Optimal Path Planning of a Target Following Fixed Wing UAV Using Sequential Decision Processes
United States Air Force Academy Air Force Academy United States
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In this work, we consider the optimal path of a fixed-wing unmanned aerial vehicle UAV tracking a mobile surface target. One of the limitations of fixed-wing UAVs in tracking mobile targets is the lack of hovering capability when the target moves much slower than the minimum UAV speed, requiring the UAV maintain an orbit about the target. In this paper, we propose a method to find the optimal policy for fixed-wing UAVs to minimize the location uncertainty of a mobile target. using a grid-based Markov Decisive Process MDP, we process a policy iteration algorithm offline to find the optimal UAV path in a discretized state space. Based on the offline optimal policy, we generate a finer grid MDP for the region of interest to efficiently process an online policy iteration to find in real-time the optimal trajectory for a UAV. We validate the proposed algorithm using computer simulations. Comparing the simulation results with other methods, we show that the proposed method has up to 13 decrease in error uncertainty than ones resulted using conventional methods.
- Pilotless Aircraft
- Target Direction, Range and Position Finding