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This paper reviews a number of recent algorithms for mobile robot path planning, navigation and motion control, which employ fuzzy logic and neurofuzzy learning and reasoning. Staring with a discussion of the structure of fuzzy and neurofuzzy systems, two fuzzy obstacle avoidance path planning algorithms are presented followed by a 3-level neurofuzzy local and global path planning scheme. Then the motion planning and control problem is considered. A fuzzy path tracking strategy is outlined, followed by a fuzzy navigation algorithm among polygonal obstacles and a learning-by-doing neurofuzzy motion planning scheme. The paper ends with a hybrid robust motion control technique witch combines the minimum interference and sliding mode control principles with fuzzy inference. A representative set of examples are included which illustrate the performance of the algorithms under various realistic conditions.
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Tom
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25--39
Opis fizyczny
Bibliogr. 36 poz., rys. 5
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autor
- Intelligent Robotics and Automation Laboratory, Electrical and Computer Engineering Department, National Technical University of Athens, Zografou 157 73, Athens, Greece.
Bibliografia
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Bibliografia
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bwmeta1.element.baztech-article-BPW1-0009-0015