Priority Planning for Robots via Fuzzy Logic Controller

Xueliang Cheng, Zhengyi Jiang, Hanlin Niu, Keir Groves, Simon Watson, Nobuto Matsuhira, Barry Lennox, Hajime Asama

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, a novel solution for resolving path planning conflicts for multiple robots by considering the priority levels of the robots is proposed. The proposed algorithm integrated fuzzy logic controller inspired by International Regulations for Preventing Collisions at Sea (COLREGs) traffic rules with a collision area membership function that identifies suitable traffic procedures for each robot to take, into the existing local and global planner and to address the problem of robot navigation in narrow environments. The proposed algorithm was validated using a simulation that used parameters from a Pioneer 3DX robot and a 2D scanned world map. The robots that were used, and the proposed planning algorithm, are generic and could be applied in various real scenarios, such as production facilities, warehouses and product delivery. The results of the simulation experiments demonstrate that this algorithm can effectively solve the problem of ensuring that robots with higher priority pass through narrow areas first.
Original languageEnglish
Title of host publicationIFAC World Congress 2023
Publication statusAccepted/In press - 28 Jun 2023

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