Aspects Of Soft Computing Intelligent Robotics And Control
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Aspects of Soft Computing, Intelligent Robotics and Control
Author: János Fodor
language: en
Publisher: Springer Science & Business Media
Release Date: 2009-08-20
Soft computing, as a collection of techniques exploiting approximation and tolerance for imprecision and uncertainty in traditionally intractable problems, has become very effective and popular especially because of the synergy derived from its components. The integration of constituent technologies provides complementary methods that allow developing flexible computing tools and solving complex problems. A wide area of natural applications of soft computing techniques consists of the control of dynamic systems, including robots. Loosely speaking, control can be understood as driving a process to attain a desired goal. Intelligent control can be seen as an extension of this concept, to include autonomous human-like interactions of a machine with the environment. Intelligent robots can be characterized by the ability to operate in an uncertain, changing environment with the help of appropriate sensing. They have the power to autonomously plan and execute motion sequences to achieve a goal specified by a human user without detailed instructions. In this volume leading specialists address various theoretical and practical aspects in soft computing, intelligent robotics and control. The problems discussed are taken from fuzzy systems, neural networks, interactive evolutionary computation, intelligent mobile robotics, and intelligent control of linear and nonlinear dynamic systems.
Advances in Soft Computing, Intelligent Robotics and Control
Author: János Fodor
language: en
Publisher: Springer Science & Business Media
Release Date: 2014-03-20
Soft computing, intelligent robotics and control are in the core interest of contemporary engineering. Essential characteristics of soft computing methods are the ability to handle vague information, to apply human-like reasoning, their learning capability and ease of application. Soft computing techniques are widely applied in the control of dynamic systems, including mobile robots. The present volume is a collection of 20 chapters written by respectable experts of the fields, addressing various theoretical and practical aspects in soft computing, intelligent robotics and control. The first part of the book concerns with issues of intelligent robotics, including robust xed point transformation design, experimental verification of the input-output feedback linearization of differentially driven mobile robot and applying kinematic synthesis to micro electro-mechanical systems design. The second part of the book is devoted to fundamental aspects of soft computing. This includes practical aspects of fuzzy rule interpolation, subjective weights based meta learning in multi criteria decision making, swarm-based heuristics for an area exploration and knowledge driven adaptive product representations. The last part addresses different problems, issues and methods of applied mathematics. This includes perturbation estimates for invariant subspaces of Hessenberg matrices, uncertainty and nonlinearity modelling by probabilistic metric spaces and comparison and visualization of the DNA of six primates.
Intelligent Control of Robotic Systems
Author: D. Katic
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-03-14
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.