Unmanned aerial vehicle cluster control platform and application

Abstract

The invention discloses an unmanned aerial vehicle cluster control platform, and the platform comprises a user interface module which is used for task configuration, real-time monitoring and flight path visualization; the control and management module supports cooperative control and dynamic path planning of three-dimensional and two-dimensional scenes; the data processing module is used for real-time data collection and analysis and global situation awareness; the hardware collaboration interface layer communicates with a flight control node of the unmanned aerial vehicle and an airborne computer in real time to realize instruction issuing and data synchronization; the flight task scheduling module is used for dynamically adjusting task distribution according to task priorities and environmental conditions; the unmanned aerial vehicle cluster flight management module is used for coordinating multi-aircraft cooperative flight, obstacle avoidance and state monitoring; the platform controls unmanned aerial vehicle clusters in a three-dimensional space scene and a two-dimensional plane scene at the same time, and dynamic path planning, obstacle avoidance and multi-vehicle task collaboration are achieved through a hardware collaboration mechanism. The problems that a traditional unmanned aerial vehicle control platform cannot perform multi-scene comprehensive control and is low in hardware cooperation efficiency can be solved.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle (UAV) swarm control, and particularly to a UAV swarm control platform and a three-dimensional UAV swarm control system. Background Art

[0002] In recent years, UAV swarm control technology has developed rapidly, especially in the military, agricultural and other fields. With the continuous progress of UAV technology, swarm flight has gradually become an efficient operation mode. Especially when performing complex tasks, it can improve the efficiency and execution quality of tasks through multi-aircraft collaborative work.

[0003] Traditional UAV control platforms mostly focus on single-dimensional control or cannot effectively perform comprehensive control in multiple scenarios (such as three-dimensional space and two-dimensional ground scenarios), making it difficult to meet the requirements of real-time control, obstacle avoidance, task allocation and dynamic adjustment. In addition, the existing control platforms have insufficient cooperation with hardware (such as flight control nodes, on-board computers, etc.), and cannot efficiently transmit data and coordinate multi-aircraft operations. The existing technologies generally have problems such as un-intelligent flight task allocation, poor dynamic adjustment ability, and lagging real-time feedback.

[0004] Therefore, it is necessary to provide a UAV swarm control platform that can simultaneously control in three-dimensional and two-dimensional scenarios, and can efficiently cooperate with hardware to improve the efficiency and safety of UAV swarm operations. Summary of the Invention

[0005] In view of the above deficiencies or improvement requirements of the prior art, the present invention provides a UAV swarm control platform and application, which can solve the problems that traditional UAV control platforms cannot perform comprehensive control in multiple scenarios and have low cooperation efficiency with hardware.

[0006] On the one hand, an embodiment of the present invention provides a UAV swarm control platform, including: a user interface module for task configuration, real-time monitoring and flight path visualization; a control and management module including a three-dimensional scene control sub-module and a two-dimensional scene control sub-module, supporting collaborative control and dynamic path planning in three-dimensional and two-dimensional scenarios; a data processing module for real-time data collection, analysis and global situation awareness; a hardware cooperation interface layer for real-time communication with the flight control nodes and on-board computers of the UAVs to implement instruction issuance and data synchronization; a flight task scheduling module for dynamically adjusting task allocation according to task priorities and environmental conditions; a UAV swarm flight management module for coordinating multi-aircraft collaborative flight, obstacle avoidance and status monitoring; wherein, the platform simultaneously controls the UAV swarm in three-dimensional space and two-dimensional plane scenarios, and realizes dynamic path planning, obstacle avoidance and multi-aircraft task collaboration through a hardware cooperation mechanism.

[0007] In one embodiment of the present invention, the three-dimensional scene control sub-module displays the position, flight path, and flight parameters of the unmanned aerial vehicle (UAV) through a three-dimensional visualization interface, supporting the operator to adjust the flight attitude and path in real time; the two-dimensional scene control sub-module displays the UAV position and trajectory in a plane view, which is used for path optimization and task allocation in a simplified task scenario.

