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Proceedings Paper

Thorough exploration of complex environments with a space-based potential field
Author(s): Alina Kenealy; Nicholas Primiano; Alex Keyes; Damian M. Lyons
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Paper Abstract

Robotic exploration, for the purposes of search and rescue or explosive device detection, can be improved by using a team of multiple robots. Potential field navigation methods offer natural and efficient distributed exploration algorithms in which team members are mutually repelled to spread out and cover the area efficiently. However, they also suffer from field minima issues. Liu and Lyons proposed a Space-Based Potential Field (SBPF) algorithm that disperses robots efficiently and also ensures they are driven in a distributed fashion to cover complex geometry. In this paper, the approach is modified to handle two problems with the original SBPF method: fast exploration of enclosed spaces, and fast navigation of convex obstacles. Firstly, a “gate-sensing” function was implemented. The function draws the robot to narrow openings, such as doors or corridors that it might otherwise pass by, to ensure every room can be explored. Secondly, an improved obstacle field conveyor belt function was developed which allows the robot to avoid walls and barriers while using their surface as a motion guide to avoid being trapped. Simulation results, where the modified SPBF program controls the MobileSim Pioneer 3-AT simulator program, are presented for a selection of maps that capture difficult to explore geometries. Physical robot results are also presented, where a team of Pioneer 3-AT robots is controlled by the modified SBPF program. Data collected prior to the improvements, new simulation results, and robot experiments are presented as evidence of performance improvements.

Paper Details

Date Published: 8 February 2015
PDF: 8 pages
Proc. SPIE 9406, Intelligent Robots and Computer Vision XXXII: Algorithms and Techniques, 940605 (8 February 2015); doi: 10.1117/12.2080153
Show Author Affiliations
Alina Kenealy, Fordham Univ. (United States)
Nicholas Primiano, Fordham Univ. (United States)
Alex Keyes, Fordham Univ. (United States)
Damian M. Lyons, Fordham Univ. (United States)

Published in SPIE Proceedings Vol. 9406:
Intelligent Robots and Computer Vision XXXII: Algorithms and Techniques
Juha Röning; David Casasent, Editor(s)

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