Towards high-speed autonomous navigation of unknown environments
Author(s)Richter, Charles Andrew; Roy, Nicholas
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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.
DepartmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory; Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Proceedings of SPIE--the Society of Photo-Optical Instrumentation Engineers, 2015
Richter, Charles, and Nicholas Roy. “Towards High-Speed Autonomous Navigation of Unknown Environments.” Ed. Thomas George, Achyut K. Dutta, and M. Saif Islam. N.p., 2015. 94671P. © 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)
Final published version