UAV Bezier Curve Maneuver Planning Using Genetic Algorithm

摘要

This paper presents Unmanned Aerial Vehicle (UAV) path planning using a Genetic Algorithm (GA) in a static environment at constant altitude. The cubic Bezier curve is used as path reference. The GA will find a proper control points position such that a minimum-length feasible path will be achieved. An optimization objective is a minimum path length with constraints. There are two constraints that must be satisfied, a free collision and a minimum turning radius. Fuzzy rules are applied in fitness function to satisfy these constraints. It needs to detect collisions after the curvature is satisfied. Results show that the proposed algorithm succeeded to find the goal path.