GeoDesic-VPC: Spatial partitioning for multi-robot coverage problem

dc.contributor.authorNair, V.G.
dc.contributor.authorGuruprasad, K.R.
dc.date.accessioned2026-02-05T09:29:10Z
dc.date.issued2020
dc.description.abstractIn 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.
dc.identifier.citationInternational Journal of Robotics and Automation, 2020, 35, 3, pp. 189-198
dc.identifier.issn8268185
dc.identifier.urihttps://doi.org/10.2316/J.2020.206-0303
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/24170
dc.publisherActa Press journals@actapress.com
dc.subjectAgricultural robots
dc.subjectCells
dc.subjectGeodesy
dc.subjectIndustrial robots
dc.subjectMATLAB
dc.subjectMultipurpose robots
dc.subjectTopology
dc.subjectCo-operating robots
dc.subjectComplete coverages
dc.subjectCoverage algorithms
dc.subjectCoverage problem
dc.subjectGeodesic distances
dc.subjectSimulation in matlabs
dc.subjectSpatial partitioning
dc.subjectVoronoi partition
dc.subjectCytology
dc.titleGeoDesic-VPC: Spatial partitioning for multi-robot coverage problem

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