FAST

FAST We propose Frontier Allocation Synchronized by Token passing (FAST), a distributed algorithm for online terrain coverage using multiple mobile robots, ensuring mutually exclusive selection of frontier cells. Many existing approaches cover the terrain in an irregular fashion, without considering the usability of the already covered region. For instance, in the task of floor cleaning in an office building, these approaches do not guarantee the cleanliness of large unbroken areas until a majority of the task is complete. FAST on the other hand, incrementally traverses the terrain generating structured trajectories for each robot. Following a structured trajectory for coverage path planning is proven to be a very powerful approach in literature. This renders large portions of the terrain usable even before the completion of the coverage task. The novel map representation techniques used in FAST render it scalable to large terrains, without affecting the volume of communication among robots. Moreover, the distributed nature of FAST allows incorporation of fault-tolerance mechanisms. Empirical investigations on maps of varied complexities and sizes both in simulation and on an experimental test-bed demonstrate that the proposed algorithm performs better than some of the benchmark approaches in terms of coverage completion time and less redundant coverage. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Intelligent & Robotic Systems Springer Journals
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Publisher
Springer Netherlands
Copyright
Copyright © 2016 by Springer Science+Business Media Dordrecht
Subject
Engineering; Control, Robotics, Mechatronics; Electrical Engineering; Artificial Intelligence (incl. Robotics); Mechanical Engineering
ISSN
0921-0296
eISSN
1573-0409
D.O.I.
10.1007/s10846-016-0416-2
Publisher site
See Article on Publisher Site

Abstract

We propose Frontier Allocation Synchronized by Token passing (FAST), a distributed algorithm for online terrain coverage using multiple mobile robots, ensuring mutually exclusive selection of frontier cells. Many existing approaches cover the terrain in an irregular fashion, without considering the usability of the already covered region. For instance, in the task of floor cleaning in an office building, these approaches do not guarantee the cleanliness of large unbroken areas until a majority of the task is complete. FAST on the other hand, incrementally traverses the terrain generating structured trajectories for each robot. Following a structured trajectory for coverage path planning is proven to be a very powerful approach in literature. This renders large portions of the terrain usable even before the completion of the coverage task. The novel map representation techniques used in FAST render it scalable to large terrains, without affecting the volume of communication among robots. Moreover, the distributed nature of FAST allows incorporation of fault-tolerance mechanisms. Empirical investigations on maps of varied complexities and sizes both in simulation and on an experimental test-bed demonstrate that the proposed algorithm performs better than some of the benchmark approaches in terms of coverage completion time and less redundant coverage.

Journal

Journal of Intelligent & Robotic SystemsSpringer Journals

Published: Sep 17, 2016

References

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