Self-learning Hierarchical Fuzzy Logic Controller in Multi-Robot Systems

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In this paper, hierarchical fuzzy logic control systems and genetic algorithms are amalgamated to provide an integrated knowledge base for intelligent control of mobile robots for collision-avoidance in a common workspace. genetic algorithms are employed as an adaptive method for learning the fuzzy rules of the control system. A two robot systems is considered in the plane, each is made up of two layers to reduce the number of control laws to be learnt by the genetic algorithm. In the first layer, ignoring the possibility of collision, steering angles for the control of each robot to their associated target are determined by a genetic algorithm. In the second layer a genetic algorithm is used to determine adjustment of these controls to avid collision.
Original languageEnglish
Title of host publicationThe institute of engineering Australia
PublisherThe institute of engineering Australia
Number of pages6
ISBN (Print)0858256312
Publication statusPublished - 23 Oct 1995


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