UAV Trajectory Design for Obstacle Avoidance Based on Cell-Varying JPS in Smart Cities

With their high mobility and flexible configuration, unmanned aerial vehicles (UAVs), play important roles in the development of intelligent transportation in smart cities. Due to the complex three-dimensional (3D) flight environments, obtaining an optimal collision-safe flight path is a challenge with the limited computational capability of UAVs. In this paper, we propose a UAV trajectory design method for obstacle avoidance, which could be used in UAV intelligence navigation. First, we propose a cell-varying JPS method in hexagonal cells to integrate the aerodynamic constraints into trajectory designing in a two-dimensional (2D) plane. Second, we develop the cell-varying JPS with modified pruning and jumping rules and extend this modified version to trajectory-planning in the three-dimensional (3D) environments. Our simulation results demonstrate that the proposed cell-varying JPS achieves the reduction up to 4.2% in path length compared with the existing method while guaranteeing a safe flight.