Multi-UAV Trajectory Planning during Cooperative Tracking Based on a Fusion Algorithm Integrating MPC and Standoff
Abstract
:1. Introduction
2. UAV Model and Environment Model
2.1. UAV Motion Model
2.2. UAV Collision Avoidance Model
2.3. Moving Target Model
2.4. Target Observation Coverage Modelling
3. Designing a Multi-UAV Cooperative Tracking System Based on the Fusion Algorithm
3.1. System Design
3.2. Multi-UAV Cooperative Trajectory Planning Based on the Fusion Algorithm
3.2.1. Multi-UAV Formation Control Based on the Standoff Algorithm
3.2.2. Track Planning UAVs Take during Cooperative Tracking of the Moving Target Based on the Fusion Algorithm
Algorithm 1: Fusion Algorithm Based on MPC and Standoff. |
1. Initialize map environment information |
2. Initialize fusion algorithm information |
3. Initialize multi-UAV movement information |
4. For step = 1, 2, …, N: |
5. Obtain the initial state of UAVs in environments , and |
6. For k = 1, …, J: |
7. if multi-UAV formations encounter no surprises: |
8. Comprehensive consideration of UAV trajectory planning constraints: ,, |
9. Input prediction of velocity and angular velocity control in the time domain , |
10. “red” UAV in the environment executing the previous control input of the drone and correcting speed variables based on the Standoff algorithm, and obtains the next state |
11. “yellow” UAV in the environment executing the previous control input of the drone and correcting speed variables based on the Standoff algorithm, and obtains the next state |
12. “green” UAV in the environment executing the previous control input of the drone and correcting speed variables based on the Standoff algorithm, and obtains the next state |
13. Store the above track planning information in the model predictive control module |
14. if multi-UAV formations encounters an unexpected obstacle: |
15. UAV reconfiguration planning based on Computational (12) |
16. Update drone location information based on minimum generation value |
17. end if |
18. else: break |
19. end if |
20. end for |
21. step = step + 1 |
22. end for |
3.3. Application Steps of Multi-UAV Cooperative Tracking of the Moving Target Based on the Fusion Algorithm
4. Simulation Verification
5. Discussion
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Serial Number | Parameters Name | Parameter Value |
---|---|---|
1 | UAV1 starting position | (200 m, 5 m, 115 m) |
2 | UAV2 starting position | (160 m, 5 m, 75 m) |
3 | UAV3 starting position | (240 m, 5 m, 75 m) |
4 | Target starting position | (200 m, 5 m, 95 m) |
5 | UAV initial speed | 25 m/s |
6 | UAV speed range | [20 m/s, 40 m/s] |
7 | Maximum yaw angle of UAV | π/4 rad |
8 | Maximum pitch angle of UAV | π/4 rad |
9 | Minimum turning radius for UAV | 10 m |
10 | Number of UAVs | 3 |
11 | Maximum speed constraint for UAVs | 40 m/s |
12 | Minimum speed constraint for UAVs | 10 m/s |
13 | Maximum angular velocity constraint for UAVs | 0.25 rad/s |
Serial Number | Coordinate Position | Radius Size of Obstacle |
---|---|---|
1 | (100 m, 270 m, 250 m) | 50 m |
2 | (200 m, 300 m, 250 m) | 50 m |
UAV Category | Usage | Effective Number of Detected Steps (Scene 1-Total: 100) | Effective Number of Detected Steps (Scene 2-Total: 100) | Effective Number of Detected Steps (Scene 3-Total: 100) |
---|---|---|---|---|
UAV1 | Fusion algorithm | 100 | 100 | 100 |
Model predictive control algorithm | 100 | 100 | 100 | |
UAV2 | Fusion algorithm | 89 | 88 | 92 |
Model predictive control algorithm | 86 | 84 | 88 | |
UAV3 | Fusion algorithm | 97 | 95 | 95 |
Model predictive control algorithm | 82 | 80 | 81 |
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Li, B.; Song, C.; Bai, S.; Huang, J.; Ma, R.; Wan, K.; Neretin, E. Multi-UAV Trajectory Planning during Cooperative Tracking Based on a Fusion Algorithm Integrating MPC and Standoff. Drones 2023, 7, 196. https://doi.org/10.3390/drones7030196
Li B, Song C, Bai S, Huang J, Ma R, Wan K, Neretin E. Multi-UAV Trajectory Planning during Cooperative Tracking Based on a Fusion Algorithm Integrating MPC and Standoff. Drones. 2023; 7(3):196. https://doi.org/10.3390/drones7030196
Chicago/Turabian StyleLi, Bo, Chao Song, Shuangxia Bai, Jingyi Huang, Rui Ma, Kaifang Wan, and Evgeny Neretin. 2023. "Multi-UAV Trajectory Planning during Cooperative Tracking Based on a Fusion Algorithm Integrating MPC and Standoff" Drones 7, no. 3: 196. https://doi.org/10.3390/drones7030196