Intelligent Control of Robotic Systems:
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 m...
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| Main Authors: | , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Dordrecht
Springer Netherlands
2003
|
| Series: | International Series on Microprocessor-Based and Intelligent Systems Engineering
25 |
| Subjects: | |
| Online Access: | DE-634 DE-573 Volltext |
| Summary: | 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 intelligent control of robotic systems |
| Physical Description: | 1 Online-Ressource (XIX, 296 p) |
| ISBN: | 9789401703178 |
| DOI: | 10.1007/978-94-017-0317-8 |
Staff View
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| 520 | |a 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 intelligent control of robotic systems | ||
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| indexdate | 2025-03-12T15:00:51Z |
| institution | BVB |
| isbn | 9789401703178 |
| language | English |
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| physical | 1 Online-Ressource (XIX, 296 p) |
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| series | International Series on Microprocessor-Based and Intelligent Systems Engineering |
| series2 | International Series on Microprocessor-Based and Intelligent Systems Engineering |
| spelling | Katic, Dusko 1959- Verfasser (DE-588)142572691 aut Intelligent Control of Robotic Systems by Dusko Katic, Miomir Vukobratovic Dordrecht Springer Netherlands 2003 1 Online-Ressource (XIX, 296 p) txt rdacontent c rdamedia cr rdacarrier International Series on Microprocessor-Based and Intelligent Systems Engineering 25 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 intelligent control of robotic systems Engineering Robotics and Automation Electrical Engineering Control, Robotics, Mechatronics Statistical Physics, Dynamical Systems and Complexity Artificial Intelligence (incl. Robotics) Mechanical Engineering Artificial intelligence Statistical physics Dynamical systems Mechanical engineering Control engineering Robotics Mechatronics Automation Electrical engineering Vukobratović, Miomir 1931-2012 Verfasser (DE-588)11933853X aut Erscheint auch als Druck-Ausgabe 9789048164264 International Series on Microprocessor-Based and Intelligent Systems Engineering 25 (DE-604)BV046828176 25 https://doi.org/10.1007/978-94-017-0317-8 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Katic, Dusko 1959- Vukobratović, Miomir 1931-2012 Intelligent Control of Robotic Systems International Series on Microprocessor-Based and Intelligent Systems Engineering Engineering Robotics and Automation Electrical Engineering Control, Robotics, Mechatronics Statistical Physics, Dynamical Systems and Complexity Artificial Intelligence (incl. Robotics) Mechanical Engineering Artificial intelligence Statistical physics Dynamical systems Mechanical engineering Control engineering Robotics Mechatronics Automation Electrical engineering |
| title | Intelligent Control of Robotic Systems |
| title_auth | Intelligent Control of Robotic Systems |
| title_exact_search | Intelligent Control of Robotic Systems |
| title_full | Intelligent Control of Robotic Systems by Dusko Katic, Miomir Vukobratovic |
| title_fullStr | Intelligent Control of Robotic Systems by Dusko Katic, Miomir Vukobratovic |
| title_full_unstemmed | Intelligent Control of Robotic Systems by Dusko Katic, Miomir Vukobratovic |
| title_short | Intelligent Control of Robotic Systems |
| title_sort | intelligent control of robotic systems |
| topic | Engineering Robotics and Automation Electrical Engineering Control, Robotics, Mechatronics Statistical Physics, Dynamical Systems and Complexity Artificial Intelligence (incl. Robotics) Mechanical Engineering Artificial intelligence Statistical physics Dynamical systems Mechanical engineering Control engineering Robotics Mechatronics Automation Electrical engineering |
| topic_facet | Engineering Robotics and Automation Electrical Engineering Control, Robotics, Mechatronics Statistical Physics, Dynamical Systems and Complexity Artificial Intelligence (incl. Robotics) Mechanical Engineering Artificial intelligence Statistical physics Dynamical systems Mechanical engineering Control engineering Robotics Mechatronics Automation Electrical engineering |
| url | https://doi.org/10.1007/978-94-017-0317-8 |
| volume_link | (DE-604)BV046828176 |
| work_keys_str_mv | AT katicdusko intelligentcontrolofroboticsystems AT vukobratovicmiomir intelligentcontrolofroboticsystems |