Unmanned vehicle control system and method based on global information

Abstract

The invention relates to an unmanned vehicle control system and method based on global information, and is suitable for a multi-platform unmanned vehicle system. According to the system, a cooperative control model is added on the basis of an existing whole vehicle control model, and a final execution control instruction is calculated and generated by receiving a remote control instruction, vehicle state feedback information and global information including a superior command control instruction, situation map information and other vehicle cooperative information. The cooperative control method adopts a three-level priority control strategy: the control strategy 1 ensures the driving safety and rationality; the control strategy 2 adjusts the instruction to meet the multi-vehicle cooperation requirement; and the control strategy 3 adjusts task execution according to the superior command instruction. By introducing global information, the task execution capability and the multi-platform adaptability of the unmanned vehicle group are improved, a systematic solution is provided, and meanwhile, the system has the advantages of being simple in structure and easy to transform.

Description

Technical Field

[0001] The present invention belongs to the technical field of unmanned vehicle control, and relates to an overall structure of an unmanned vehicle control system and an information flow execution mechanism. Background Art

[0002] The motion control of unmanned vehicles mainly relies on the control commands issued by the remote control end. Simple unmanned vehicles directly execute the commands after receiving the remote control commands. Some unmanned vehicles will comprehensively judge the feasibility of command execution based on the status information of the entire vehicle after receiving the control commands. Different control strategies will be implemented when different fault levels occur in the chassis. This control method is more suitable for the control system of a single control end to a single platform.

[0003] With the advancement of unmanned vehicle technology, multi-platform unmanned systems are rapidly developing. A multi-platform unmanned vehicle system refers to unmanned vehicles (autonomous vehicles) and their supporting technology systems that can operate collaboratively across a variety of hardware, software, or application scenarios. These systems utilize standardized interfaces, modular design, and cross-platform compatibility to enable seamless collaboration and resource sharing across different platforms (e.g., different vehicle models, sensor configurations, operating systems, or cloud services). Their core goal is to enhance the flexibility, scalability, and application scope of unmanned vehicle technology. In addition to acquiring information about the vehicle itself, unmanned vehicles in a multi-platform system also obtain global information, such as command information, environmental information about the driving area, and information about collaboration with other unmanned vehicles in the multi-platform system. During motion control, the unmanned vehicle must consider all of this information to comprehensively assess its behavior and determine the control instructions that best meet its control requirements. Therefore, a control system that adapts to multiple platforms must consider global information, such as the vehicle's state and situation. Summary of the Invention

[0004] In view of this, the present invention provides an unmanned vehicle control system and method based on global information, which is suitable for multi-platform unmanned vehicle systems. By classifying control instructions and grading control models, new instructions for unmanned vehicles can be obtained. These instructions can control the movement of unmanned vehicles while meeting application scenarios of cluster control such as multi-vehicle collaboration.

[0005] The specific technical solutions are as follows: A global information-based unmanned vehicle control system adds a collaborative control model to the existing whole-vehicle control model of the unmanned vehicle; the whole-vehicle control model calculates control instruction 1 based on received remote control instructions, feedback information from vehicle execution components, and feedback information from vehicle status components, and sends the result to the collaborative control model; the collaborative control model receives global information control instructions and calculates control instruction 2 based on control instruction 1 and the global information control instructions, and control instruction 2 serves as the final execution control instruction of the unmanned vehicle.

[0006] Furthermore, remote control instructions are generated by the remote control terminal of the unmanned vehicle and are used to manually control the actions of the current vehicle; global information control instructions include three parts, namely, control instructions generated by the superior command and control system; situation information generated by the situation map; and collaborative information generated by other vehicles.

[0007] Furthermore, when there is no global information control instruction, the unmanned vehicle executes according to the received remote control instruction.

[0008] A global information-based unmanned vehicle collaborative control method is based on an unmanned vehicle control system and is implemented by a collaborative control model. It specifically includes three independent control strategies with increasing priorities. Control strategy 1 is used to ensure that the control instructions 1 of the unmanned vehicle in the next driving area meet the requirements of situation information, thereby ensuring the safety and rationality of driving; control strategy 2 adjusts the output instructions of control strategy 1 by receiving collaborative information from other vehicles to ensure that the driving instructions of the unmanned vehicle meet the requirements of multi-vehicle collaboration; control strategy 3 adjusts the output instructions of control strategy 2 by receiving instructions from a superior command and control system to ensure that the driving instructions and task execution of the unmanned vehicle meet the requirements of the superior command and control system, thereby realizing collaboration between the unmanned vehicle and the superior command and control system.

