Self-Aware Helicopters: Full-Scale Automated Landing and Obstacle Avoidance in Unmapped Environments
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
@conference{Chamberlain-2011-7232,author = {Lyle J. Chamberlain and Sebastian Scherer and Sanjiv Singh},
title = {Self-Aware Helicopters: Full-Scale Automated Landing and Obstacle Avoidance in Unmapped Environments},
booktitle = {Proceedings of AHS 67th Annual Forum},
year = {2011},
month = {March},
editor = {Matt Whaley},
keywords = {helicopter, UAV, UAS, optionally-manned, perception, planning, automated landing, obstacle avoidance},
}