A Novel Collision Avoidance Logic for Unmanned Aerial Vehicles Using Real-Time Trajectory Planning

An effective collision avoidance logic should prevent collision without excessive alerting. This requirement would be even more stringent for an automatic collision avoidance logic, which is probably required by Unmanned Aerial Vehicles to mitigate the impact of delayed or lost link issues. In order to improve the safety performance and reduce the frequency of false alarms, this thesis proposes a novel collision avoidance logic based on the three-layer architecture and a real-time trajectory planning method. The aim of this thesis is to develop a real-time trajectory planning algorithm for the proposed collision avoidance logic and to determine the integrated logic’s feasibility, merits and limitations for practical applications. To develop the trajectory planning algorithm, an optimal control problem is formulated and an inverse-dynamic direct method along with a two stage, derivative-free pattern search method is used as the solution approach. The developed algorithm is able to take into account the flyability of three dimensional manoeuvres, the robustness to the intruder state uncertainty and the field-of-regard restriction of surveillance sensors. The testing results show that the standalone executable of the algorithm is able to provide a flyable avoidance trajectory with a maximum computation time less than 0.5 seconds. To evaluate the performance of the proposed logic, an evaluation framework for Monte Carlo simulations and a baseline approach for comparison are constructed. Based on five Monte Carlo simulation experiments, it is found that the proposed logic should be feasible as 1) it is able to achieve an update rate of 2Hz, 2) its safety performance is comparable with a reference requirement from another initial feasibility study, and 3) despite a 0.5 seconds computation latency, it outperforms the baseline approach in terms of safety performance and robustness to sensor and feedback error.