Multi-load multi-task intelligent unmanned vehicle system

Abstract

The invention belongs to the technical field of unmanned vehicles, and particularly relates to a multi-load multi-task intelligent unmanned vehicle system which comprises a command control system and a control system. The command and control system is responsible for overall task planning, decision making and resource scheduling, including specific task planning, instruction issuing, situation awareness and decision making, receiving data information of various instructions and intelligence through a wireless communication network, displaying, analyzing and fusing the data, and providing decision basis for commanders; the control system is responsible for converting decisions of the command and control system into specific vehicle actions including vehicle control, armed control and receiving instructions issued by the command and control system, software is divided into the control system and the command and control system, system complexity can be better managed, task execution efficiency can be better improved, driving safety can be better guaranteed, and technical feasibility can be better achieved; the unmanned vehicle can safely and efficiently execute tasks in various complex environments through the mode of division of labor and cooperation.

Description

Technical Field

[0001] The present invention belongs to the technical field of unmanned vehicles, and in particular relates to a multi-load and multi-task intelligent unmanned vehicle system. Background Art

[0002] As a significant achievement of modern scientific and technological development, intelligent unmanned vehicle technology encompasses multiple fields, including robotics, autonomous driving, sensor technology, communications technology, and artificial intelligence algorithms. These unmanned vehicles are designed to adapt to and perform diverse missions, such as logistics and transportation, environmental monitoring, search and rescue operations, and military reconnaissance, by combining hardware and software and carrying different payloads. However, despite the broad application prospects and significant technical advantages of multi-payload, multi-task intelligent unmanned vehicles, existing technologies still have certain drawbacks and deficiencies: First, in terms of human-machine collaboration, in tasks that require human-machine collaboration, how to ensure better interaction between unmanned vehicles and operators is an important issue.

[0003] Second, in terms of mission payload interchangeability, there may be problems with the interchangeability and compatibility of different mission payloads, affecting the flexibility and efficiency of the mission. Summary of the Invention

[0004] In order to solve the above-mentioned problems existing in the prior art, the present invention provides a multi-payload and multi-task intelligent unmanned vehicle system. By dividing the software into two systems, control and command, it can better manage system complexity, improve task execution efficiency, ensure driving safety and achieve technical feasibility. This division of labor and cooperation enables unmanned vehicles to perform tasks safely and efficiently in various complex environments.

[0005] To achieve the above-mentioned object, the present invention provides the following technical solutions: a multi-load and multi-task intelligent unmanned vehicle system, which includes a command and control system and a control system; The command and control system is responsible for overall mission planning, decision-making, and resource scheduling, including specific mission planning, command issuance, situational awareness, and decision-making. It receives various commands and intelligence data through wireless communication networks, and displays, analyzes, and integrates these data to provide decision-making basis for commanders. The command and control system is specifically divided into two parts: mission planning and decision-making, and multi-payload resource realization and scheduling. The control system is responsible for converting the decisions of the command and control system into specific vehicle actions, including vehicle control and weapon control. It receives instructions from the command and control system and controls the unmanned vehicle to drive and operate according to the instructions. It integrates precise sensors, actuators and control systems to ensure that the unmanned vehicle can drive stably and safely. The control system is specifically divided into three parts: high-precision positioning and navigation, execution control, and safety assurance mechanism.

[0006] As an optimal technical solution for a multi-load and multi-task intelligent unmanned vehicle system of the present invention, in the task planning and decision-making part, by adopting artificial intelligence algorithms, tasks are intelligently assigned to the most suitable unmanned vehicle or unmanned vehicle cluster according to the task type, urgency and current status of the unmanned vehicle. During the execution of the task, environmental changes, traffic conditions and the status of the unmanned vehicle are monitored in real time, and task planning is dynamically adjusted. When encountering emergencies or new instructions from human operators, it can respond quickly, replan the path or adjust the task priority to ensure the continuity and effectiveness of human-machine collaboration.

[0007] As a preferred technical solution for a multi-payload, multi-task intelligent unmanned vehicle system of the present invention, the multi-payload resource realization and scheduling part integrates multiple sensor data (such as radar, lidar, camera) and map information to perform multi-source information fusion. It can share the environmental information, task execution progress, potential risks and other information perceived by the unmanned vehicle with the human operator in real time. At the same time, it can also receive and process instructions and feedback from the operator, realizing seamless communication and collaboration between man and machine.