[0008] In one embodiment of the present invention, the hardware cooperation interface layer includes: a flight control system interface for sending flight control instructions and receiving sensor data; an on-board computer interface for exchanging environmental perception data and flight information with the UAV on-board computer; and a communication management system for completing low-latency data synchronization between the platform and the UAV.

[0009] In one embodiment of the present invention, the flight task scheduling module includes a dynamic task scheduling sub-module and a task priority management sub-module, which automatically adjusts the task execution order according to real-time environmental data and the UAV status.

[0010] In one embodiment of the present invention, the UAV cluster flight management module includes an obstacle avoidance and optimization sub-module. The obstacle avoidance and optimization sub-module uses lidar and infrared sensor data to calculate the obstacle avoidance path in real time, and ensures the safety of multi-UAV cooperative flight through dynamic replanning.

[0011] In one embodiment of the present invention, when the obstacle avoidance and optimization sub-module detects a sudden obstacle, it preferentially generates a local obstacle avoidance path based on a three-dimensional path planning algorithm and broadcasts it to all UAVs in the cluster through the communication management system.

[0012] In one embodiment of the present invention, the data processing module performs fusion analysis on multi-UAV sensor data through machine learning algorithms, generates a global flight situation prediction, and provides decision support for task scheduling.

[0013] In one embodiment of the present invention, the path planning and optimization sub-module generates a three-dimensional path according to terrain data and flight area restrictions, and dynamically adjusts the path through a real-time obstacle avoidance algorithm to keep the multi-UAVs at an optimal interval.

[0014] In one embodiment of the present invention, the platform supports cross-scene joint operations, including: responding to the operator's switching operation between the three-dimensional and two-dimensional views, and realizing cross-dimensional task collaboration through the collaborative control module.

[0015] On the other hand, an embodiment of the present invention provides a three-dimensional control system for a UAV cluster, including: a host computer; a UAV cluster; the host computer is equipped with the UAV cluster control platform as described in any one of the above embodiments for controlling the UAV cluster.

[0016] As can be seen from the above, compared with the prior art, the above solution conceived by the present invention can have one or more of the following beneficial effects:

[0017] The UAV swarm control platform proposed in the embodiment of the present invention can achieve more efficient task scheduling and flight planning by controlling in three-dimensional and two-dimensional scenarios simultaneously. Three-dimensional control can ensure flight path planning and obstacle avoidance in complex environments, while two-dimensional control is suitable for simplified tasks such as ground inspection and material delivery. The deep integration of the platform with hardware devices such as flight control nodes and on-board computers ensures real-time synchronization and information sharing of flight control data, avoids operation delays, and improves the accuracy and reliability of swarm flight. Through dynamic path adjustment, obstacle avoidance technology, and real-time task feedback mechanism, it can effectively avoid collisions of the UAV swarm and potential risks in task execution, ensuring the safe flight of UAVs in complex environments. The platform can flexibly switch between three-dimensional and two-dimensional control modes according to the task type, adapt to various task requirements in different fields (such as military, agriculture, logistics, etc.), and has broad application prospects.

[0018] Through the following detailed description with reference to the accompanying drawings, other features of the present invention become apparent. It should be understood, however, that the drawings are designed solely for the purpose of explanation and not as a definition of the scope of the present invention. It should also be understood that, unless otherwise indicated, the drawings are not necessarily drawn to scale and are merely intended to conceptually illustrate the structures and processes described herein. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings described herein are used to provide a further understanding of the present invention and form a part of the present invention. The illustrative embodiments and descriptions thereof are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0020] Figure 1 is a schematic structural diagram of a UAV swarm control platform provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0021] It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other. The present invention will be described below with reference to the accompanying drawings and in conjunction with the embodiments.

