Author:
Long Yang,Zuo Zheming,Su Yixin,Li Jie,Zhang Huajun
Abstract
The bacterial foraging optimisation (BFO) algorithm is a commonly adopted bio-inspired optimisation algorithm. However, BFO is not a proper choice in coping with continuous global path planning in the context of unmanned surface vehicles (USVs). In this paper, a grid partition-based BFO algorithm, named AS-BFO, is proposed to address this issue in which the enhancement is contributed by the involvement of the A* algorithm. The chemotaxis operation is redesigned in AS-BFO. Through repeated simulations, the relative optimal parameter combination of the proposed algorithm is obtained and the most influential parameters are identified by sensitivity analysis. The performance of AS-BFO is evaluated via five size grid maps and the results show that AS-BFO has advantages in USV global path planning.
Publisher
Cambridge University Press (CUP)
Subject
Ocean Engineering,Oceanography
Reference34 articles.
1. Global sensitivity analysis of a pig fattening unit model simulating technico-economic performance and environmental impacts
2. Research on path planning for mobile robot based on grid and hybrid of GA/SA;Yang;Advanced Materials Research,2015
3. Autonomous robot path planning in dynamic environment using a new optimization technique inspired by bacterial foraging technique
4. An adaptive bacterial foraging algorithm for fuzzy entropy based image segmentation;Nandita;Expert Systems with Applications,2015
5. Research of no-idle flow shop scheduling based on improved bacteria foraging optimization algorithm;Li;Computer Engineering and Applications,2015
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