Distributed unmanned aerial vehicle cluster control method and system in denial environment

Abstract

The invention belongs to the related technical field of multi-unmanned aerial vehicle cooperative positioning and control, and particularly relates to a distributed unmanned aerial vehicle cluster control method and system in a denial environment, and the method comprises the steps: configuring an upper-layer cooperative control subsystem and a lower-layer speed control subsystem on each unmanned aerial vehicle, and setting a master control host; the three unmanned aerial vehicles serve as UWB base stations, and upper-layer systems of other unmanned aerial vehicles obtain the horizontal distances of the unmanned aerial vehicles through UWB; each unmanned aerial vehicle lower-layer system obtains the height of the corresponding unmanned aerial vehicle in real time and transmits the height to the corresponding upper-layer system through the shared information pool; the host transmits a task instruction to the upper-layer system of each unmanned aerial vehicle through the shared message pool; and after receiving the instruction, each unmanned aerial vehicle upper-layer system calculates the horizontal position of the corresponding unmanned aerial vehicle based on the horizontal distance of the corresponding unmanned aerial vehicle and the horizontal position of each UWB base station, calculates the expected speed of the corresponding unmanned aerial vehicle according to the spatial position of the corresponding unmanned aerial vehicle, and realizes control through the corresponding lower-layer system. According to the invention, efficient control of the distributed unmanned aerial vehicle cluster in the denial environment is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field related to the collaborative positioning and control of multiple unmanned aerial vehicles (UAVs), and more specifically, relates to a distributed UAV swarm control method and system in a denied environment. Background Art

[0002] In modern UAV applications, the denied environment (an environment with limited or interfered GPS signals) poses a severe challenge to the collaboration and control capabilities of UAVs. Traditional UAV positioning methods rely on GNSS (such as GPS) signals for positioning and navigation. However, in complex or hostile environments, the reliability of GPS signals is significantly reduced, resulting in a decrease in UAV positioning accuracy and even the inability to perform tasks normally. This problem is particularly prominent in applications such as military reconnaissance and monitoring. Especially in areas with strong electromagnetic interference, GPS signals may be artificially blocked or interfered, thus restricting the collaborative combat capabilities and the flexibility of autonomous task execution of UAVs. Therefore, to address the challenges of the denied environment, it is necessary to design a UAV swarm control system that does not rely on GPS signals and can operate stably in complex environments.

[0003] In addition, the potential of UAV systems has received extensive attention. Compared with fixed-wing UAVs, small quadrotor UAVs are more suitable for performing tasks with high requirements for flight accuracy and reliability due to their strong concealment, high flight stability, and convenient operation. In this context, it is crucial to improve the collaborative capabilities and task execution efficiency of small quadrotor UAV swarms, which also poses higher requirements for the design of hardware and software systems.

[0004] In terms of hardware, it is difficult for existing systems to find an ideal balance among lightweight, stability, and high scalability. Although lightweight design helps to improve flight time and maneuverability, it may also affect the stability and load-bearing capacity of the system. In terms of stability, although existing designs focus on flight control and anti-interference capabilities, when increasing hardware scalability (such as adding sensors, computing units, etc.), it often increases the weight and complexity of the system, affecting flight performance. Therefore, how to improve the hardware scalability while ensuring the lightweight and stability of the system has become a major challenge in the design of UAV systems. And in terms of software, in complex environments, centralized control systems often cannot effectively handle communication delays or interruptions, resulting in unsatisfactory collaborative control effects.

[0005] Generally speaking, the performance of centralized collaborative control systems in terms of real-time performance, communication stability, and motion control accuracy is still insufficient to meet the high requirements for distributed collaborative flight in complex environments. Summary of the Invention

[0006] In view of the above deficiencies or improvement requirements of the prior art, the present invention provides a distributed UAV cluster control method and system in a denial environment, aiming to achieve real-time and highly communication-stable control of a distributed UAV cluster in a denial environment.

[0007] To achieve the above object, according to one aspect of the present invention, a distributed UAV cluster control method in a denial environment is provided. An upper-layer cooperative control subsystem and a lower-layer speed control subsystem are configured on each UAV, and a master control host is additionally set up to control the distributed UAV cluster in a denial environment in the following manner:

[0008] The upper-layer cooperative control subsystem of each UAV controls the flight altitude of each UAV to be the same in real time, and three preset UAVs control their flight positions unchanged and serve as UWB base stations respectively. The upper-layer cooperative control subsystems of other UAVs respectively obtain the horizontal distance information between themselves and each UWB base station through UWB; the lower-layer speed control subsystem of each UAV obtains the altitude information of the corresponding UAV in real time and transmits it to the upper-layer cooperative control subsystem of the corresponding UAV through a shared information pool.

