Motion Planning for a Fixed-Wing UAV in Urban Environments

This paper presents motion planning for fixed-wing unmanned aerial vehicles (UAVs) using Rapidly-exploring Random Trees (RRTs), given a starting location and destination in the presence of static obstacles. Generating a near optimal path in an obstacle rich environment within a very short time window was well addressed by the RRT approach and was tightly established for a 2-D domain. Adopting this solution, it is investigated for urban environments. In this paper, taking real time situations for a fixed-wing UAV into account, a practical solution for its path planning in an urban environment is proposed. The turn radius and climb rate constraints of a UAV are considered in this regard. A combination of pursuit guidance law and line of sight guidance law is used to track the UAV in 3-D domain. Simulations studies are presented to demonstrate the performance of the proposed algorithm along with the guidance law.