Self-Aware Helicopters: Full-Scale Automated Landing and Obstacle Avoidance in Unmapped Environments - Robotics Institute Carnegie Mellon University

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

Lyle J. Chamberlain, Sebastian Scherer, and Sanjiv Singh
Conference Paper, Proceedings of AHS 67th Annual Forum, March, 2011

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},
}