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Landing Zone Determination For Autonomous Rotorcraft In Surveillance Applications, Timothy Mclain, Gary J. Ellingson, Justin Mackay

Faculty Publications

This paper presents an approach for finding possible landing sites for a rotorcraft from an inertially referenced point-cloud model of the environment. To identify potential landing sites that are suitably flat and level, a grid-based random sample consensus algorithm separates the terrain map into discrete areas for plane-fitting analysis. Landing sites are selected that satisfy constraints on flatness and levelness while optimizing the surveillance target’s visibility. Flight test results are presented from a small multirotor aircraft flying over a scale-model cityscape. Results from real-time landing-site experiments are presented and discussed.