Optimized UAVs' Collision-free 2D Path Planning Based on Quintic Pythagorean Hodograph Curves
Aya Abdelhady Deaf, Ahmed Hosny Eid, Kamel Elserafi · 2024
This paper proposes optimized 2D paths and trajectories planning of UAVs in a static simple environment with known obstacles and borders. The paths are produced using quintic Pythagorean Hodograph curves (PH curves) to obtain feasible flyable and smooth paths for UAVs. The produced paths satisfy UAV's kinematic and dynamic constraints like curvature bounds and minimum bending energy. The paths also meet the safety collision-free with all obstacles, borders in the environment, and inter-collision between UAVs with minimum length joining the start and the goal points for each UAV. A genetic algorithm optimization technique (GA) is proposed to select the optimal curve parameters for obtaining the optimized paths and trajectories for each UAV satisfying all mentioned conditions and constraints.