tailieunhanh - Sổ tay thiết kế hệ thống cơ khí P24

24 Intelligent Soft-Computing Techniques in Robotics Introduction Connectionist Approach in Robotics Basic Concepts • Connectionist Models with Applications in Robotics • Learning Principles and Rules Neural Network Issues in Robotics Kinematic Robot Learning by Neural Networks • Dynamic Robot Learning at the Executive Control Level • Sensor-Based Robot Learning Dustic M. Kati´ c Mihajlo Pupin Institute Fuzzy Logic Approach Introduction • Mathematical Foundations • Fuzzy Controller • Direct Applications • Hybridization with Model-Based Control Branko Karan Mihajlo Pupin Institute Neuro-Fuzzy Approach in Robotics Genetic Approach in Robotics Conclusion Introduction Robots and machines that perform various tasks in an intelligent and autonomous manner are required in many contemporary technical. | 24 Intelligent Soft-Computing Techniques in Robotics Dustic M. Katic Mihajlo Pupin Institute Branko Karan Mihajlo Pupin Institute Introduction Connectionist Approach in Robotics Basic Concepts Connectionist Models with Applications in Robotics Learning Principles and Rules Neural Network Issues in Robotics Kinematic Robot Learning by Neural Networks Dynamic Robot Learning at the Executive Control Level Sensor-Based Robot Learning Fuzzy Logic Approach Introduction Mathematical Foundations Fuzzy Controller Direct Applications Hybridization with Model-Based Control Neuro-Fuzzy Approach in Robotics Genetic Approach in Robotics Conclusion Introduction Robots and machines that perform various tasks in an intelligent and autonomous manner are required in many contemporary technical systems. Autonomous robots have to perform various anthropomorphic tasks in both unfamiliar or familiar working environments by themselves much like humans. They have to be able to determine all possible actions in unpredictable dynamic environments using information from various sensors. In advance human operators can transfer to robots the knowledge experience and skill to solve complex tasks. In the case of a robot performing tasks in an unknown enviroment the knowledge may not be sufficient. Hence robots have to adapt and be capable of acquiring new knowledge through learning. The basic components of robot intelligence are actuation perception and control. Significant effort has been attempted to make robots more intelligent by integrating advanced sensor systems as vision tactile sensing etc. But one of the ultimate and primary goals of contemporary robotics is development of intelligent algorithms that can further improve the performance of robotic systems using the above-mentioned human intelligent functions. Intelligent control is a new discipline that has emerged from the classical control disciplines with primary research interest in specific .