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

摘要

This paper addresses path planning of an unmanned aerial vehicle (UAV) withremote sensing capabilities (or wireless communication capabilities). The goalof the path planning is to find a minimum-flight-time closed tour of the UAVvisiting all executable areas of given remote sensing and communication tasks;in order to incorporate the nonlinear vehicle dynamics, this problem isregarded as a dynamically-constrained traveling salesman problem withneighborhoods. To obtain a close-to-optimal solution for the path planning in atractable manner, a sampling-based roadmap algorithm that embeds an optimalcontrol-based path generation process is proposed. The algorithm improves thecomputational efficiency by reducing numerical computations required foroptimizing inefficient local paths, and by extracting additional informationfrom a roadmap of a fixed number of samples. Comparative numerical simulationsvalidate the efficiency of the presented algorithm in reducing computation timeand improving the solution quality compared to previous roadmap-based planningmethods.