[0022] In order to enable those of ordinary skill in the art to better understand the technical solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments, and all should belong to the protection scope of the present invention.

[0023] It should be noted that the terms "first", "second", etc. in the description, claims and the above-mentioned drawings of the present invention are used to distinguish similar objects and do not necessarily have to be used to describe a specific order or sequence. It should be understood that such terms can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0024] It should also be noted that the division of multiple embodiments in the present invention is only for convenience of description and should not constitute a special limitation. The features in various embodiments can be combined and cross-referenced without contradiction.

[0025]

First Embodiment

[0026] As Figure 1 shown, the first embodiment of the present invention proposes a UAV swarm control platform, for example, including: a user interface module, a control and management module, a data processing module, a hardware cooperation interface layer, a flight task scheduling module, and a UAV swarm flight management module. Among them, the user interface module is used for task configuration, real-time monitoring, and flight path visualization. The control and management module includes a three-dimensional scene control sub-module and a two-dimensional scene control sub-module, supporting the cooperative control of three-dimensional and two-dimensional scenes and dynamic path planning. The data processing module is used for real-time data collection, analysis, and global situation awareness. The hardware cooperation interface layer communicates with the flight control nodes and on-board computers of the UAVs in real time to achieve instruction issuance and data synchronization. The flight task scheduling module dynamically adjusts task allocation according to task priorities and environmental conditions. The UAV swarm flight management module coordinates multi-aircraft cooperative flight, obstacle avoidance, and status monitoring. Among them, the platform simultaneously controls the UAV swarm in three-dimensional space and two-dimensional plane scenes, and realizes dynamic path planning, obstacle avoidance, and multi-aircraft task cooperation through a hardware cooperation mechanism.

[0027] Specifically, the user interface module provides an intuitive interaction interface for the operator to monitor and configure the flight tasks of the UAV swarm, including real-time feedback, task scheduling, status monitoring, flight path visualization, etc., including a task configuration and monitoring sub-module and a real-time feedback and monitoring sub-module. The task configuration and monitoring sub-module is used to set UAV tasks, schedule tasks, and adjust task priorities. The real-time feedback and monitoring sub-module displays the real-time flight status, task progress, and flight path.

[0028] The control and management module handles the global control of the cluster, coordinates the task execution of each drone, and ensures the efficient cooperation of tasks, including a 3D scene control sub-module, a 2D scene control sub-module, and a path planning and optimization sub-module. The 3D scene control sub-module displays the flight status and path of the drones through a 3D map and view, providing spatial information for flight. The 2D scene control sub-module performs tasks such as task allocation and path optimization in a 2D view. The path planning and optimization sub-module generates dynamic flight paths for each drone and adjusts them according to the real-time environment (such as weather, obstacles, etc.).

[0029] The data processing module collects and analyzes the flight data transmitted from each drone, provides real-time feedback and prediction, and processes and makes decisions on large-scale sensor data, including a real-time data collection sub-module, a data analysis and processing sub-module, and a big data analysis sub-module. The real-time data collection sub-module receives the sensor data of each drone, including flight position, speed, battery level, etc. The data analysis and processing sub-module analyzes the state of the drones through algorithms and makes decisions such as task scheduling and path optimization. The big data analysis sub-module fuses and analyzes the data of multiple drones to provide global flight situation awareness.

[0030] The hardware cooperation interface layer works in cooperation with the flight control systems and on-board computers of each drone to ensure the real-time execution of instructions and data synchronization, including a flight control system interface, an on-board computer interface, and a communication management system. The platform issues flight control instructions through the flight control system interface and receives flight status feedback. The on-board computer interface exchanges data with the on-board computers of each drone, including environmental perception data, flight information, etc. The communication management system ensures real-time and low-latency data communication between the platform and the drones.