[0008] As a preferred technical solution for the multi-payload, multi-task intelligent unmanned vehicle system of the present invention, the high-precision positioning and navigation part achieves high-precision positioning of the unmanned vehicle by combining GPS and an inertial navigation system (INS). High-precision map data is used for map matching and path planning to ensure that the unmanned vehicle travels along the predetermined route. Through sensors such as radar, lidar, and cameras, the unmanned vehicle can perceive the surrounding environment in real time and identify obstacles and pedestrians. Under the supervision of human operators, the unmanned vehicle can autonomously plan its driving route and use advanced obstacle avoidance algorithms based on perception data to avoid obstacles, ensuring the accuracy and safety of task execution.

[0009] As an optimal technical solution for a multi-load and multi-task intelligent unmanned vehicle system of the present invention, in the execution control part, precise control of the steering, acceleration, and braking actuators of the unmanned vehicle is achieved by adopting a control algorithm. For an unmanned vehicle carrying a mission payload, precise operation of the payload can be achieved. Under the guidance of a human operator, the release of the payload, adjustment of the angle, or execution of other specific actions can be precisely controlled to meet diverse mission requirements.

[0010] As a preferred technical solution for a multi-load and multi-task intelligent unmanned vehicle system of the present invention, in the safety assurance mechanism part, redundant design is adopted in key components and systems to improve the reliability and safety of the system, monitor the status of the unmanned vehicle in real time, predict potential faults and perform diagnosis, and ensure that the unmanned vehicle can take timely countermeasures when a fault occurs.

[0011] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention has a simple structure. By dividing the software into two systems, control and command, it is intended to better manage system complexity, improve task execution efficiency, ensure driving safety, and achieve technical feasibility. This division of labor and cooperation enables unmanned vehicles to perform tasks safely and efficiently in various complex environments.

[0012] 2. The present invention is highly efficient, and its modular design allows the unmanned vehicle to be flexibly configured according to mission requirements and adapt to the needs of different loads and tasks, thereby improving efficiency and mission load interchangeability.

[0013] 3. The present invention has low cost: through the interchangeability of mission payloads, multiple unmanned vehicles can share limited mission payload resources to avoid duplication and redundancy. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 is a control block diagram of the present invention; Figure 2 This is the control connection diagram of the unmanned vehicle of the present invention. DETAILED DESCRIPTION

[0015] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention. Example

[0016] See also Figure 1-2 The present invention provides the following technical solutions: a multi-load and multi-task intelligent unmanned vehicle system, whose technical architecture is divided into two parts: command and control. These two parts work closely together to drive the unmanned vehicle to complete complex tasks.

[0017] The command and control system is the brain and nerve center of the unmanned vehicle, responsible for overall mission planning, decision-making and resource scheduling, including specific mission planning, command issuance, situational awareness, decision-making, etc. It receives various instructions, intelligence and other data information through wireless communication networks, and displays, analyzes and integrates these data to provide decision-making basis for commanders.

[0018] The charge system is divided into the following specific parts: Mission planning and decision-making: Based on artificial intelligence algorithms, tasks are intelligently assigned to the most suitable unmanned vehicle or unmanned vehicle cluster according to the task type, urgency and current status of the unmanned vehicle. During the execution of the task, environmental changes, traffic conditions and the status of the unmanned vehicle are monitored in real time, and mission planning is dynamically adjusted. When encountering emergencies or new instructions from human operators, it can respond quickly, replan the path or adjust the task priority to ensure the continuity and effectiveness of human-machine collaboration.

[0019] Multi-payload resource implementation and scheduling: Integrates multiple sensor data (such as radar, lidar, cameras, etc.) and map information to perform multi-source information fusion. It can share the environmental information, task execution progress, potential risks and other information perceived by the unmanned vehicle with human operators in real time. At the same time, it can also receive and process instructions and feedback from the operator, realizing seamless communication and collaboration between humans and machines.

[0020] In addition, in the multi-load resource implementation and scheduling part, there are the following designs: Modular design: The unmanned vehicle adopts a modular design, separating the basic parts such as the chassis, power system, and control system from the mission payload part, and designing the unmanned vehicle's mission payload into independent modules. Each module has specific functions and interface standards, so that different types of mission payload modules (such as cargo boxes, environmental monitoring equipment, rescue equipment, etc.) can be easily replaced and combined. Each mission payload module should have the ability to quickly connect and disconnect so that it can be quickly installed or removed before the unmanned vehicle performs a mission. This design not only reduces maintenance costs, but also improves the scalability and upgradeability of the system.

