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DC Field | Value | Language |
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dc.contributor.author | Nair V.G. | |
dc.contributor.author | Guruprasad K.R. | |
dc.date.accessioned | 2021-05-05T10:27:11Z | - |
dc.date.available | 2021-05-05T10:27:11Z | - |
dc.date.issued | 2020 | |
dc.identifier.citation | International Journal of Robotics and Automation Vol. 35 , 3 , p. 189 - 198 | en_US |
dc.identifier.uri | https://doi.org/10.2316/J.2020.206-0303 | |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/15490 | - |
dc.description.abstract | In this paper, we address a problem of area coverage using multiple cooperating robots using a “partition and cover" approach, where the area of interest is decomposed into as many cells as the robots, and each robot is assigned the task of covering a cell. While the most partitioning approaches used in the literature in the context of a robotic coverage problem may result in topologically disconnected cells in the presence of obstacles leading to incomplete coverage, we propose to use geodesic distance-based generalization of the Voronoi partition, ensuring that each cell that is allotted for a robot for coverage is a topologically connected region, and hence, achieving a complete coverage. The proposed multi-robot coverage strategy is demonstrated with simulation in MATLAB and V-rep simulator, using two single-robot coverage algorithms reported in the literature, namely boustrophedon decomposition-based coverage and spanning tree-based coverage algorithms. © 2020 SAE International. All rights reserved. | en_US |
dc.title | GeoDesic-VPC: Spatial partitioning for multi-robot coverage problem | en_US |
dc.type | Article | en_US |
Appears in Collections: | 1. Journal Articles |
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