Multi-unmanned aerial vehicle circulating task relay planning method

Abstract

The invention discloses a multi-unmanned aerial vehicle circulating task relay planning method, and belongs to the field of task planning. The method comprises the steps of firstly constructing an unmanned aerial vehicle electric quantity endurance model; then constructing an unmanned aerial vehicle circulating task arrangement mechanism; then constructing a task relay mechanism; then task parameters are set and loaded into the unmanned aerial vehicle; then, the multiple unmanned aerial vehicles autonomously perform task planning and execute tasks according to the task parameters; on the basis of an unmanned aerial vehicle electric quantity endurance model and a task arrangement mechanism, and then on the basis of a task relay mechanism, replacement and return flight battery replacement are carried out; and repeatedly executing until the task is finished. The unmanned aerial vehicle electric quantity endurance model is constructed, a multi-unmanned aerial vehicle circulating task arrangement mechanism is designed, unmanned aerial vehicle tasks are divided into stages of ascending, advancing, homeward voyage, descending and the like, the influence of the wind speed and the wind direction on the electric quantity of each stage is considered, the task execution capacity of the unmanned aerial vehicle in a complex scene is improved, and the task relay efficiency of the unmanned aerial vehicle is improved. The problem of insufficient endurance time of a single unmanned aerial vehicle is solved.

Description

Technical Field

[0001] This invention relates to the field of mission planning, and in particular to a multi-UAV cyclical mission relay planning method, which solves the problem of insufficient UAV endurance in complex scenarios. Background Technology

[0002] With the widespread application of drone technology in environmental monitoring, material delivery, and agricultural plant protection, the demand for long-duration operations in complex scenarios is increasing daily. For example, regular inspections of large ecological reserves require multispectral imaging of areas spanning thousands of square kilometers; cross-sea material delivery missions require cross-regional transport along designated routes; and forest fire monitoring requires continuous thermal imaging detection of high-risk areas for hours or even days. These tasks generally feature large spatial spans, long operation cycles, and high data collection requirements, posing challenges to improving the mission planning capabilities of drones.

[0003] However, current drone operations still face numerous technical bottlenecks. On the one hand, limited by factors such as battery energy density, aerodynamic design, and motor efficiency, the flight time of a single drone is typically 30-120 minutes, making it difficult to independently complete long-duration, long-distance continuous tasks. Manually replacing batteries or refueling not only causes mission interruptions but may also introduce safety risks due to takeoff and landing operations. On the other hand, traditional single-point mission planning methods are only suitable for simple scenarios. In complex tasks involving multi-drone collaboration, dynamic path planning adjustments, and task priority switching, problems such as frequent path conflicts, low resource utilization, and poor task coordination efficiency arise. Existing technologies struggle to achieve seamless relay among multiple drones in complex mission environments, leading to low mission execution efficiency and even the inability to complete critical mission nodes due to insufficient flight time. Therefore, there is an urgent need for a cyclical flight mission relay planning method that can overcome flight time limitations and optimize multi-drone collaborative operations to meet the long-duration operational needs in highly complex scenarios. Summary of the Invention

[0004] This invention addresses the problem of continuous execution of UAV missions in complex scenarios by proposing a multi-UAV cyclical mission relay planning method to solve the difficulty of continuous mission execution caused by short UAV endurance and high mission complexity.

[0005] The technical solution adopted in this invention is as follows:

[0006] A method for planning relay missions involving multiple unmanned aerial vehicles (UAVs) includes the following steps:

[0007] (1) Construct a model for the battery life of a drone;

[0008] (2) Construct a cyclical task scheduling mechanism for unmanned aerial vehicles (UAVs);

[0009] (3) Establish a task relay mechanism;

[0010] (4) Set the mission parameters and load them into the UAV;

[0011] (5) One group of UAVs takes off, autonomously plans the mission based on the mission parameters, and executes the mission;

[0012] (6) Based on the UAV battery life model and task scheduling mechanism, obtain two sets of UAV takeoff times;

[0013] (7) Two groups of UAVs take off and autonomously plan their missions according to the mission parameters, and fly to the mission area;

[0014] (8) Based on the task relay mechanism, UAV group 2 takes over the task from UAV group 1, and UAV group 1 returns to base and swaps batteries;

[0015] (9) The subsequent execution process is analogous to steps (5)-(8) until the task is completed.

