Towards high-speed autonomous navigation of unknown environments

Charles Richter; Nicholas Roy

doi:10.1117/12.2178668

22 May 2015 Towards high-speed autonomous navigation of unknown environments

Charles Richter, Nicholas Roy

Proceedings Volume 9467, Micro- and Nanotechnology Sensors, Systems, and Applications VII; 94671P (2015) https://doi.org/10.1117/12.2178668
Event: SPIE Defense + Security, 2015, Baltimore, MD, United States

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.

Citation Download Citation

Charles Richter and Nicholas Roy "Towards high-speed autonomous navigation of unknown environments", Proc. SPIE 9467, Micro- and Nanotechnology Sensors, Systems, and Applications VII, 94671P (22 May 2015); https://doi.org/10.1117/12.2178668

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