[0021] The chassis and control system of unmanned vehicles should adopt unified standards and interfaces to ensure compatibility with different types of mission payload modules. The control system should have the ability to dynamically identify mission payload modules and automatically adjust control parameters and strategies according to the installed modules.

[0022] Intelligent identification and docking: The unmanned vehicle is equipped with an intelligent identification system, which automatically identifies the type, status and configuration information of the mission payload module through sensors and recognition algorithms. Through precise mechanical and electrical interface design, it ensures seamless connection and stable operation between the mission payload module and the unmanned vehicle body.

[0023] Dynamic mission planning: The command and control system has dynamic mission planning capabilities and can automatically adjust mission execution strategies and path planning based on the type and status of the current mission payload. At the same time, it can predict and evaluate various situations during mission execution. It can also communicate in real time with the ground control center or other unmanned vehicles to collaboratively complete complex tasks.

[0024] The control system is the executive body of the unmanned vehicle, responsible for converting the decisions of the command and control system into specific vehicle actions, including vehicle control, weapon control, etc. It receives instructions issued by the command and control system and controls the unmanned vehicle to drive, operate and perform other operations according to the instructions. It integrates sophisticated sensors, actuators and control systems to ensure that the unmanned vehicle can drive stably and safely.

[0025] The control system is divided into the following specific parts: High-precision positioning and navigation: Combined with GPS and inertial navigation systems (INS), the unmanned vehicle achieves high-precision positioning. High-precision map data is used for map matching and path planning to ensure that the unmanned vehicle travels along the predetermined route. Through sensors such as radar, lidar, and cameras, it perceives the surrounding environment in real time and identifies obstacles and pedestrians. Under the supervision of human operators, it can autonomously plan its driving route and use advanced obstacle avoidance algorithms based on perception data to avoid obstacles, ensuring the accuracy and safety of mission execution.

[0026] Execution control: Advanced control algorithms are used to achieve precise control of the steering, acceleration, braking and other actuators of the unmanned vehicle. For unmanned vehicles carrying mission payloads, it can achieve precise operation of the payload. Under the guidance of human operators, it can accurately control the release of the payload, adjust the angle or perform other specific actions to meet diverse mission requirements.

[0027] Safety assurance mechanism: Redundant design is used in key components and systems to improve the reliability and safety of the system, monitor the status of the unmanned vehicle in real time, predict potential failures and diagnose them, and ensure that the unmanned vehicle can take timely countermeasures when a failure occurs.

[0028] The collaborative working mechanism between command and control of the present invention: information sharing and synchronization are achieved between the command and control system and the control system to ensure the continuity and consistency of task execution. In complex task scenarios, the command and control system and the control system work together to jointly make decisions and adjust task execution strategies. According to the real-time situation during task execution, the command and control strategies are dynamically adjusted to adapt to environmental changes and changes in task requirements.

[0029] The business process of the present invention is as follows: First, the user starts the computer or dedicated terminal in the control center, enters the user name and password through the login interface for identity authentication, and after the authentication is passed, the system starts and enters the main interface; On the main interface, load and connect the unmanned vehicle. The user clicks or selects the "Command and Control System" icon or menu item to enter the command and control interface. The interface usually contains multiple areas such as the task list, map display area, map tools, and measurement plotting. Tasks can be added, task paths can be created, and tasks can be assigned to the vehicle. Next, the user clicks or selects the "Control System" icon or menu item to enter the control interface. The control interface is an interface used to directly control the driving and payload operation of the unmanned vehicle. The interface usually includes parameters of input devices such as joysticks, buttons, sliders, as well as real-time videos and sub-windows from various perspectives of the unmanned vehicle. The control system will display tasks assigned and created by the command and control system. Click on the sub-window to put it in the main window, and it will automatically identify the type, status and configuration information of the mission payload module, display the detection information of the unmanned vehicle's payload, and configure and control the payload; In the task list, users can see multiple assigned tasks. Each task may be accompanied by a status indicator (such as pending, in progress, completed, etc.). Users can select and activate the task by clicking the task item with the mouse and execute it. Open the information panel to display the vehicle's equipment information, chassis information, and payload information on the equipment page. The target information and intelligence source can be viewed on the intelligence page. The log can show the details and status information of all tasks.