[0016] Furthermore, the UAV battery life model described in step (1) is represented as follows:

[0017] ;

[0018] in, This indicates the total battery capacity of the drone. and These represent the power consumption per unit distance the drone ascends and descends, respectively. and These represent the drone's ascent and descent velocity vectors, respectively. Indicates the drone's flight altitude. Represents the wind speed vector. , and These represent wind speeds in the geodetic coordinate system. , and Coordinates in direction This indicates the amount of electricity consumed per unit distance the drone flies horizontally. This indicates the distance between the drone's takeoff point and the mission area. This represents the forward velocity vector of the drone. and The heading of the UAV during its forward movement is indicated in the geodetic coordinate system. and Directional coordinates This represents the return-to-home velocity vector of the drone. and The heading during the drone's return journey is indicated in the geodetic coordinate system. and Directional coordinates This indicates the amount of electricity consumed per unit of time the drone hovers. Indicates the hovering time. This indicates the safe battery level reserved by the drone; depending on different mission parameters, the hovering time capability for performing the mission can be obtained based on the aforementioned drone battery life model.

[0019] Furthermore, the UAV cyclic mission orchestration mechanism described in step (2) is represented as follows:

[0020] Multiple drones are divided into several drone groups. Drones within each group are paired up for cyclical missions. In a cyclical mission involving two drones, the trigger for drone 2 to depart during the mission is to ensure that drone 1 has sufficient remaining battery power for return, landing, and safety when drone 2 arrives at the mission area. The specific calculation method is as follows:

[0021] (2a) Let the departure time of UAV 1 be ;

[0022] (2b) Total duration of mission performed by UAV 1 Represented as:

[0023] ;

[0024] in, The magnitude of the drone's ascent velocity. The descent speed modulus of the drone. The forward velocity modulus of the drone. The return-to-home speed modulus of the drone;

[0025] (2c) The time when UAV 2 arrives at the mission area Represented as:

[0026] ;

[0027] (2d) The departure time of UAV 2 is Represented as:

[0028] .

[0029] Furthermore, the task relay mechanism described in step (3) is represented as follows:

[0030] During the cyclical execution of tasks by drones in pairs between groups, the specific method of task relay is as follows: drones in pairs between groups directly share task parameters. When a new drone arrives at the task area, it directly loads the task parameters and starts executing the task, while the corresponding drone that is already executing the task simply returns to base.

[0031] Furthermore, the autonomous task planning method described in step (5) is as follows:

[0032] (5a) Separate each UAV in UAV group 1 in sequence according to a fixed height difference;

[0033] (5b) For any one of the drones, its starting point is denoted as The endpoint of the task area is denoted as ;

[0034] (5c) The center of the line connecting the start and end points of the UAV is represented as ;

[0035] (5d) The planned forward flight path of the UAV is: The planned return flight path is as follows: ,in - exist - The direction of the perpendicular line, - exist - The angle is counterclockwise. .

[0036] Furthermore, the autonomous task planning method described in step (7) is as follows:

[0037] (7a) Separate each UAV in the two groups of UAVs according to a fixed height difference;

[0038] (7b) For any one of the drones, its starting point is denoted as The endpoint of the task area is denoted as ;

[0039] (7c) The center of the line connecting the start and end points of the UAV is represented as ;

[0040] (7d) The planned forward flight path of the UAV is: The planned return flight path is as follows: ,in - exist - The direction of the perpendicular line, - exist - The angle is clockwise. .

[0041] Compared with the prior art, the present invention has the following advantages:

[0042] 1. This invention constructs a drone battery life model, which divides the drone mission into stages such as ascent, forward movement, return, and descent, and considers the impact of wind speed and wind direction on the battery life of each stage, and finally retains a safe battery level.

[0043] 2. This invention designs a multi-UAV cyclical task orchestration mechanism, which can improve the task execution capability of UAVs in complex scenarios and solve the problem of insufficient battery life of a single UAV.

[0044] 3. This invention designs a multi-UAV mission relay mechanism, which improves the efficiency of UAV mission relay by sharing mission parameters among multiple UAVs and loading mission parameters. Attached Figure Description

[0045] Figure 1 This is a schematic diagram of the overall process of the present invention.

[0046] Figure 2 This is a schematic diagram of the task planning of the present invention. Detailed Implementation

[0047] The following will clearly and completely describe the concept, technical advantages, and resulting technical effects of the present invention with reference to embodiments, so as to fully understand the purpose, features, and effects of the present invention. It should be noted that the specific embodiments described herein are only used to explain the present invention and do not limit the present invention.