[0009] The host transmits task instructions to the upper-layer cooperative control subsystems of each UAV through a shared message pool.

[0010] After receiving the task instructions, the upper-layer cooperative control subsystem of each UAV calculates the horizontal position information of the corresponding UAV by constructing and solving a system of equations based on the horizontal distance information of the corresponding UAV and the known horizontal position information of each UWB base station, and combines the received altitude information to obtain the spatial position information of the corresponding UAV; according to the spatial position information of the corresponding UAV and the expected spatial position for executing the task instruction, the expected speed of the corresponding UAV in the launch inertial system is calculated, the expected speed is converted to the expected speed in the NED coordinate system through coordinate transformation, and is transmitted to the lower-layer speed control subsystem of the corresponding UAV through a shared message pool to achieve flight control of the corresponding UAV.

[0011] Further, the calculation method of the horizontal position information of each UAV is as follows:

[0012]

[0013] In the formula, d 0i , d 1i , d 2i respectively represent the distances from the i-th UAV to the 0th, 1st, and 2nd UAVs, and the 0th, 1st, and 2nd UAVs are the UWB base stations respectively; (x i , y i ), (x0, y0), (x1, y1), and (x2, y2) respectively represent the horizontal positions of the i-th, 0th, 1st, and 2nd UAVs.

[0014] Furthermore, the method for determining the expected velocity (v i ' ,x , v i ' ,y , v i ' ,z ) of the i-th unmanned aerial vehicle in the launch inertial system is as follows:

[0015]

[0016] In the formula, respectively represent the three PID control parameters of the x-axis position control loop of the i-th unmanned aerial vehicle; respectively represent the three PID control parameters of the y-axis position control loop of the i-th unmanned aerial vehicle, respectively represent the three PID control parameters of the z-axis position control loop of the i-th unmanned aerial vehicle; limit represents a limiting function to ensure that the integral term is between the corresponding ±max, respectively represent the maximum value of the integral term of the i-th unmanned aerial vehicle in the control loop.

[0017] Furthermore, the method of coordinate transformation is as follows:

[0018] v i,x = v i ' ,x cosα - v' i,x sinα

[0019] v i,y = v' i,y sinα + v' i,y cosα

[0020] v i,z = v′ i,z

[0021] In the formula, α represents the angle between the launch inertial system and the NED coordinate system.

[0022] Furthermore, the method for determining the expected pitch angle θ i , roll angle φ i and yaw angle ψ i is as follows:

[0023]

[0024] In the formula, respectively represent the three PID control parameters of the x-axis velocity control loop of the i-th unmanned aerial vehicle, respectively represent the three PID control parameters of the y-axis velocity control loop of the i-th unmanned aerial vehicle, They respectively represent the three PID control parameters of the z-axis speed control loop of the i-th unmanned aerial vehicle (UAV); limit represents a limiting function to ensure that the integral term is between the corresponding ±max; They respectively represent the maximum value of the integral term of the i-th UAV in the control loop; (v i,cmdx , v i,cmdy , v i,cmdz ) represents the desired speed of the i-th UAV when performing tasks in a denied environment; (v i,x , v i,y , v i,z ) represents the actual speed of the i-th UAV.

[0025] According to another aspect of the present invention, there is provided a distributed UAV cluster control system in a denied environment for implementing a distributed UAV cluster control method in a denied environment as described above, including: a master control host, and an upper-layer collaborative control subsystem and a lower-layer speed control subsystem deployed in each UAV.

[0026] Furthermore, both the master control host and the upper-layer collaborative control subsystems of each UAV are implemented based on the ROS operating system, and the shared message pool is implemented through the MAVROS functional package; each lower-layer speed control subsystem of each UAV is implemented based on the PX4 software platform to perform lower-layer execution control on the distributed UAV cluster.

[0027] Furthermore, each upper-layer collaborative control subsystem of each UAV is divided into a master node, a state switching node, a positioning and parsing node, a task execution node, and a message packaging node; among them, the master node is used to receive task instructions from the shared message pool; the state switching node is used to parse task instructions and switch the UAV state; the task execution node is used to execute tasks according to the current UAV state and calculate the desired speed; the positioning and parsing node is used to obtain horizontal distance information in real time based on UWB, resolve horizontal position information, and combine the received height information to obtain spatial position information.

[0028] Furthermore, each upper-layer collaborative control subsystem of each UAV adopts Nooploop LinkTrack P-AS in the distributed UWB ranging mode of DRMode to implement the acquisition of UAV horizontal distance information.

