Collaborative Mapping and Search for Autonomous Helicopters

This paper describes recent results from a partnership between the Sikorsky Aircraft Corporation and the Georgia Institute of Technology to develop, improve, and flight test a multi-aircraft collaborative architecture, focused on decentralized autonomous decision-making. The architecture includes a finite-state machine, Voronoi mapping strategy, and real-time information sharing system designed to solve a challenge problem. The architecture was implemented on a pair of Yamaha RMax helicopters outfitted with modular avionics, as well as an associated set of simulation tools. Simulation results for single- and multiple-aircraft scenarios are presented, along with a quadratic relationship between mapping speed and task completion time. Further work suggested includes validation of simulation results in flight test with two real aircraft, as well as further exploration between search problem parameters and theoretical optimal performance.