Coverage Path Planning With Budget Constraints for Multiple Unmanned Ground Vehicles

Article

Tran, Vu Phi, Perera, Asanka, Garrat, Matthew A., Kasmarik, Kathryn and Anavatti, Sreenatha G.. 2023. "Coverage Path Planning With Budget Constraints for Multiple Unmanned Ground Vehicles." IEEE Transactions on Intelligent Transportation Systems. 24 (11), pp. 12506-12522. https://doi.org/10.1109/TITS.2023.3285624
Article Title

Coverage Path Planning With Budget Constraints for Multiple Unmanned Ground Vehicles

ERA Journal ID3746
Article CategoryArticle
AuthorsTran, Vu Phi, Perera, Asanka, Garrat, Matthew A., Kasmarik, Kathryn and Anavatti, Sreenatha G.
Journal TitleIEEE Transactions on Intelligent Transportation Systems
Journal Citation24 (11), pp. 12506-12522
Number of Pages17
Year2023
PublisherIEEE (Institute of Electrical and Electronics Engineers)
Place of PublicationUnited States
ISSN1524-9050
1558-0016
Digital Object Identifier (DOI)https://doi.org/10.1109/TITS.2023.3285624
Web Address (URL)https://ieeexplore.ieee.org/abstract/document/10168054
Abstract

This paper proposes an innovative approach to coverage path planning and obstacle avoidance for multiple Unmanned Ground Vehicles (UGVs) in a changing environment, taking into account constraints on the time, path length, number of UGVs and obstacles. Our approach leverages deformable virtual leader-follower formations to enable UGVs to adapt their formation based on both planned and real-time sensor data. A hierarchical block algorithm is employed to identify areas in the environment where UGV formations can spread out to meet time and budget constraints. Additionally, we introduce a novel control scheme that allows each UGV to generate a local steering force to dodge any static and mobile obstacles based on the closest safe angle. Results from simulations and real UGV experiments demonstrate that our approach achieves a higher coverage percentage than rule-based and reactive swarming approaches without planning. Our approach offers a promising solution for efficient coverage path planning and obstacle avoidance in complex environments with multiple UGVs.

KeywordsCoverage path planning; spanning tree coverage; optimisation technique; formation control; obstacle avoidance; autonomous vehicles
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 20204007. Control engineering, mechatronics and robotics
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Byline AffiliationsUniversity of New South Wales
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