[0031] The flight task scheduling module dynamically schedules tasks according to the priority of tasks, environmental conditions, and flight status, and performs task allocation and adjustment, including a dynamic task scheduling sub-module and a task allocation and priority management sub-module. The dynamic task scheduling sub-module adjusts the priority of tasks according to the execution situation of tasks and automatically adjusts the task execution order of the drones. The task allocation and priority management sub-module makes intelligent allocations according to the type and urgency of tasks.

[0032] The drone cluster flight management module manages and coordinates the flight tasks of the drone cluster, including multi-aircraft cooperative flight, obstacle avoidance, and flight status monitoring, etc., including a multi-aircraft cooperative control sub-module, a flight status monitoring sub-module, and an obstacle avoidance and optimization sub-module. The multi-aircraft cooperative control sub-module ensures that all drones can fly cooperatively and avoids mutual interference and collision. The flight status monitoring sub-module monitors the flight status of each drone in real time to ensure the safe execution of tasks. The obstacle avoidance and optimization sub-module makes obstacle avoidance adjustments according to real-time feedback to ensure the safety and efficiency of the flight path.

[0033] Figure 1 The data flow and control flow in it include:

[0034] User interaction with the platform: The user inputs tasks and adjusts task parameters through the UI interface, and operates the platform to manage and schedule the UAV cluster. The control and management module generates instructions based on the user input and feedbacks the flight status.

[0035] Flight control and hardware cooperation: The platform communicates with the flight control system and on-board computer of the UAV through the hardware cooperation interface, and adjusts the flight path and tasks in real time to ensure that the UAVs execute according to the task requirements.

[0036] Real-time data analysis and feedback: The flight data transmitted from the flight control system and on-board computer is collected and processed in real time, and is used for dynamic adjustment, path planning and optimization of flight tasks.

[0037] Flight task scheduling and optimization: The platform dynamically schedules and adjusts tasks according to the real-time environment and flight status to ensure the efficient cooperation of the UAV cluster.

[0038] The technical solutions and functions implemented by the UAV cluster control platform in this embodiment are described in detail below:

[0039] 1. UAV cluster control

[0040] Three-dimensional scene control: Displays the flight status, flight tracks, task execution status, etc. of the UAV cluster through a three-dimensional visualization interface. In the three-dimensional scene, the operator can monitor the flight dynamics of the UAV cluster in real time and control and adjust parameters such as the flight path, speed, and attitude.

[0041] Two-dimensional scene control: Displays the positions and tracks of the UAV cluster on a two-dimensional plane (ground view), which is suitable for relatively simple tasks such as ground inspection and material delivery. The two-dimensional scene control can work in coordination with the three-dimensional scene control to provide more comprehensive flight information for the operator.

[0042] Multi-aircraft cooperative control: The platform supports multi-aircraft cooperative flight. Through task scheduling, dynamic path planning, and flight status monitoring, it ensures the coordinated cooperation between UAVs, avoids collisions, reduces energy consumption, and improves operation efficiency.

[0043] Flight task scheduling: According to the priorities of different tasks, the status of UAVs, and environmental changes (such as weather, obstacles, flight areas, etc.), this module is responsible for dynamically scheduling and allocating tasks and adjusting the flight path in real time to ensure the efficient execution of tasks.

[0044] 2. Hardware cooperation control mechanism

[0045] Flight Control Node Interface: Each unmanned aircraft in the unmanned aircraft cluster is equipped with a flight control node. Through real-time data communication with the platform, it transmits flight status and sensor data (such as position, speed, attitude, environmental information) back to the control platform. Based on this data, the platform adjusts the flight parameters of the unmanned aircraft in real time to ensure that it executes tasks according to the predetermined flight path.

[0046] Onboard Computer Integration: Each unmanned aircraft is equipped with an onboard computer for processing complex flight control and sensor data. Through collaborative work with the onboard computer, the platform combines three-dimensional and two-dimensional control information to achieve functions such as dynamic path planning, obstacle avoidance, and target tracking.