[0048] See Figure 1 This embodiment provides a multi-UAV cyclical mission relay planning method, which includes:

[0049] S1: Construct a drone battery life model, represented as follows:

[0050] ;

[0051] in, This indicates the total battery capacity of the drone. and These represent the power consumption per unit distance the drone ascends and descends, respectively. and These represent the drone's ascent and descent velocity vectors, respectively. Indicates the drone's flight altitude. Represents the wind speed vector. , and These represent wind speeds in the geodetic coordinate system. , and Coordinates in direction This indicates the amount of electricity consumed per unit distance the drone flies horizontally. This indicates the distance between the drone's takeoff point and the mission area. This represents the forward velocity vector of the drone. and The heading of the UAV during its forward movement is indicated in the geodetic coordinate system. and Directional coordinates This represents the return-to-home velocity vector of the drone. and The heading during the drone's return journey is indicated in the geodetic coordinate system. and Directional coordinates This indicates the amount of electricity consumed per unit of time the drone hovers. Indicates the hovering time. This indicates the safe battery level reserved by the drone; depending on different mission parameters, the hovering time capability for performing the mission can be obtained based on the aforementioned drone battery life model.

[0052] S2: Construct a recurring UAV mission orchestration mechanism, as shown below:

[0053] Of the two drones, the reason why drone group 1 takes off repeatedly during the mission while drone group 2 is to ensure that when drone group 2 arrives at the mission area, drone group 1 still has enough battery power for return, landing, and safety. The specific calculation method is as follows:

[0054] Let the departure time of drone group 1 be ;

[0055] Total mission duration of drone group 1 Represented as:

[0056] ;

[0057] Arrival time of drone group 2 in the mission area It can be represented as:

[0058] ;

[0059] The departure time of drone group 2 is It can be represented as:

[0060] ;

[0061] S3: Construct a task relay mechanism, as shown below:

[0062] When multiple drones are performing tasks in a loop, the specific method of task relay is that multiple drones directly share task parameters. When a new drone arrives at the task area, it directly loads the task parameters and starts to execute the task, while another drone can simply return to base.

[0063] S4: Set the mission parameters and load them into the drone;

[0064] The mission parameters include various parameters for the UAV to perform the mission, such as observation altitude, observation angle, observation position, and other parameters.

[0065] S5: One group of drones takes off, autonomously plans and executes the mission according to the mission parameters, referring to... Figure 2 The specific planning method is as follows:

[0066] Let the starting point of the drone be... The endpoint of the mission area is ;

[0067] The center of the drone's start-end line (start point - end point) is represented as: ;

[0068] The planned waypoints for the drone are: , , ,in - exist - The direction of the perpendicular line, - exist - The angle is counterclockwise. ;

[0069] The drones in drone group 1 are separated by a fixed altitude difference.

[0070] S6: Based on the UAV battery life model and mission scheduling mechanism, obtain two sets of UAV takeoff times;

[0071] S7: Two groups of drones take off, autonomously plan their missions based on mission parameters, and execute the missions, referring to... Figure 2 The specific planning method is as follows:

[0072] Let the starting point of the drone be... The endpoint of the mission area is ;

[0073] The center of the drone's start-end line (start point - end point) is represented as: ;

[0074] The planned waypoints for the drone are: , , ,in - exist - The direction of the perpendicular line, - exist - The angle is clockwise. ;

[0075] The drones in the two drone groups are separated by a fixed altitude difference.

[0076] S8: Based on the mission relay mechanism, two groups of drones take over the mission from one group of drones, and one group of drones returns to base and swaps batteries;

[0077] S9: The subsequent execution process is analogous to steps S5-S8, until the task is completed.

[0078] After drone group 1 returns and finishes battery swapping, based on the departure time of drone group 2... Analogous to steps S5-S8, a mission relay is performed. When the mission trajectory is long, multiple groups of drones sequentially perform a relay, return, and battery swap process until the mission is completed. In the relay, fixed altitude differences and included angles are set between the two groups of drones. To ensure that no flight path conflicts occur during drone handover and return, in addition, such as Figure 2 As shown, a safe flight distance is set. In two groups of drones that take turns executing tasks, the distance between the endpoint target point 1 and target point 2 in the task area of ​​each pair of corresponding drones is the safe flight distance. This is to prevent flight path conflicts while ensuring that the task parameters are met and the task is executed in turn.

