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