[0009] Furthermore, control strategy 1 generates intermediate instruction 1 based on the received situation information and control instruction 1. If there is no situation information in the current cycle, control instruction 1 is directly generated as intermediate instruction 1; the specific content of control strategy 1 includes unmanned vehicle speed limit, turning radius limit, and safety factor adjustment.

[0010] Furthermore, control strategy 2 generates intermediate instruction 2 based on the received collaborative information and the output instruction generated by control strategy 1. If there is no collaborative information in the current cycle, the output instruction generated by control strategy 1 is directly generated as intermediate instruction 2; the specific content of control strategy 2 includes the coordinated adjustment of the unmanned vehicle speed, direction, and task instructions.

[0011] Furthermore, control strategy 3 generates control instruction 2 based on the instructions received from the superior command and control system and the output instructions generated by control strategy 2. If there is no instruction from the superior command and control system in the current cycle, the output instruction generated by control strategy 2 is directly generated as control instruction 2; the specific content of control strategy 3 includes the command and control adjustment of the unmanned vehicle speed, direction and mission instructions.

[0012] The beneficial effects that can be achieved by adopting the present invention are as follows: 1. The present invention improves the ability of unmanned vehicles to perform group tasks by introducing global information such as the command system into the vehicle control system, and provides a solution for the systematization of unmanned vehicles.

[0013] 2. The present invention is applicable to control systems on multiple platforms and can make comprehensive judgments on vehicle behavior, thereby determining the control instructions that best meet control requirements.

[0014] 3. The present invention forms a new control architecture for unmanned platforms by introducing global information into the control system, which can improve the control capability of unmanned platforms.

[0015] 4. The system of the present invention has a simple structure and is easy to modify vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is the overall architecture diagram of the system of the present invention; Figure 2 This is an architecture diagram of the collaborative control method of the present invention; Figure 3 Schematic diagram of multi-platform collaborative control. DETAILED DESCRIPTION

[0017] The present invention will be further described below with reference to the accompanying drawings.

[0018] The present invention has 3 drawings in total.

[0019] Figure 1 This is the overall architecture diagram of the system described in the present invention. Remote control commands are generated by the unmanned vehicle's remote control terminal and transmitted to the control system via a wired or wireless system. Vehicle execution components refer to the components and systems used by the unmanned vehicle to execute actions, such as the power system (including the power battery, engine, generator, hydraulic pump, etc.); the drive system (including the driver, drive motor, etc.); the braking system (including the brake controller, brake pump, hydraulic valve, etc.); the steering system (including the steering controller, steering motor, etc.); and the payload system. Vehicle status components refer to the components or systems used by the unmanned vehicle to collect vehicle status information or obtain vehicle operating status information, such as the gateway, bus, attitude sensor, electrical distribution box, communication system, image acquisition system, etc. Global information, such as the command and control system, includes: 1) command commands generated by the command and control system, 2) situation information generated by the situation map, and 3) collaborative information generated by other vehicles. The unmanned vehicle's control system is divided into two modules: the vehicle control model and the collaborative control model. The vehicle control model represents the existing control system of the unmanned vehicle, while the collaborative control model is a module added in the present invention. Control instructions 1 include control instructions for the unmanned vehicle and control instructions for the mission payload.

[0020] Remote control commands from a remote control terminal are typically generated manually by the operator at the remote control terminal based on feedback from the control terminal and the current mission. These commands include platform status control, speed, direction, and mission payload control. Control commands from a higher-level command system are those sent to a specific platform based on global information and missions.

[0021] Figure 2 This is the architecture diagram of the collaborative control method described in the present invention. This method architecture includes three independent control strategies, among which control strategy 1 is mainly used to process the input information of situation information and control instruction 1, and generate intermediate instruction 1. Control strategy 2 is mainly used to process the input information of collaborative information and intermediate instruction 1, and generate intermediate instruction 2. Control strategy 3 is mainly used to process the input information of command and control instructions and intermediate instruction 2, and generate control instruction 2. The three control strategies are hierarchical and progressive, forming different priority control strategies from low to high.

[0022] Figure 3 This is a schematic diagram of multi-platform collaborative control using the present invention. The schematic diagram demonstrates the specific implementation of the present invention in multi-vehicle collaborative control. During the implementation process, each unmanned vehicle is equipped with Figure 1 The control architecture shown in the figure is shown. During mission execution, each unmanned vehicle receives its own remote control commands, as well as command and control commands from the command and control system and collaborative information from neighboring unmanned vehicles. Situational information is generated by the situation map based on factors such as terrain and enemy firepower. It primarily provides information about the terrain and safety conditions in the next driving area for the unmanned vehicle. Command and control commands are issued by the command and control system and are primarily used to direct the unmanned vehicle to perform specific tasks or provide specific control information such as start and stop. Collaborative information is generated by neighboring vehicles and is primarily used to coordinate neighboring unmanned vehicles to perform collaborative tasks. In the absence of global information such as from the command and control system, unmanned vehicles 1 through n execute the received remote control commands. Once the unmanned vehicle receives global information such as from the command and control system, it processes it according to the corresponding control strategy and generates new control commands to control the unmanned vehicle.

