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Carnegie Mellon Robotics Institute

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Abstract

In this paper we present a perception and autonomy package that for the first time allows a full-scale unmanned helicopter (the Boeing Unmanned Little Bird) to automatically fly through unmapped, obstacle-laden terrain, find a landing zone, and perform a safe landing near a casualty, all with no human control or input. The system also demonstrates the ability to avoid obstacles while in low-altitude flight. The perception system consists of a 3D LADAR mapping unit with sufficient range, accuracy, and bandwidth to bring autonomous flight into the realm of full-scale aircraft. Efficient evaluation of this data and fast planning algorithms provide the aircraft with safe flight trajectories in real-time. We show the results of several fully autonomous landing and obstacle avoidance missions.

Keywords

helicopter, UAV, UAS, optionally-manned, perception, planning, automated landing, obstacle avoidance

Notes

Associated Center(s) / Consortia: Field Robotics Center

Text Reference

Lyle J. Chamberlain, Sebastian Scherer, and Sanjiv Singh, "Self-Aware Helicopters: Full-Scale Automated Landing and Obstacle Avoidance in Unmapped Environments," AHS Forum 67, March, 2011.

BibTeX Reference

@inproceedings{Chamberlain_2011_6870,
   author = "Lyle J. Chamberlain and Sebastian Scherer and Sanjiv Singh",
   editor = "Matt Whaley",
   title = "Self-Aware Helicopters: Full-Scale Automated Landing and Obstacle Avoidance in Unmapped Environments",
   booktitle = "AHS Forum 67",
   month = "March",
   year = "2011",
}

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