Claims

1. A multi-UAV cyclical relay mission planning method, characterized in that: Includes the following steps: (1) Construct a model for the battery life of a drone; (2) Construct a cyclical task scheduling mechanism for unmanned aerial vehicles (UAVs); (3) Establish a task relay mechanism; (4) Set the mission parameters and load them into the UAV; (5) One group of UAVs takes off, autonomously plans the mission based on the mission parameters, and executes the mission; (6) Based on the UAV battery life model and task scheduling mechanism, obtain two sets of UAV takeoff times; (7) Two groups of UAVs take off and autonomously plan their missions according to the mission parameters, and fly to the mission area; (8) Based on the task relay mechanism, UAV group 2 takes over the task from UAV group 1, and UAV group 1 returns to base and swaps batteries; (9) The subsequent execution process is analogous to steps (5)-(8) until the task is completed.

2. The multi-UAV cyclic reciprocating mission relay planning method according to claim 1, characterized in that: The drone battery life model described in step (1) is represented as follows: ； in, This indicates the total battery capacity of the drone. and These represent the power consumption per unit distance the drone ascends and descends, respectively. and These represent the drone's ascent and descent velocity vectors, respectively. Indicates the drone's flight altitude. Represents the wind speed vector. , and These represent wind speeds in the geodetic coordinate system. , and Coordinates in direction This indicates the amount of electricity consumed per unit distance the drone flies horizontally. This indicates the distance between the drone's takeoff point and the mission area. This represents the forward velocity vector of the drone. and The heading of the UAV during its forward movement is indicated in the geodetic coordinate system. and Directional coordinates This represents the return-to-home velocity vector of the drone. and The heading during the drone's return journey is indicated in the geodetic coordinate system. and Directional coordinates This indicates the amount of electricity consumed per unit of time the drone hovers. Indicates hover time. This indicates the safe battery level reserved by the drone; depending on different mission parameters, the hovering time capability for performing the mission can be obtained based on the aforementioned drone battery life model.

3. The multi-UAV cyclic reciprocating mission relay planning method according to claim 2, characterized in that: The UAV cyclic mission orchestration mechanism described in step (2) is as follows: Multiple drones are divided into several drone groups. Drones within each group are paired up for cyclical missions. In a cyclical mission involving two drones, the trigger for drone 2 to depart during the mission is to ensure that drone 1 has sufficient remaining battery power for return, landing, and safety when drone 2 arrives at the mission area. The specific calculation method is as follows: (2a) Let the departure time of UAV 1 be ; (2b) Total duration of mission performed by UAV 1 Represented as: ； in, The magnitude of the drone's ascent velocity. The descent speed modulus of the drone. The forward velocity modulus of the drone. The return-to-home speed modulus of the drone; (2c) The time when UAV 2 arrives at the mission area Represented as: ； (2d) The departure time of UAV 2 is Represented as: 。 4. The multi-UAV cyclic reciprocating mission relay planning method according to claim 1, characterized in that: The task relay mechanism described in step (3) is represented as follows: During the cyclical execution of tasks by drones in pairs between groups, the specific method of task relay is as follows: drones in pairs between groups directly share task parameters. When a new drone arrives at the task area, it directly loads the task parameters and starts executing the task, while the corresponding drone that is already executing the task simply returns to base.

5. The multi-UAV cyclic reciprocating mission relay planning method according to claim 1, characterized in that: The autonomous task planning method described in step (5) is as follows: (5a) Separate each UAV in UAV group 1 in sequence according to a fixed height difference; (5b) For any one of the drones, its starting point is denoted as The endpoint of the task area is denoted as ; (5c) The center of the line connecting the start and end points of the UAV is represented as ; (5d) The planned forward flight path of the UAV is: The planned return flight path is as follows: ,in - exist - The direction of the perpendicular line, - exist - The angle is counterclockwise. .

6. The multi-UAV cyclic reciprocating mission relay planning method according to claim 1, characterized in that: The autonomous task planning method described in step (7) is as follows: (7a) Separate each UAV in the two groups of UAVs according to a fixed height difference; (7b) For any one of the drones, its starting point is denoted as The endpoint of the task area is denoted as ; (7c) The center of the line connecting the start and end points of the UAV is represented as ; (7d) The planned forward flight path of the UAV is: The planned return flight path is as follows: ,in - exist - The direction of the perpendicular line, - exist - The angle is clockwise. .

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