[0029] Furthermore, each lower-layer speed control subsystem of each UAV adopts a laser-optical flow integrated module MTF-01 to implement the acquisition of the height information of the corresponding UAV.

[0030] Generally speaking, compared with the prior art through the above technical solutions conceived by the present invention, the technical solutions provided by the present invention mainly have the following beneficial effects:

[0031] 1. The present invention proposes a control method for a distributed UAV cluster applicable to a denied environment. Combining the flight characteristics of quadrotor UAVs, it uses UWB (Ultra Wide Band) technology for ranging. The aim is to enable a multi-UAV system to achieve precise positioning and control by measuring the relative horizontal distance when global position coordinates cannot be obtained. This system enables a multi-UAV formation to rely on relative positioning in a denied environment without relying on traditional GPS positioning technology, thus expanding the application scenarios of the multi-UAV system in complex and interfering environments. Additionally, aiming at the technical problems in traditional cooperative control systems of small rotor UAVs, such as the overly large volume of the hardware system, the mismatch between the software and hardware systems, and the centralized structure, which lead to unsatisfactory control effects and poor stability of the cluster system, this embodiment proposes the idea of hierarchical control design. It proposes to configure an upper-layer cooperative control subsystem and a lower-layer speed control subsystem on each UAV, and additionally set up a master control host for sending task instructions to each UAV and monitoring the status of each UAV. The master control host and the upper-layer cooperative control subsystems of each UAV transmit task instructions and UAV status information through a shared message pool, and cooperate to control the UAV cluster to complete tasks. The task instructions include unlocking, takeoff, task, and landing instructions. The upper-layer cooperative control subsystem and the lower-layer speed control subsystem of each UAV transmit UAV position and attitude information through the shared message pool. This hierarchical control method meets the design requirements of distributed, high-performance, small-size, and convenient communication for outdoor small rotor UAVs, and at the same time ensures that the UAVs can still stably and precisely complete distributed cooperative control tasks in an environment where GPS signals are limited or interfered with. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a flowchart of a control method for a distributed UAV cluster in a denied environment provided by an embodiment of the present invention;

[0033] Figure 2 It is a control structure diagram provided by an embodiment of the present invention;

[0034] Figure 3 It is a schematic diagram of the framework of a distributed cooperative control software system for small rotor UAVs provided by an embodiment of the present invention;

[0035] Figure 4 It is a connection diagram of ROS nodes of the software system provided by an embodiment of the present invention;

[0036] Figure 5 It is a hardware topology connection diagram of a single small rotor UAV provided by an embodiment of the present invention;

[0037] Figure 6 It is a hardware topology connection diagram of a distributed cooperation of a small rotor UAV cluster provided by an embodiment of the present invention. Detailed Implementation Manner

[0038] In order to make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0039] Embodiment 1

[0040] A distributed UAV cluster control method in a denial environment. An upper-layer collaborative control subsystem and a lower-layer speed control subsystem are configured on each UAV, and a general control host is additionally set up to send task instructions to each UAV and monitor the status of each UAV. The general control host and the upper-layer collaborative control subsystems of each UAV transmit task instructions and UAV status information through a shared message pool, and cooperate to control the UAV cluster to complete tasks. The task instructions include unlocking, taking off, task, and landing instructions; the upper-layer collaborative control subsystem and the lower-layer speed control subsystem of each UAV transmit UAV position and attitude information through the shared message pool.

[0041] The upper-layer collaborative control subsystem, the lower-layer speed control subsystem of each UAV, and the general control host, as Figure 1 shown, implement the control of the distributed UAV cluster in a denial environment in the following manner:

[0042] The upper-layer collaborative control subsystem of each UAV controls the flight heights of each UAV to be the same in real time, and three preset UAVs control their flight positions unchanged and are respectively used as UWB base stations. The upper-layer collaborative control subsystems of the other UAVs respectively obtain the horizontal distance information between themselves and each UWB base station through UWB; the lower-layer speed control subsystem of each UAV obtains the height information of the corresponding UAV in real time and transmits it to the upper-layer collaborative control subsystem of the corresponding UAV through the shared information pool.

[0043] The general control host transmits task instructions to the upper-layer collaborative control subsystems of each UAV through the shared message pool.

