Vandermeulen, I., Gross, R. orcid.org/0000-0003-1826-1375 and Kolling, A. (2019) Turn-minimizing multirobot coverage. In: 2019 International Conference on Robotics and Automation (ICRA). 2019 International Conference on Robotics and Automation (ICRA), 20-24 May 2019, Montreal, Canada. IEEE ISBN 9781538681763
Abstract
Document Sections I. Introduction II. Partitioning the Environment III. Combining Ranks Into Paths IV. Results V. Conclusions Authors Figures References Keywords Metrics Abstract: Multirobot coverage is the problem of planning paths for several identical robots such that the combined regions traced out by the robots completely cover their environment. We consider the problem of multirobot coverage with the objective of minimizing the mission time, which depends on the number of turns taken by the robots. To solve this problem, we first partition the environment into ranks which are long thin rectangles the width of the robot's coverage tool. Our novel partitioning heuristic produces a set of ranks which minimizes the number of turns. Next, we solve a variant of the multiple travelling salesperson problem (m-TSP) on the set of ranks to minimize the robots' mission time. The resulting coverage plan is guaranteed to cover the entire environment. We present coverage plans for a robotic vacuum using real maps of 25 indoor environments and compare the solutions to paths planned without the objective of minimizing turns. Turn minimization reduced the number of turns by 6.7% and coverage time by 3.8% on average for teams of 1-5 robots.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 08 Mar 2019 11:52 |
Last Modified: | 12 Aug 2020 00:38 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/ICRA.2019.8794002 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:143336 |