Planning Alternate Routes using a Single Sampling Based Planner


2012_planningalternateroutes

Engine malfunctions during helicopter flight poses a large risk to pilot and crew. Without a quick and coordinated reaction, such situations lead to a complete loss of control. An autonomous landing system could react quicker to regain control, however current emergency landing methods only generate dynamically feasible trajectories without considering obstacles. We address the problem of autonomously landing a helicopter while considering a realistic context: multiple potential landing zones, geographical terrain, sensor limitations and pilot contextual knowledge. We designed a planning system to generate alternate routes (AR) that respect these factors till touchdown exploiting the human-in-loop to make a choice. This paper presents an algorithm, RRT*-AR, building upon the optimal sampling-based algorithm RRT* to generate AR in realtime and examines its performance for simulated failures occurring in mountainous terrain, while maintaining optimality guarantees. After over 4500 trials, RRT*-AR outperformed RRT* by providing the human 280% more options 67% faster on average. As a result, it provides a much wider safety margin for unaccounted disturbances, and a more secure environment for a pilot. Using AR, the focus can now shift on delivering safety guarantees and handling uncertainties in these situations.


Related Publications

RRT*-AR: Sampling-Based Alternate Routes Planning with Applications to Autonomous Emergency Landing of a Helicopter
Sanjiban Choudhury, Sebastian Scherer and Sanjiv Singh
International Conference on Robotics and Automation May, 2013
pdf
Autonomous Emergency Landing of a Helicopter: Motion Planning with Hard Time-Constraints
Sanjiban Choudhury, Sebastian Scherer and Sanjiv Singh
AHS Forum 69 May, 2013
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Realtime Alternate Routes Planning: The RRT*-AR Algorithm
Sanjiban Choudhury, Sebastian Scherer and Sanjiv Singh
CMU-RI-TR-12-27 December, 2012
pdf