Reliable Precision Landing for Autonomous Drone-in-a-Box Systems
Precision landing of drones is a well-established concept, but industrial use cases introduce added complexity. Scenarios such as landing on moving platforms, like trucks, boats, or in drone-in-a-box systems, demand high reliability in challenging environments. These applications involve costly hardware and critical payloads, where accuracy is paramount. This work investigates edge cases commonly encountered in industrial precision landing and demonstrates how advanced filtering techniques can mitigate their impact. We explore several sensor fusion strategies and filtering approaches. Through simulation and field testing, we highlight key failure modes and propose practical solutions to achieve robust, repeatable landings in real-world conditions.
Committee: Professor Nitin Sanket (WPI), Professor Greg Lewin (WPI) and Ivan Stamatovski (CTO) Easy Aerial