Hybrid Boustrophedon and Partition Tree Group Algorithm for Coverage Path Planning Problem with Energy Constraints

Giang, Tran Thi Cam; Bình, Huỳnh Thị Thanh

doi:10.1007/978-981-19-8234-7_49

Cited by 1 publication

(1 citation statement)

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“…In the context of a real-world problem, a rising key point in CCPP [26][27][28] requires double-pass complete coverage (DPCC). For example, in a restaurant, most parts of a typical dining floor only require standard cleaning, while some areas might require more attention [29].…”

Section: Introductionmentioning

confidence: 99%

Inter-Reconfigurable Robot Path Planner for Double-Pass Complete Coverage Problem

Sang,

Yang,

et al. 2024

Mathematics

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Recent advancements in autonomous mobile robots have led to significant progress in area coverage tasks. However, challenges persist in optimizing the efficiency and computational complexity of complete coverage path planner (CCPP) algorithms for multi-robot systems, particularly in scenarios requiring revisiting or a double pass in specific locations, such as cleaning robots addressing spilled consumables. This paper presents an innovative approach to tackling the double-pass complete coverage problem using an autonomous inter-reconfigurable robot path planner. Our solution leverages a modified Glasius bio-inspired neural network (GBNN) to facilitate double-pass coverage through inter-reconfiguration between two robots. We compare our proposed algorithm with traditional multi-robot path planning in a centralized system, demonstrating a reduction in algorithm iterations and computation time. Our experimental results underscore the efficacy of the proposed solution in enhancing the efficiency of area coverage tasks. Furthermore, we discuss the implementation details and limitations of our study, providing insights for future research directions in autonomous robotics.

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