[0044] After receiving the mission instructions, the upper-layer cooperative control subsystem of each UAV calculates the horizontal position information of the corresponding UAV by solving a system of equations based on the horizontal distance information of the corresponding UAV and the known horizontal position information of each UWB base station, and obtains the spatial position information of the corresponding UAV by combining the received altitude information; according to the spatial position information of the corresponding UAV and the expected spatial position for executing the mission instructions, the expected velocity of the corresponding UAV in the launch inertial system is calculated, the expected velocity is converted to the expected velocity in the NED coordinate system through coordinate transformation, and is transmitted to the lower-layer velocity control subsystem of the corresponding UAV through the shared message pool to achieve the flight control of the corresponding UAV.

[0045] In a denied environment, traditional GNSS (such as GPS) positioning methods cannot work reliably. To meet the positioning requirements in a denied environment, this embodiment designs a multi-UAV cooperative positioning and control algorithm suitable for a denied environment, combines the flight characteristics of quadrotor UAVs, and uses UWB (Ultra Wide Band technology) for ranging, aiming to achieve precise positioning and control by measuring the relative horizontal distance when the multi-UAV system cannot obtain global position coordinates. This system enables the multi-UAV formation to rely on relative positioning in a denied environment without relying on traditional GPS positioning technology, thus expanding the application scenarios of the multi-UAV system in complex and interference environments. Additionally, in military and civilian fields (such as terrain exploration, cooperative reconnaissance, power inspection, logistics and express delivery, etc.).

[0046] Furthermore, aiming at the technical problems in traditional small rotor UAV cooperative control systems, such as the too large volume of the hardware system, the mismatch between the software and hardware systems, and the centralized structure, resulting in unsatisfactory control effects and poor stability of the cluster system, this embodiment proposes the idea of hierarchical control design, proposes to configure an upper-layer cooperative control subsystem and a lower-layer velocity control subsystem on each UAV, and additionally set up a master control host for sending mission instructions to each UAV and monitoring the status of each UAV. The master control host and the upper-layer cooperative control subsystems of each UAV transmit mission instructions and UAV status information through the shared message pool to cooperate and divide the work to control the UAV cluster to complete the mission. The mission instructions include unlocking, takeoff, mission, and landing instructions; the upper-layer cooperative control subsystem and the lower-layer velocity control subsystem of each UAV transmit UAV position and attitude information through the shared message pool. This hierarchical control method meets the design requirements of distributed, high-performance, small size, and convenient communication for outdoor small rotor UAVs, while ensuring that the UAVs can still stably and accurately complete the distributed cooperative control task in an environment where GPS signals are limited or interfered. This design not only improves the robustness of the system but also enables efficient cluster cooperative operations in complex environments, giving full play to the advantages of the multi-UAV system in a denied environment.

[0047] As a preferred embodiment, a coordinate system is established in the denial environment. To facilitate the description of the UWB horizontal cooperative positioning algorithm, it is assumed here that the heights of each UAV are the same, and only the horizontal positions of the UAVs are considered. Let the horizontal position of the i-th aircraft be (x i , y i ). The distance from the i-th UAV to the j-th UAV is d ij . Taking UAVs 0, 1, and 2 as the reference, the positions of other UAVs in the denial environment can be calculated by the following formula (inverse-solving the self-position coordinates based on the coordinates of the three positioning aircraft):

[0048]

[0049] In the formula, d 0i , d 1i , d 2i respectively represent the distances from the i-th UAV to UAVs 0, 1, and 2, and UAVs 0, 1, and 2 are the UWB base stations respectively; (x i , y i ), (x0, y0), (x1, y1), and (x2, y2) respectively represent the horizontal positions of the i-th, 0-th, 1-st, and 2-nd aircraft.

[0050] Then, the lower-layer speed control subsystem of each UAV, according to the laser data, fuses the data of the barometer and inertial navigation unit configured in its own lower layer to obtain the altitude information of the UAV and transmits it to the upper-layer cooperative control subsystem of the UAV. Preferably, the laser-optical flow integrated module can be MTF-01. Therefore, the position information of the i-th UAV is recorded as (x i , y i , z i ). In addition, let the expected position of the i-th UAV performing tasks in the denial environment be (x i,cmd , y i,cmd , z i,cmd ). Design the i-th PID controller. The upper layer of the i-th one obtains the expected speed (v' i,x , v' i,y , v' i,z ) of the UAV in the launch inertial system.

[0051] As a preferred embodiment, the determination method of the expected speed (v i ', v ,x , v i ', v ,y , v i ', v ,z ) of the i-th UAV in the launch inertial system is as follows:

[0052]

[0053] In the formula, respectively represent the three PID control parameters of the x-axis position control loop of the i-th unmanned aerial vehicle; respectively represent the three PID control parameters of the y-axis position control loop of the i-th unmanned aerial vehicle, respectively represent the three PID control parameters of the z-axis position control loop of the i-th unmanned aerial vehicle; limit represents the amplitude limiting function to ensure that the integral term is between the corresponding ±max, respectively represent the maximum value of the integral term of the i-th unmanned aerial vehicle in the control loop.

