A Compound Online Local Path Planning and Situation-Aware Dynamic Obstacle Avoidance System for UAV

In this paper, a composite system of Unmanned Aerial Vehicles (UAVs) including path planning and dynamic obstacle avoidance is proposed. The system can deal with complex low-altitude environments, achieve autonomous flight path planning, and dynamically avoid obstacles. When obstacles were detected at a relatively far distance, a local collision-free flight path near the affected route is planned online using a plant growth algorithm proposed without changing the current flight state of the UAV. When a moving obstacle suddenly enters the UAV’s flight path at a closer distance, a situation-aware dynamic obstacle avoidance algorithm based on artificial potential fields is preferentially activated to respond at the fastest speed. Meanwhile, the local planner is also used to plan a new local collision-free path again, ensuring the UAV’s flight safety to the greatest extent with minimal cost. The effectiveness of the intelligent UAV composite path planning and dynamic obstacle avoidance system is demonstrated in simulation environment and real-world experiments.