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Self-Aware Helicopters: Full-Scale Automated Landing and Obstacle Avoidance in Unmapped Environments

Lyle J. Chamberlain, Sebastian Scherer and Sanjiv Singh
Conference Paper, Carnegie Mellon University, AHS Forum 67, March, 2011

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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.

BibTeX Reference
@conference{Chamberlain-2011-7232,
title = {Self-Aware Helicopters: Full-Scale Automated Landing and Obstacle Avoidance in Unmapped Environments},
author = {Lyle J. Chamberlain and Sebastian Scherer and Sanjiv Singh},
booktitle = {AHS Forum 67},
keyword = {helicopter, UAV, UAS, optionally-manned, perception, planning, automated landing, obstacle avoidance},
school = {Robotics Institute , Carnegie Mellon University},
month = {March},
year = {2011},
address = {Pittsburgh, PA},
}
2017-09-13T10:40:25+00:00