[0054] Since the position information of the unmanned aerial vehicle is based on the denied environment coordinate system (consistent with the direction of the unmanned aerial vehicle launch inertial system), the obtained (v' i,x , v' i,y , v' i,z ) refers to the desired velocity in the unmanned aerial vehicle launch inertial system, while the velocity information used in PX4 to calculate the actual motor control amount is based on the NED coordinate system. Therefore, coordinate transformation is required.

[0055] As a preferred implementation, the method of coordinate transformation is:

[0056] v i,x = v' i,x cosα - v' i,x sinα

[0057] v i,y = v' i,y sinα + v' i,y cosα

[0058] v i,z = v′ i,z

[0059] In the formula, α represents the angle between the launch inertial system and the NED coordinate system.

[0060] After the upper-layer cooperative control subsystem obtains the desired velocity in the NED, PX4 can receive the desired velocity transmitted by MAVROS and achieve fast and accurate tracking of it. The controller structure is as Figure 2 shown.

[0061] According to Figure 2 , the conversion relationship between the velocity in the unmanned aerial vehicle launch inertial system and the velocity in the northeast sky satisfies the above coordinate transformation formula. The converted velocity obtains the desired pitch angle θ i , roll angle φ i and yaw angle ψ i through the cascaded velocity controller and attitude controller.

[0062] As a preferred implementation, the desired pitch angle θi , the roll angle φ i and the yaw angle ψ i are determined as follows:

[0063]

[0064] In the formula, respectively represent the three control parameters of the PID of the x-axis speed control loop of the i-th UAV, respectively represent the three control parameters of the PID of the y-axis speed control loop of the i-th UAV, respectively represent the three control parameters of the PID of the z-axis speed control loop of the i-th UAV; limit represents the amplitude limiting function to ensure that the integral term is between the corresponding ±max; respectively represent the maximum value of the integral term of the i-th UAV in the control loop; (v i,cmdx , v i,cmdy , v i,cmdz ) represents the expected speed of the i-th UAV to perform tasks in the denied environment; (v i,x , v i,y , v i,z ) represents the actual speed of the i-th UAV.

[0065] Embodiment 2

[0066] A distributed UAV cluster control system in a denied environment, which is used to execute a distributed UAV cluster control method in a denied environment as described in Embodiment 1 above, includes: a master control host, and an upper-layer cooperative control subsystem and a lower-layer speed control subsystem deployed in each UAV.

[0067] As a preferred implementation, both the master control host and the upper-layer cooperative control subsystems of each UAV are implemented based on the ROS operating system, and the shared message pool is implemented through the MAVROS function package; each UAV lower-layer speed control subsystem is implemented based on the PX4 software platform to perform lower-layer execution control on the distributed UAV cluster.

[0068] By adopting the UWB ranging method, combined with a lightweight and modular hardware platform and an extensible software framework, a stable and efficient multi-UAV cooperative flight system in a denied environment is constructed, which can effectively improve the adaptability of the UAV cluster in a complex environment, break through the limitations of traditional GNSS positioning, and provide strong technical support for the wide application of UAVs in a denied environment in the future.

[0069] In specific implementation, as a preferred implementation manner, each upper-layer cooperative control subsystem of the UAVs is divided into a master node, a state switching node, a positioning and parsing node, a task execution node, and a message packaging node; wherein, the master node is used to receive task instructions from the shared message pool; the state switching node is used to parse the task instructions and switch the UAV state; the task execution node is used to execute tasks according to the current UAV state and calculate the desired speed; the positioning and parsing node is used to obtain horizontal distance information in real time based on UWB, calculate horizontal position information, and obtain spatial position information by combining the received height information.

[0070] In specific implementation, as a preferred implementation manner, each lower-layer speed control subsystem of the UAVs adopts a laser-optical flow integrated module MTF-01 to obtain the height information of the corresponding UAV.

[0071] The distributed cooperative control software system of small rotor UAVs is as Figure 3 shown on the left. This system is mainly divided into two sub-modules, an upper-layer cooperative control subsystem based on ROS and a lower-layer speed control subsystem based on the PX4 software system.

