A bio-inspired collision-free 4D trajectory generation method for unmanned aerial vehicles based on tau theory

A bio-inspired collision-free 4D trajectory generation method for Unmanned Aerial Vehicles (UAVs) is presented in this paper. The centralized method can provide an optimal or near-optimal 4D trajectory for every member in a UAV group. The trajectories are generated by the bio-inspired tau-G strategy which is more succinct than the existed methods, and the strategy can adjust speed of UAVs intelligently to meet the arrival time. Collisions between trajectories are detected by the Protected Airspace Zone method, and the collisions unresolved in the trajectory curvature adjustment process will be further planned by two conflict resolution approaches. The whole trajectory generation problem is optimized by Particle Swarm Optimization (PSO) algorithm with a stochastic initial solution. This method has been verified in simulations where multiple quad-rotors cooperatively complete a challenging simultaneous arrival mission.