Autonomous Emergency Landing of a Helicopter: Motion Planning with Hard Time-Constraints

摘要

Engine malfunctions during helicopter flight poses a large risk to pilot and crew. Without a quick and coordinated reaction,rnsuch situations lead to a complete loss of control. An autonomous landing system is capable of reacting quicklyrnto regain control, however current emergency landing methods focus only on the offline generation of dynamicallyrnfeasible trajectories while ignoring the more severe constraints faced while autonomously landing a real helicopterrnduring an unplanned engine failure. We address the problem of autonomously landing a helicopter while consideringrna realistic context: hard time-constraints, challenging terrain, sensor limitations and availability of pilot contextualrnknowledge. We designed a planning system that deals with all these factors by being able to compute alternate routesrn(AR) in a rapid fashion. This paper presents an algorithm, RRT*-AR, building upon the optimal sampling-based algorithmrnRRT* to generate AR in realtime while maintaining optimality guarantees and examines its performance forrnsimulated failures occurring in mountainous terrain. After over 4500 trials, RRT*-AR outperformed RRT* by providingrnthe human 280% more options 67% faster on average. As a result, it provides a much wider safety margin forrnunaccounted disturbances, and a more secure environment for a pilot.