[0030] Advantages of the present invention: Simple structure: Dividing the software into two systems, control and command, is to better manage system complexity, improve task execution efficiency, ensure driving safety and achieve technical feasibility. This division of labor and cooperation enables unmanned vehicles to perform tasks safely and efficiently in various complex environments.

[0031] High efficiency and modular design allow unmanned vehicles to be flexibly configured according to mission requirements and adapt to the needs of different loads and tasks, thereby improving efficiency and mission payload interchangeability.

[0032] The cost is low. Through the interchangeability of mission payloads, multiple unmanned vehicles can share limited mission payload resources to avoid duplication and redundancy.

[0033] In addition, the contents not described in detail in this embodiment are all within the scope of existing technology and common knowledge.

[0034] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A multi-payload, multi-task intelligent unmanned vehicle system, characterized by a command and control system and a control system; The command and control system is responsible for overall mission planning, decision-making, and resource scheduling, including specific mission planning, command issuance, situational awareness, and decision-making. It receives various commands and intelligence data through wireless communication networks, and displays, analyzes, and integrates these data to provide decision-making basis for commanders. The command and control system is specifically divided into two parts: mission planning and decision-making, and multi-payload resource realization and scheduling. The control system is responsible for converting the decisions of the command and control system into specific vehicle actions, including vehicle control and weapon control. It receives instructions from the command and control system and controls the unmanned vehicle to drive and operate according to the instructions. It integrates precise sensors, actuators and control systems to ensure that the unmanned vehicle can drive stably and safely. The control system is specifically divided into three parts: high-precision positioning and navigation, execution control, and safety assurance mechanism.

2. The multi-load, multi-task intelligent unmanned vehicle system according to claim 1, characterized in that: In the task planning and decision-making part, by adopting artificial intelligence algorithms, tasks are intelligently assigned to the most suitable unmanned vehicle or unmanned vehicle cluster based on the task type, urgency and current status of the unmanned vehicle. During the execution of the task, environmental changes, traffic conditions and the status of the unmanned vehicle are monitored in real time, and task planning is dynamically adjusted. When encountering emergencies or new instructions from human operators, it can respond quickly, replan the path or adjust the task priority to ensure the continuity and effectiveness of human-machine collaboration.

3. The multi-load, multi-task intelligent unmanned vehicle system according to claim 1, characterized in that: In the multi-payload resource implementation and scheduling part, by integrating multiple sensor data (such as radar, lidar, camera) and map information, multi-source information fusion is performed, which can share the environmental information, task execution progress, potential risks and other information perceived by the unmanned vehicle with the human operator in real time. At the same time, it can also receive and process instructions and feedback from the operator, realizing seamless communication and collaboration between man and machine.

4. The multi-load, multi-task intelligent unmanned vehicle system according to claim 1, characterized in that: In the high-precision positioning and navigation part, the high-precision positioning of the unmanned vehicle is achieved by combining GPS and inertial navigation system (INS). High-precision map data is used for map matching and path planning to ensure that the unmanned vehicle travels along the predetermined route. Through radar, lidar, camera and other sensors, the surrounding environment is perceived in real time, obstacles and pedestrians are identified, and under the supervision of human operators, the driving route can be planned autonomously. Based on the perception data, advanced obstacle avoidance algorithms are used to avoid obstacles, ensuring the accuracy and safety of mission execution.

5. The multi-load and multi-task intelligent unmanned vehicle system according to claim 1, characterized in that: In the execution control part, the control algorithm is adopted to achieve precise control of the steering, acceleration, and braking actuators of the unmanned vehicle. For unmanned vehicles carrying mission payloads, precise operation of the payload can be achieved. Under the guidance of human operators, the release of the payload, adjustment of angles, or execution of other specific actions can be precisely controlled to meet diverse mission requirements.

6. The multi-load and multi-task intelligent unmanned vehicle system according to claim 1, characterized in that: In the safety assurance mechanism part, by adopting redundant design on key components and systems, the reliability and safety of the system are improved, the status of the unmanned vehicle is monitored in real time, potential failures are predicted and diagnosed, and it is ensured that the unmanned vehicle can take timely countermeasures when a failure occurs.

Images