[0047] Data Synchronization and Information Sharing: The platform synchronizes data with the flight control nodes and onboard computers of each unmanned aircraft through wireless communication to ensure that each unmanned aircraft can share flight status, environmental perception information, etc. in real time. This data sharing mechanism helps to improve the collaborative combat ability and decision-making efficiency of the cluster.

[0048] 3. Flight Path Planning and Obstacle Avoidance Functions

[0049] Three-Dimensional Path Planning: The platform generates the three-dimensional flight path of the unmanned aircraft according to mission requirements and environmental information (such as terrain, obstacles, flight area restrictions, etc.). The path planning module adjusts the path in real time to avoid obstacles and ensure the optimal interval between unmanned aircraft during multi-aircraft flight.

[0050] Two-Dimensional Path Planning: On the two-dimensional plane, the platform can quickly calculate and optimize the mission path. For example, in scenarios such as ground material delivery and area inspection, it adjusts the flight route in real time to avoid area overlap or flight delays.

[0051] Obstacle Avoidance and Dynamic Adjustment: Using sensor data (such as lidar, infrared sensors, ultrasonic waves, etc.), the platform can perceive the surrounding environment in real time and calculate the best obstacle avoidance strategy. When encountering sudden obstacles or flight area restrictions, the platform can immediately re-plan the path to ensure the safe flight of the unmanned aircraft cluster.

[0052] 4. Multi-Scene Control and Dynamic Feedback Mechanism

[0053] Multi-Scene Collaborative Control: The platform supports simultaneous control in three-dimensional and two-dimensional scenarios. The operator can quickly switch between different scenarios or perform joint operations on them. The coordinated work of the two scenarios can greatly improve the mission efficiency, especially in complex tasks that require cross-dimensional collaborative control.

[0054] Real-Time Feedback and Decision Support: The platform can receive data from each unmanned aircraft in real time and provide intelligent decision support through data analysis and machine learning algorithms. The system can adjust task priorities, re-plan paths, etc. based on real-time data analysis to ensure the efficiency and safety of task completion.

[0055] In summary, an unmanned aerial vehicle cluster control platform proposed in an embodiment of the present invention can achieve more efficient task scheduling and flight planning by controlling in three-dimensional and two-dimensional scenes at the same time. Three-dimensional control can ensure flight path planning and obstacle avoidance in complex environments, and two-dimensional control is suitable for simplified tasks, such as ground inspection, material delivery, etc.; the deep integration of the platform with flight control nodes, airborne computers and other hardware devices ensures real-time synchronization and information sharing of flight control data, avoids operation delays, and improves the accuracy and reliability of cluster flight; through dynamic path adjustment, obstacle avoidance technology and real-time feedback mechanism of tasks, it can effectively avoid collisions of unmanned aerial vehicle clusters and potential risks in task execution, ensuring the safe flight of unmanned aerial vehicles in complex environments; the platform can flexibly switch between three-dimensional and two-dimensional control modes according to the task type, adapt to various task requirements in different fields (such as military, agriculture, logistics, etc.), and has broad application prospects.

[0056] [Second embodiment]

[0057] The second embodiment of the present invention proposes a three-dimensional control system for a drone cluster, including: a host computer and a drone cluster. The host computer is equipped with the drone cluster control platform described in the first embodiment, which is used to control the drone cluster. It is worth mentioning that the architecture and functions implemented by the specific drone cluster control platform are as described in the first embodiment, so they will not be described in detail here, and the beneficial effects of this embodiment are the same as those of the first embodiment, so they will not be repeated here for the sake of brevity.

[0058] In addition, it can be understood that the aforementioned embodiments are only exemplary descriptions of the present invention. Under the premise that the technical features do not conflict, the structures do not contradict, and the purpose of the present invention is not violated, the technical solutions of the various embodiments can be arbitrarily combined and used in combination.

