An Online Path-Planning Strategy for an Unmanned Aerial Vehicle Crossing Mobile Narrow Passages

Aerial inspection missions over long distances are guided by planning paths with minimum energy consumption, which generally leads to routes with shorter distances. However, these conditions cannot always be met due to the environment’s geometric constraints, especially in the most unexpected (unsafe, dangerous, and risky) scenarios. The aim of this work is to improve the efficiency, stability, and security of unmanned aerial vehicles (UAVs) during inspection missions in unstructured and unpredictable environments. Traditional path-planning techniques that prioritize minimum energy consumption often lead to routes with shorter distances, but these can be hindered by environmental geometric constraints and risky scenarios. To address this challenge, a new path-planning algorithm is proposed that ensures safe passage through challenging moving locations while respecting the physical limitations of the robot and the shape of narrow passages. The algorithm is combined with a controller design for obstacle avoidance. Experimental results with different motion restrictions are presented, demonstrating the effectiveness of the proposed approach.