This paper introduces a time-optimal swarm trajectory planner for cooperative uncrewed aerial vehicle (UAV) systems, designed to generate collision-free trajectories for flocking control in cluttered environments. To achieve this goal, model predictive contour control is utilised to generate time-optimal trajectories for each UAV. By demonstrating the differential flatness dynamic equations, the system state constraints are simplified, the algorithm’s complexity is reduced, and the overall stability is improved. Additionally, flocking control is achieved among multiple UAVs by applying virtual repulsive and attractive forces. Furthermore, an event-triggered trajectory deconflict strategy for trajectory replanning is considered to resolve multiple trajectory conflicts. Comparative experiments with baseline methods have confirmed that the proposed planner can generate faster and safer trajectories than conventional methods.
T-STAR: Time-Optimal Swarm Trajectory Planning for Quadrotor Unmanned Aerial Vehicles
IEEE Transactions on Intelligent Transportation Systems ; 26 , 8 ; 12532-12547
2025-08-01
2290180 byte
Article (Journal)
Electronic Resource
English
Trajectory planning with mid-air collision avoidance for quadrotor unmanned aerial vehicles
SAGE Publications | 2022
|Event-Triggered Adaptive Trajectory Tracking Control for Quadrotor Unmanned Aerial Vehicles
Springer Verlag | 2023
|Quadrotor unmanned aerial vehicle trajectory planning method based on space-time joint optimization
European Patent Office | 2020
|