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Modified PSO algorithms with Request and Reset for leak source localization using multiple robots
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DOI：10.1016/j.neucom.2018.02.078.png)
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摘要
En 中文
Leak source localization is a very important topic that has receivedmuch research attention in recent years. The Request and Reset strategy is introduced here into the GC-PSO and D-PSO algorithms to improve the localization strategy. In the Request and Reset process, some of the low fitness particles are requested to be removed from their current group with their positions reset to assist the globally best particle, with those particles then combined into an optimal group to enhance the search around the globally best particle. Other two existing algorithms are improved by modifying the learning factor and inertia weight as comparison. Serval experiments are conducted by simulation to investigate the feature of the proposed algorithms, in which the impact of environmental size and population size as well as error adaptability are considered. Experimental results demonstrated the feasibility and advantage of the proposed approaches. MGC-PSO has the superior performance to the other methods in aspect of success rate and iteration time. (c) 2018 Elsevier B.V. All rights reserved.
Keyword:
Odor source
Multi-robot
Particle swarm optimization
Request and Reset
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期刊
IF:
6.5
论文数:
2.5W
被引数:
6.5W
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A PSO-based multi-robot cooperation method for target searching in unknown environments.png)
NEUROCOMPUTING
NEUROCOMPUTINGIF6.5
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