are executed by the processor through running the software programs and modules stored in the storage medium, thereby performing various functional applications and data processing, thus realizing the aforementioned collaborative scheduling and control method for an unmanned loader. The storage medium may include high-speed random access storage media, and may also include non-volatile storage media, such as one or more magnetic storage systems, flash memory, or other non-volatile solid-state storage media. In some instances, the storage medium may further include storage media remotely configured relative to the processor, which can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0122] The processor can call the information and application stored in the storage medium through the transmission system to perform the following steps: Step 101, acquire environmental data of the loading site in real time, construct a dynamic environmental map of the loading site, and mark obstacles, the location of each unmanned loader, material piles and dynamic targets;

[0123] Step 102: Decompose the global task into subtasks and assign the subtasks to each unmanned loader. When an unmanned loader malfunctions or a subtask changes, the subtasks are reassigned.

[0124] Step 103: Generate a global path for each unmanned loader. When obstacles and / or dynamic targets are detected, avoid collisions through local replanning.

[0125] Specifically, step 103 also includes: ensuring that the paths of multiple unmanned loaders are not conflicting through spatiotemporal corridors or distributed negotiation.

[0126] Step 104: Form a formation of multiple unmanned loaders and set time synchronization error function, path following error function and direction coordination error function to perform collaborative control between the unmanned loaders.

[0127] Specifically, this also includes: adjusting the motor power of the unmanned loader according to the task intensity of the sub-tasks; and planning the charging time of the unmanned loader in combination with the electricity price period and task queue.

[0128] Specifically, this also includes: real-time monitoring of the health status of each unmanned loader, wherein the health status includes: vibration, battery temperature and hydraulic pressure of the unmanned loader.

[0129] Specifically, it also includes: setting up a remote monitoring interface, through which users can obtain abnormal alarms of the unmanned loader, and through the manual takeover entry on the remote monitoring interface to take over the unmanned loader.

[0130] Specifically, the time synchronization error function includes:

[0131] ,

[0132] in, For time synchronization error, The number of unmanned loaders, For the first The operation progress timestamp of an unmanned loader For the first The operation progress timestamp of an unmanned loader The first adjustment factor for time synchronization error. This is the second adjustment factor for time synchronization error.

[0133] Specifically, the path following error function includes:

[0134] ,

[0135] in, This is the path following error. For the first The location of the unmanned loader For the first The location of the unmanned loader This is the first adjustment factor for the path following error. This is the second adjustment factor for the path following error. This is the third adjustment factor for the path following error.

[0136] Specifically, the direction coordination error function includes:

[0137] ,

[0138] in, For directional coordination error, For the first The heading angle of an unmanned loader For the first An unmanned loader, The first adjustment factor for directional coordination error. This is the second adjustment factor for directional coordination error.

[0139] Specifically, set a target time. By continuously adjusting the task execution sequence of each unmanned loader, minimize;

[0140] The path of each unmanned loader is dynamically adjusted through a path planning algorithm, so that... and minimize.

[0141] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0142] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0143] In the several embodiments provided by this invention, it should be understood that the disclosed technical content can be implemented in other ways. The system embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection between units or modules, and may be electrical or other forms.

[0144] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0145] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0146] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes: USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, optical disks, and other media capable of storing program code.

[0147] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A collaborative scheduling and control method for unmanned loaders, characterized in that, include: Step 101: Acquire environmental data of the loading site in real time, construct a dynamic environmental map of the loading site, and mark obstacles, the location of each unmanned loader, material piles, and dynamic targets. Step 102: Decompose the global task into subtasks and assign the subtasks to each unmanned loader. When an unmanned loader malfunctions or a subtask changes, the subtasks are reassigned. Step 103: Generate a global path for each unmanned loader. When obstacles and / or dynamic targets are detected, avoid collisions through local replanning. Step 104: Form a formation of multiple unmanned loaders and set time synchronization error function, path following error function and direction coordination error function to perform collaborative control between the unmanned loaders; The orientation coordination error function includes: ， in, For directional coordination error, For the first The heading angle of an unmanned loader For the first An unmanned loader, The first adjustment factor for directional coordination error. This is the second adjustment factor for the directional coordination error. This refers to the number of unmanned loaders.

2. The method for collaborative scheduling and control of an unmanned loader as described in claim 1, characterized in that, Also includes: A remote monitoring interface is set up, through which users can obtain abnormal alarms from the unmanned loader and take over the unmanned loader through the manual takeover entry on the remote monitoring interface.

3. The method for collaborative scheduling and control of an unmanned loader as described in claim 1, characterized in that, Step 103 also includes ensuring that the paths of multiple unmanned loaders are conflict-free through spatiotemporal corridors or distributed negotiation.

4. The method for collaborative scheduling and control of an unmanned loader as described in claim 1, characterized in that, Also includes: The health status of each unmanned loader is monitored in real time, including the vibration, battery temperature, and hydraulic pressure of the unmanned loader.

5. The method for collaborative scheduling and control of an unmanned loader as described in claim 1, characterized in that, Also includes: Adjust the motor power of the unmanned loader according to the task intensity of the sub-tasks; plan the charging time of the unmanned loader in combination with the electricity price period and task queue.

6. The method for collaborative scheduling and control of an unmanned loader as described in claim 1, characterized in that, The time synchronization error function includes: ， in, For time synchronization error, The number of unmanned loaders, For the first The operation progress timestamp of an unmanned loader For the first The operation progress timestamp of an unmanned loader The first adjustment factor for time synchronization error. This is the second adjustment factor for time synchronization error.

7. The method for collaborative scheduling and control of an unmanned loader as described in claim 6, characterized in that, The path following error function includes: ， in, This is the path following error. For the first The location of the unmanned loader For the first The location of the unmanned loader This is the first adjustment factor for the path following error. This is the second adjustment factor for the path following error. This is the third adjustment factor for the path following error.

8. The method for collaborative scheduling and control of an unmanned loader as described in claim 1, characterized in that, Set target time By continuously adjusting the task execution sequence of each unmanned loader, minimize; The path of each unmanned loader is dynamically adjusted through a path planning algorithm, so that... and minimize.

9. A collaborative scheduling and control system for unmanned loaders, characterized in that, include: The environmental modeling module is used to acquire environmental data of the loading site in real time, build a dynamic environmental map of the loading site, and mark obstacles, the location of each unmanned loader, material piles and dynamic targets. The task allocation module is used to break down global tasks into subtasks and assign subtasks to each unmanned loader. When an unmanned loader malfunctions or a subtask changes, the subtasks are reassigned. The path planning module is used to generate a global path for each unmanned loader. When obstacles and / or dynamic targets are detected, collisions are avoided through local replanning. The collaboration module is used to group multiple unmanned loaders into a formation and set time synchronization error function, path following error function and direction coordination error function to perform collaborative control between the unmanned loaders; The orientation coordination error function includes: ， in, For directional coordination error, For the first The heading angle of an unmanned loader For the first An unmanned loader, The first adjustment factor for directional coordination error. This is the second adjustment factor for the directional coordination error. This refers to the number of unmanned loaders.

Images