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Proceedings Paper

Towards high-speed autonomous navigation of unknown environments
Author(s): Charles Richter; Nicholas Roy
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Paper Abstract

In this paper, we summarize recent research enabling high-speed navigation in unknown environments for dynamic robots that perceive the world through onboard sensors. Many existing solutions to this problem guarantee safety by making the conservative assumption that any unknown portion of the map may contain an obstacle, and therefore constrain planned motions to lie entirely within known free space. In this work, we observe that safety constraints may significantly limit performance and that faster navigation is possible if the planner reasons about collision with unobserved obstacles probabilistically. Our overall approach is to use machine learning to approximate the expected costs of collision using the current state of the map and the planned trajectory. Our contribution is to demonstrate fast but safe planning using a learned function to predict future collision probabilities.

Paper Details

Date Published: 22 May 2015
PDF: 9 pages
Proc. SPIE 9467, Micro- and Nanotechnology Sensors, Systems, and Applications VII, 94671P (22 May 2015); doi: 10.1117/12.2178668
Show Author Affiliations
Charles Richter, Massachusetts Institute of Technology (United States)
Nicholas Roy, Massachusetts Institute of Technology (United States)


Published in SPIE Proceedings Vol. 9467:
Micro- and Nanotechnology Sensors, Systems, and Applications VII
Thomas George; Achyut K. Dutta; M. Saif Islam, Editor(s)

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