[0023] The present invention proposes an unmanned vehicle control method based on global information, which is an overall control information flow of an unmanned vehicle.

[0024] First, the unmanned vehicle control system receives a remote control instruction from the remote control terminal. This instruction is input into the vehicle control model of the control system as control information source 1. At the same time, the vehicle control model receives feedback information from the vehicle execution components and status components, namely control information source 2. Information sources 1 and 2 serve as control inputs of the vehicle control model. After being solved by the vehicle control model, control instruction 1 is obtained, which is input into the collaborative control model. The collaborative control model also receives control information source 3, which is control instructions from global information such as the accusation system. After control instruction 1 and control information source 3 are solved by the collaborative control model, control instruction 2 is obtained. Control instruction 2 is output to the execution component of the unmanned vehicle to complete the motion control and load control of the unmanned vehicle. Figure 1 shown.

[0025] Secondly, the control information source 3 is divided into three categories: situation information, collaborative information, and command and control instructions. The collaborative control model uses a hierarchical discrimination method to fuse and judge the information of the control information source 3, such as Figure 2 As shown. It is divided into three steps.

[0026] In the first step, the situation map generates situation information for the unmanned platform's driving area based on the terrain conditions and enemy firepower. The collaborative control model's control strategy 1 analyzes and judges control instruction 1 based on the situation information, generating a new intermediate instruction 1.

[0027] Control strategy 1 is mainly used to determine whether the platform instructions meet the situation map requirements. The judgment content includes but is not limited to the following categories: (1) Obtain the maximum speed v1 of the unmanned vehicle in the next driving area based on the situation information, and compare v1 with the speed value in control instruction 1. If the command value in control instruction 1 is greater than v1, replace the speed value in control instruction 1 with v1.

[0028] (2) Obtain the maximum turning radius r1 of the unmanned vehicle in the next area based on the situation information, and compare r1 with the turning radius in control instruction 1. If the command value in control instruction 1 is smaller than r1, replace the turning radius value in control instruction 1 with r1.

[0029] (3) Based on the situation information, such as enemy firepower, the platform's driving safety factor for the next area is obtained. (Safety factors are represented by 1 to 0, ranging from the safest to the least safe, and their values ​​are obtained using situation assessment methods based on different situation requirements.) The speed value in control instruction 1 is multiplied by the safety factor to obtain the new speed value for control instruction 1. For example, if the driving safety in the next area is 0, the new speed information for that area is also 0, and the platform should stop moving immediately.

[0030] After the control strategy 1 is processed, the control instruction 1 is generated into an intermediate instruction 1 and input into the control strategy 2 of the collaborative control model.

[0031] If there is no situation information in the current cycle, the control instruction 1 is directly generated as the intermediate instruction 1.

[0032] In the second step, the unmanned vehicle receives the collaborative information from other vehicles and uses the collaborative information and intermediate instruction 1 to obtain intermediate instruction 2 through control strategy 2. Control strategy 2 is mainly used to determine whether intermediate instruction 1 meets the multi-vehicle collaboration requirements. The judgment content includes but is not limited to the following categories: (1) Based on the collaborative information, the unmanned platform's next speed v2 and direction d2 are obtained. Intermediate instruction 1 is compared with this information, and the speed value v1 and direction value d1 of the intermediate instruction are gradually transitioned to v2 and d2 over the set n control cycles. In the current control cycle, v1 + (v2 - v1) / n and d1 + (d2 - d1) / n are used as new control instructions to update the corresponding values ​​of intermediate instruction 1.

[0033] (2) Based on the collaborative information, the unmanned platform obtains the next mission instruction. Based on the mission instruction, the current mission system status is checked and the corresponding instruction is updated. For example, if the collaborative information is for 2km visible light target reconnaissance, Strategy 2 checks whether the unmanned platform's reconnaissance device is turned on and whether the reconnaissance device has moved to the area specified in the collaborative information. If not, the payload control instruction is updated to Intermediate Instruction 1.

[0034] After the control strategy 2 is processed, the intermediate instruction 1 is generated into the intermediate instruction 2 and input into the control strategy 3 of the collaborative control model.

[0035] If there is no coordination information in the current cycle, the intermediate instruction 1 is directly generated into the intermediate instruction 2.