[0072] The upper-layer cooperative control subsystem obtains the UWB horizontal distance information between adjacent aircrafts packaged by LinkTrack through the ROS function package, and obtains sensor data in the MAVLINK message format from the lower-layer speed control subsystem through the MAVROS function package, including the vertical height information of the UAV obtained by laser, as well as the fused UAV position information, Euler angle attitude information, flight speed information, etc. In addition, the host can send unlocking, takeoff, task, and landing instructions to each UAV, monitor the state of each UAV, and each UAV receives the control instructions sent by the host and the state information of other UAVs through the Discovery mechanism of ROS, executes its own tasks according to the host instructions or the state information of other UAVs, and sends the current UAV desired speed (in the NED coordinate system) instruction to the lower-layer speed loop through the MAVROS function package. Then, the lower-layer control system completes speed control and attitude control, and finally sends control instructions to the four motors to achieve coordinated control of the UAV cluster system.

[0073] For software-level operations, it is necessary to upload flight tasks to each UAV first. Enter flight instructions into the shared message pool through the ground terminal computer (host), including stages such as one-key unlocking, one-key takeoff, task mode, and return and landing. Based on the tasks in each stage, each UAV calculates the corresponding desired speed instruction based on the flight instructions and the current state, and sends it to PX4 for PID speed control and attitude control. The entire process is as Figure 3 shown in the middle part.

[0074] The ROS nodes of this system are divided into the main node uav_main, the state switching node switch_uav_node, the message packaging node pack_uav_states, the positioning parsing nodes linktrack_uav, uwb_uav, and the task execution nodes search_uav, detect_uav. The main node uav_main is responsible for scheduling different tasks; the state switching node switch_uav_node is responsible for processing the task instructions sent by the host, controlling the task state switching between flight phases such as unlocking, taking off, performing tasks, and landing of each UAV. It can not only control a single UAV separately, but also control all UAVs simultaneously; the message packaging node pack_uav_states receives status and control instructions from the execution nodes, and packages this information and sends it to the MAVROS message pool for other UAVs and PX4 to use; the positioning parsing nodes linktrack_uav, uwb_uav are responsible for parsing UWB information and performing UAV position calculations; the task execution nodes search_uav, detect_uav contain the tasks corresponding to each UAV. The connection diagram between the nodes is as shown in Figure 4 shown.

[0075] The software design of the collaborative control system can be divided into three stages: information acquisition, search task execution, and information publishing stage. As shown in the right part of Figure 3 Figure. First, three positioning aircraft fly at a fixed altitude to act as UWB base stations, establish a denied environment coordinate system, and then the remaining UAVs respectively obtain the distance information between themselves and each positioning aircraft according to UWB, and calculate their own position information. Then comes the search task execution stage, including tasks such as grid search, YOLO detection, and flying towards the landing point. Finally, during the execution of the task, it is necessary to continuously publish its own desired speed and status information to the shared information pool.

[0076] This embodiment realizes the positioning of the UAV in the horizontal direction through UWB. The ranging method used is UWB, and the ranging module model can be preferably Nooploop LinkTrack P-AS. This module can provide centimeter-level accurate distance measurement within a range of 40 meters. The distributed ranging mode of DR Mode is adopted, and thus the distance information between UAVs can be obtained.

[0077] The collaborative control hardware system of small rotor UAVs mainly includes an upper-layer collaborative control subsystem, a lower-layer speed control subsystem, a power management system, and an actuator system. The upper-layer collaborative control subsystem includes a host computer and the on-board computers of all UAVs, which communicate through a radio to form a self-organizing network. Under this self-organizing network, the host computer can monitor the status of each UAV and control its modes (flight phases such as unlocking, takeoff, mission, landing, etc.), ensuring the safe control of the cluster UAVs to a certain extent. The upper-layer collaborative control subsystem of each UAV can obtain sensor data, including sensor data from UWB, laser optical flow, cameras, inertial sensing units, etc., as well as information such as the speed and attitude of the UAV. It can also obtain the status information of neighboring UAVs, such as their positions and speeds, from adjacent UAVs. After being processed by the collaborative controller, it sends the desired speed and throttle information to the lower-layer speed control subsystem. The lower-layer speed control subsystem uses PID control to regulate the rotational speeds of the four motors to achieve stable speed tracking. Additionally, the host computer can monitor the position and attitude information of all UAVs and can timely assign tasks and schedule the UAVs. The power management system is responsible for supplying power to each component unit. The actuator system controls the rotational speeds of the four motors according to the instructions of the underlying control system. The hardware connection topology diagram of a single UAV is as Figure 5 shown.

