Optimal Control-Based UAV Path Planning with Dynamically-Constrained TSP with Neighborhoods

Abstract: This paper addresses path planning of an unmanned aerial vehicle (UAV) with remote sensing capabilities (or wireless communication capabilities). The goal of the path planning is to find a minimum-flight-time closed tour of the UAV visiting all executable areas of given remote sensing and communication tasks; in order to incorporate the nonlinear vehicle dynamics, this problem is regarded as a dynamically-constrained traveling salesman problem with neighborhoods. To obtain a close-to-optimal solution for the path planning in a tractable manner, a sampling-based roadmap algorithm that embeds an optimal control-based path generation process is proposed. The algorithm improves the computational efficiency by reducing numerical computations required for optimizing inefficient local paths, and by extracting additional information from a roadmap of a fixed number of samples. Comparative numerical simulations validate the efficiency of the presented algorithm in reducing computation time and improving the solution quality compared to previous roadmap-based planning methods.