[0059] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and / or methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units / modules is only a logical function division. There may be other division methods in actual implementation, such as multiple units or modules can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0060] The unit / module described as a separation component may or may not be physically separated. The component shown as a unit / module may or may not be a physical unit, that is, it may be located in one place or distributed to multiple network units. Some or all of the units / modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0061] In addition, each functional unit / module in various embodiments of the present invention can be integrated into one processing unit / module, or each unit / module can exist physically alone, or two or more units / modules can be integrated into one unit / module. The above integrated unit / module can be implemented in the form of hardware, or in the form of hardware plus software functional unit / module.

[0062] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A drone cluster control platform, characterized in that: include: User interface module for mission configuration, real-time monitoring, and flight path visualization; The control and management module includes a 3D scene control submodule and a 2D scene control submodule, supporting the coordinated control and dynamic path planning of 3D and 2D scenes; Data processing module, used for real-time data collection, analysis and global situation awareness; The hardware collaborative interface layer communicates with the UAV's flight control node and onboard computer in real time to achieve command issuance and data synchronization; Flight mission scheduling module, dynamically adjusts task allocation according to task priority and environmental conditions; UAV cluster flight management module, coordinating multi-drone collaborative flight, obstacle avoidance and status monitoring; Among them, the platform simultaneously controls drone clusters in three-dimensional space and two-dimensional plane scenes, and realizes dynamic path planning, obstacle avoidance and multi-machine task collaboration through hardware coordination mechanism.

2. The UAV cluster control platform according to claim 1, characterized in that: The 3D scene control submodule displays the position, track and flight parameters of the UAV through a 3D visualization interface, supporting the operator to adjust the flight attitude and path in real time; The two-dimensional scene control submodule displays the position and trajectory of the UAV in a plan view to simplify path optimization and task allocation in mission scenarios.

3. The UAV cluster control platform according to claim 1, characterized in that: The hardware coordination interface layer includes: Flight control system interface, used to issue flight control commands and receive sensor data; Airborne computer interface, used to exchange environmental perception data and flight information with the UAV's onboard computer; A communication management system is used to complete low-latency data synchronization between the platform and the drone.

4. The UAV cluster control platform according to claim 1, characterized in that: The flight mission scheduling module includes a dynamic task scheduling submodule and a task priority management submodule, which automatically adjusts the task execution order according to real-time environmental data and drone status.

5. The UAV cluster control platform according to claim 1, characterized in that: The UAV cluster flight management module includes an obstacle avoidance and optimization submodule, which uses laser radar and infrared sensor data to calculate obstacle avoidance paths in real time and ensures the safety of multi-machine collaborative flight through dynamic replanning.

6. The UAV cluster control platform according to claim 5, characterized in that: When a sudden obstacle is detected, the obstacle avoidance and optimization submodule preferentially generates a local obstacle avoidance path based on a three-dimensional path planning algorithm and broadcasts it to all drones in the cluster through the communication management system.

7. The UAV cluster control platform according to claim 1, characterized in that: The data processing module performs fusion analysis on multi-aircraft sensor data through machine learning algorithms, generates global flight situation predictions, and provides decision support for mission scheduling.

8. The UAV cluster control platform according to claim 1, characterized in that: The path planning and optimization submodule generates a three-dimensional path based on terrain data and flight area restrictions, and dynamically adjusts the path through a real-time obstacle avoidance algorithm to ensure that multiple drones are at the optimal interval.

9. The UAV cluster control platform according to claim 1, characterized in that: The platform supports cross-scenario joint operations, including: responding to the operator's switching operation between three-dimensional and two-dimensional views, and achieving cross-dimensional task collaboration through a collaborative control module.

10. A three-dimensional control system for drone swarms, characterized in that: include: Host computer; drone swarms; The host computer is equipped with the drone cluster control platform as described in any one of claims 1 to 9, and is used to control the drone cluster.

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