[0078] Each UAV can form a UAV network through the radio, receive control instructions from the host computer and the status and position information of other UAVs, calculate its own position based on this information, and execute tasks in different phases, such as positioning, searching, landing at the target point, etc., and finally collaborate to achieve the goal. The collaborative hardware topology diagram is as Figure 6 shown.

[0079] As an implementation example, the upper control board uses a Nano TX2 development board, with an operating system environment of Ubuntu18.04, on which a ROS system is configured. It can achieve information transmission with the Pixhawk underlying control board through the loaded MAVROS function package. In addition, the upper-layer collaborative control subsystem is equipped with a camera, a UWB module, and a communication radio module. Combining information such as laser optical flow, it can help the cluster UAVs complete tasks such as collaborative positioning, target recognition, and distributed communication in a denied environment.

[0080] The lower-layer speed control subsystem uses a relatively small-sized Pixhawk Mini4 main control board for the underlying speed tracking control of the UAV. This control board integrates on-board sensors: IMU and gyroscope. PX4 generates control instructions for the underlying brushless motors of the UAV through the PID speed control algorithm by receiving the UAV pose information sent by the upper-layer collaborative control subsystem and combining the data of the inertial navigation unit IMU and the gyroscope, realizing stable speed tracking control of the UAV.

[0081] The power management system of the small rotor UAV is divided into three parts: lithium-platinum battery, battery-free circuit BEC, and power management module. The power supply line of the battery can be divided into three parts. The first part supplies power to the Pixhawk flight control board and nano board through the power management module. The second part passes through the power management module and connects to the electronic speed controller to supply power to the power system motor. The third part directly connects to the 5v BEC module, and the output is connected to the Pixhawk I / O port to balance the voltage.

[0082] The actuators of the small rotor UAV include four brushless motors and two pairs of three-blade five-inch propellers. By controlling the rotation speed of the four motors, the takeoff and landing of the UAV are achieved, the attitude of the UAV is adjusted, and then the position and speed of the UAV are adjusted.

[0083] The related technical solutions are the same as those in Embodiment 1 and will not be elaborated here.

[0084] Generally speaking, in modern UAV applications, the positioning of traditional UAVs relies on GNSS, which limits the cooperative combat ability and flexibility of autonomous mission execution of UAVs. This problem is particularly prominent in applications such as military reconnaissance and monitoring. To address the challenges of the denial environment, the present invention designs a multi-UAV cooperative control system that uses UWB and laser and integrates optical flow, inertial measurement unit, etc. to achieve positioning. Secondly, aiming at the technical problems existing in the traditional small rotor UAV cooperative control system, such as the too large volume of the hardware system, the mismatch between the software and hardware systems, and the poor stability of the cluster system, the present invention designs a lightweight rotor UAV cooperative control software and hardware system suitable for the denial environment by combining the idea of hierarchical design. In addition, the performance of the centralized cooperative control system in terms of real-time performance, communication stability, and motion control accuracy is still insufficient to meet the high requirements for distributed cooperative flight in complex environments. A multi-UAV cooperative flight system combining an efficient distributed control architecture and autonomous perception positioning technology is designed. In summary, by adopting the UWB ranging method and combining a lightweight and modular hardware platform and an extensible software framework, the present invention constructs a stable and efficient multi-UAV cooperative flight system in the denial environment, which can effectively improve the adaptability of the UAV cluster in complex environments, break through the limitations of traditional GNSS positioning, ensure the stability and real-time performance of communication, and provide a solid technical guarantee for the wide application of UAVs in the denial environment in the future. A multi-UAV cooperative flight system designed by the present invention that combines an efficient distributed control architecture and autonomous perception positioning technology has become the key to improving the cluster mission execution ability and application scenario adaptability.

[0085] It is easy for those skilled in the art to understand that the above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A distributed UAV cluster control method in a denial environment, characterized in that: An upper-layer collaborative control subsystem and a lower-layer speed control subsystem are configured on each drone, and a master control host is also set up to control the distributed drone cluster in a denied environment in the following ways: The upper-layer cooperative control subsystem of each drone controls the flight altitude of each drone in real time, and the three preset drones keep their flight positions unchanged, serving as UWB base stations. The upper-layer cooperative control subsystems of other drones obtain the horizontal distance information between themselves and each UWB base station through UWB; the lower-layer speed control subsystem of each drone obtains the altitude information of the corresponding drone in real time and transmits it to the upper-layer cooperative control subsystem of the corresponding drone through the shared information pool; The host transmits task instructions to the upper-level collaborative control subsystems of each UAV through a shared message pool; After receiving the task instruction, the upper-level collaborative control subsystem of each UAV obtains the horizontal position information of the corresponding UAV by constructing a set of equations to solve it based on the horizontal distance information of the corresponding UAV and the known horizontal position information of each UWB base station, and obtains the spatial position information of the corresponding UAV in combination with the received altitude information; according to the spatial position information of the corresponding UAV and the preset expected spatial position for executing the task instruction, the expected speed of the corresponding UAV in the launching inertial system is calculated, the expected speed is obtained through coordinate transformation to obtain the expected speed in the NED coordinate system, and is transmitted to the lower-level speed control subsystem of the corresponding UAV through the shared message pool to realize the flight control of the corresponding UAV.