[0036] In the third step, the unmanned vehicle receives the command and control instruction from the command and control system, and obtains the control instruction 2 by combining the command and control instruction with the intermediate instruction 2 through the control strategy 3. The control strategy 3 is mainly used to determine whether the intermediate instruction 2 meets the command and control requirements. The judgment content includes but is not limited to the following categories: (1) Based on the command and control instructions, the unmanned platform's next speed v3 and direction d3 are obtained. Intermediate instruction 2 is compared with this information, and the speed value v2 and direction value d2 of the intermediate instruction are gradually transitioned to v3 and d3 through the set n control cycles. In the current control cycle, v2 + (v3 - v2) / n and d2 + (d3 - d2) / n are used as new control instructions to update the corresponding values ​​of intermediate instruction 2.

[0037] (2) Based on the command and control instructions, the unmanned platform's next task is obtained. Based on the task instructions, the current task system status is checked and the corresponding instructions are updated. For example, if the command and control instruction is to identify a person 500 meters away in the 90° area to the right of the vehicle, Strategy 3 uses this information to check whether the unmanned platform's reconnaissance device is turned on, whether the reconnaissance device has been rotated to the right side of the vehicle, and whether the person recognition function is enabled. If not, the control instruction is updated to Intermediate Instruction 2.

[0038] After the control strategy 3 is processed, the intermediate instruction 2 is generated as the control instruction 2, which is input into the unmanned platform execution component to control the unmanned platform to execute the next cycle of motion.

[0039] If there is no command and control information in the current cycle, the intermediate instruction 2 is directly generated as the control instruction 2.

[0040] After the above collaborative control model steps are completed, the control system continues to repeat the above control steps, continuously controlling the unmanned vehicle to operate in a coordinated mode.

Claims

1. An unmanned vehicle control system based on global information, characterized by: A collaborative control model is added to the existing whole vehicle control model of the unmanned vehicle; the whole vehicle control model calculates control instruction 1 based on the received remote control instructions, feedback information from the vehicle execution components, and feedback information from the vehicle status components, and sends it to the collaborative control model; the collaborative control model receives the global information control instruction, and calculates control instruction 2 based on control instruction 1 and the global information control instruction, and control instruction 2 serves as the final execution control instruction of the unmanned vehicle.

2. The unmanned vehicle control system based on global information according to claim 1, characterized in that: Remote control commands are generated by the remote control terminal of the unmanned vehicle and are used to manually control the actions of the current vehicle; global information control commands include three parts, namely, control commands generated by the superior command and control system; situation information generated by the situation map; and collaborative information generated by other vehicles.

3. The unmanned vehicle control system based on global information according to any one of claims 1 or 2, characterized in that: When there is no global information control instruction, the unmanned vehicle executes according to the received remote control instruction.

4. A global information-based unmanned vehicle cooperative control method, based on an unmanned vehicle control system, characterized by: It is implemented by a collaborative control model, which specifically includes three independent control strategies with increasing priorities. Control strategy 1 is used to ensure that the control instructions 1 of the unmanned vehicle in the next driving area meet the requirements of the situation information, thereby ensuring the safety and rationality of driving; Control strategy 2 adjusts the output instructions of control strategy 1 by receiving collaborative information from other vehicles to ensure that the driving instructions of the unmanned vehicle meet the requirements of multi-vehicle collaboration; Control strategy 3 adjusts the output instructions of control strategy 2 by receiving instructions from the superior command and control system to ensure that the driving instructions and task execution of the unmanned vehicle meet the requirements of the superior command and control system, thereby realizing the collaboration between the unmanned vehicle and the superior command and control system.

5. The unmanned vehicle cooperative control method based on global information according to claim 4 is characterized in that: Control strategy 1 generates intermediate instruction 1 based on the received situation information and control instruction 1. If there is no situation information in the current cycle, control instruction 1 is directly generated as intermediate instruction 1; the specific content of control strategy 1 includes unmanned vehicle speed limit, turning radius limit, and safety factor adjustment.

6. The unmanned vehicle cooperative control method based on global information according to any one of claims 4 or 5, characterized in that: Control strategy 2 generates intermediate instruction 2 based on the received collaborative information and the output instruction generated by control strategy 1. If there is no collaborative information in the current cycle, the output instruction generated by control strategy 1 is directly generated as intermediate instruction 2; the specific content of control strategy 2 includes the coordinated adjustment of the unmanned vehicle speed, direction, and task instructions.

7. The unmanned vehicle cooperative control method based on global information according to claim 6, characterized in that: Control strategy 3 generates control instruction 2 based on the instructions received from the superior command and control system and the output instructions generated by control strategy 2. If there is no instruction from the superior command and control system in the current cycle, the output instruction generated by control strategy 2 is directly generated as control instruction 2; the specific content of control strategy 3 includes the command and control adjustments of the unmanned vehicle speed, direction and mission instructions.

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