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Emergency Maneuver Library – Ensuring Safe Navigation in Partially Known Environments

Sankalp Arora, Sanjiban Choudhury, Daniel Althoff and Sebastian Scherer
Conference Paper, Carnegie Mellon University, 2015 IEEE International Conference on Robotics and Automation, May, 2015

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Abstract

Autonomous mobile robots are required to operate in partially known and unstructured environments. It is imperative to guarantee safety of such systems for their successful deployment. Current state of the art does not fully exploit the sensor and dynamic capabilities of a robot. Also, given the non-holonomic systems with non-linear dynamic constraints, it becomes computationally infeasible to find an optimal solution if the full dynamics are to be exploited online. In this paper we present an online algorithm to guarantee the safety of the robot through an emergency maneuver library. The maneuvers in the emergency maneuver library are optimized such that the probability of finding an emergency maneuver that lies in the known obstacle free space is maximized. We prove that the related trajectory set diversity problem is monotonic and sub- modular which enables one to develop an efficient trajectory set generation algorithm with bounded sub-optimality. We generate an off-line computed trajectory set that exploits the full dynamics of the robot and the known obstacle-free region. We test and validate the algorithm on a full-size autonomous helicopter flying up to speeds of 56m/s in partially-known environments. We present results from 4 months of flight testing where the helicopter has been avoiding trees, performing autonomous landing, avoiding mountains while being guaranteed safe.

BibTeX Reference
@conference{Arora-2015-5945,
title = {Emergency Maneuver Library – Ensuring Safe Navigation in Partially Known Environments},
author = {Sankalp Arora and Sanjiban Choudhury and Daniel Althoff and Sebastian Scherer},
booktitle = {2015 IEEE International Conference on Robotics and Automation},
publisher = {IEEE},
school = {Robotics Institute , Carnegie Mellon University},
month = {May},
year = {2015},
address = {Pittsburgh, PA},
}
2017-09-13T10:38:43+00:00