| 書目名稱 | Intelligent Control of Robotic Systems | | 編輯 | Dusko Katic,Miomir Vukobratovic | | 視頻video | http://file.papertrans.cn/470/469550/469550.mp4 | | 叢書名稱 | Intelligent Systems, Control and Automation: Science and Engineering | | 圖書封面 |  | | 描述 | As robotic systems make their way into standard practice, they have opened the door to a wide spectrum of complex applications. Such applications usually demand that the robots be highly intelligent. Future robots are likely to have greater sensory capabilities, more intelligence, higher levels of manual dexter- ity, and adequate mobility, compared to humans. In order to ensure high-quality control and performance in robotics, new intelligent control techniques must be developed, which are capable of coping with task complexity, multi-objective decision making, large volumes of perception data and substantial amounts of heuristic information. Hence, the pursuit of intelligent autonomous robotic systems has been a topic of much fascinating research in recent years. On the other hand, as emerging technologies, Soft Computing paradigms consisting of complementary elements of Fuzzy Logic, Neural Computing and Evolutionary Computation are viewed as the most promising methods towards intelligent robotic systems. Due to their strong learning and cognitive ability and good tolerance of uncertainty and imprecision, Soft Computing techniques have found wide application in the area of intelli | | 出版日期 | Book 2003 | | 關(guān)鍵詞 | Fuzzy; algorithms; classification; control algorithm; development; fuzzy logic; genetic algorithms; learnin | | 版次 | 1 | | doi | https://doi.org/10.1007/978-94-017-0317-8 | | isbn_softcover | 978-90-481-6426-4 | | isbn_ebook | 978-94-017-0317-8Series ISSN 2213-8986 Series E-ISSN 2213-8994 | | issn_series | 2213-8986 | | copyright | Springer Science+Business Media B.V. 2003 |
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