Bat-Inspired Biogeography-Based Optimization Algorithm for Smoothly UAV Track Planning Using Bezier Function

With the extensive applications of Unmanned Aerial Vehicle (UAV), traditional approaches such as Artificial Potential Field and A-star for UAV track planning are usually limited by their low efficiency and easy failure, especially in the three-dimensional complex environments with obstacles. Moreover, most of these works do not make careful considerations on the fine-grain smooth of track requird heavily by the realistic flight of UAV. Therefore, in this paper, we propose an improved Biogeography-Based Optimization (BBO) algorithm with Bats algorithm (BA), named BIBBO for UAV track planning, which allows a new generating method with continuous Bezier curve by using adaptive-step sampling of control points to smooth original track. The simulation results verify the effectiveness and robustness of the proposed algorithm with shorter and smoother 3-D tracks, compared with typical BBO and BA algorithms.