2. The distributed UAV cluster control method according to claim 1, characterized in that: The calculation method of the horizontal position information of each UAV is: Where, d 0i ,d 1i ,d 2i Respectively represent the distances from the ith UAV to the 0th, 1st, and 2nd UAVs, where the 0th, 1st, and 2nd UAVs are the UWB base stations; (x i ,y i ), (x0,y0), (x1,y1), and (x2,y2) represent the horizontal positions of the i-th, 0-th, 1-th, and 2-th aircraft respectively.

3. The distributed UAV cluster control method according to claim 1, characterized in that: The expected speed of the i-th UAV in the launch inertial system (v' i,x ,v' i,y ,v' i,z ) is determined as follows: In the formula, They represent the three PID control parameters of the x-axis position control loop of the i-th UAV; They represent the three PID control parameters of the y-axis position control loop of the i-th UAV, They represent the three PID control parameters of the z-axis position control loop of the i-th drone; limit represents the limit function, which ensures that the integral term is between the corresponding ±max. They represent the maximum value of the integral term of the i-th UAV in the control loop; (x i,cmd ,y i,cmd ,z i,cmd ) represents the expected position of the i-th UAV in the denied environment to perform the mission; (x i ,y i ,z i ) represents the spatial position information of the i-th UAV.

4. The distributed UAV cluster control method according to claim 1, characterized in that: The coordinate conversion method is: v i,x =v' i,x cosα-v' i,x sinα v i,y =v' i,y sinα+v' i,y cosα v i,z =v' i,z Where α represents the angle between the launch inertial system and the NED coordinate system.

5. The distributed UAV cluster control method according to claim 1, characterized in that: Expected pitch angle θ i 、Roll angle φ i and yaw angle ψ i The method of determining is: In the formula, They represent the three PID control parameters of the x-axis speed control loop of the i-th drone, They represent the three PID control parameters of the y-axis speed control loop of the i-th UAV, They represent the three PID control parameters of the z-axis speed control loop of the i-th UAV respectively; limit represents the limit function to ensure that the integral term is between the corresponding ±max; They represent the maximum value of the integral term of the i-th UAV in the control loop; (v i,cmdx ,v i,cmdy ,v i,cmdz ) represents the expected speed of the i-th UAV to perform tasks in a denied environment; (v i,x ,v i,y ,v i,z ) represents the actual speed of the i-th UAV.

6. A distributed drone cluster control system in a denial environment, characterized in that: A distributed UAV cluster control method in a denied environment is used to execute the method as described in any one of claims 1 to 5, comprising: a master control host, and an upper-layer collaborative control subsystem and a lower-layer speed control subsystem deployed in each UAV.

7. The distributed UAV cluster control system according to claim 6, characterized in that: The master control host and the upper-level collaborative control subsystems of each drone are all implemented based on the ROS operating system, and the shared message pool is implemented through the MAVROS function package; the lower-level speed control subsystems of each drone are based on the PX4 software platform to implement lower-level execution control of the distributed drone cluster.

8. The distributed UAV cluster control system according to claim 7, characterized in that: The upper-layer collaborative control subsystem of each UAV is divided into a main node, a state switching node, a positioning and parsing node, a task execution node and a message packaging node; wherein the main node is used to receive task instructions from a shared message pool; the state switching node is used to parse task instructions and switch the UAV state; the task execution node is used to execute tasks according to the current UAV state and calculate the expected speed; the positioning and parsing node is used to obtain horizontal distance information based on UWB in real time, solve horizontal position information, and obtain spatial position information in combination with the received altitude information.

9. The distributed UAV cluster control system according to claim 6, characterized in that: The upper-layer collaborative control subsystem of each UAV adopts Nooploop LinkTrack P-AS in the distributed UWB ranging mode of DR Mode to obtain the horizontal distance information of the UAV.

10. The distributed UAV cluster control system according to claim 6, characterized in that: The lower-level speed control subsystem of each UAV adopts the laser-optical flow integrated module MTF-01 to obtain the altitude information of the corresponding UAV.

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