UAV collision avoidance motion planner for aircraft inspection in hangar

This paper presents a theoretical framework for a robust motion planner designed to enable an Unmanned Aerial Vehicle (UAV) to autonomously navigate a hangar environment while avoiding collisions with the aircraft, maintenance equipment, and other potential obstacles. The proposed system, grounded in the potential field method, employs attractive and repulsive forces to guide the UAV toward inspection waypoints and ensures safe separation from obstacles, leveraging conceptual onboard sensing and real-time computation capabilities. This investigation aims to enhance the safety, efficiency, and accuracy of aircraft inspections while minimizing risks to personnel. The planner’s performance is conceptually evaluated through expected metrics, such as obstacle clearance, navigation efficiency, and waypoint precision, as outlined in a theoretical model. This study positions the proposed method as a promising solution for facilitating safe and efficient UAV-based aircraft inspections in confined settings, with a future empirical validation recommended to substantiate its efficacy.

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