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Robot Intelligence, 2010 An Advanced Knowledge Processing Approach Advanced Information and Knowledge Processing Series

Langue : Anglais

Coordonnateurs : Liu Honghai, Gu Dongbing, Howlett Robert J., Liu Yonghuai

Couverture de l’ouvrage Robot Intelligence
Robot intelligence has become a major focus of intelligent robotics. Recent innovation in computational intelligence including fuzzy learning, neural networks, evolutionary computation and classical Artificial Intelligence provides sufficient theoretical and experimental foundations for enabling robots to undertake a variety of tasks with reasonable performance. This book reflects the recent advances in the field from an advanced knowledge processing perspective; there have been attempts to solve knowledge based information explosion constraints by integrating computational intelligence in the robotics context.
Programming-by-Demonstration of Robot Motions.- Grasp Recognition by Fuzzy Modeling and Hidden Markov Models.- Distributed Adaptive Coordinated Control of Multi-Manipulator Systems Using Neural Networks.- A New Framework for View-Invariant Human Action Recognition.- Using Fuzzy Gaussian Inference and Genetic Programming to Classify 3D Human Motions.- Obstacle Detection Using Cross-Ratio and Disparity Velocity.- Learning and Vision-Based Obstacle Avoidance and Navigation.- A Fraction Distortion Model for Accurate Camera Calibration and Correction.- A Leader-Follower Flocking System Based on Estimated Flocking Center.- A Behavior Based Control System for Surveillance UAVs.- Hierarchical Composite Anti-Disturbance Control for Robotic Systems Using Robust Disturbance Observer.- Autonomous Navigation for Mobile Robots with Human-Robot Interaction.- Prediction-Based Perceptual System of a Partner Robot for Natural Communication.

Dr. Honghai Liu is a Reader and Head of Intelligent Systems & Robotics Research Group (ISR), School of Creative Technologies, at the University of Portsmouth. He previously held research appointments at the Departments of Computing Science and Engineering in the Universities of London and Aberdeen, and project leader appointments in large-scale industrial control and system integration industry. Honghai has published over 150 refereed journal and conference papers including three Best Paper Awards. He is interested in approximate computation, machine intelligence, pattern recognition and their practical applications with an emphasis on approaches which could make contribution to the intelligent connection of perception to action in systems context. For this emphasis, he has been developing a framework based on approximate computing and it has been implemented into human motion analysis, multifingered robot manipulation, data novelty detection and intelligent control for electric vehicle suspensions with substantial results. He is a Senior Member of IEEE and a Member of IET.

Dongbing Gu’s current research interests include multi-agent systems, wireless sensor networks, distributed control  algorithms, distributed information fusion, cooperative control, reinforcement learning, fuzzy logic and neural network based motion control, model predictive control, wavelet multi-scale image edge detection, and Bayesian multi-scale image segmentation. His work combines fundamental concepts and tools from computer science, networks, systems and control theory.

Robert Howlett has considerable expertise in the use of Intelligent Systems in the solution of industrial problems.  He has been successful in applying neural networks, expert & fuzzy methods, web intelligence and related technology to: Sustainability: renewable energy, measurement, control, simulation and modeling of energy systems; Condition monitoring: diagnostictools and syst

Recent innovations on robot learning and adaptive methods Advanced knowledge-based qualitative reasoning Integration of robot learning and robot control Includes supplementary material: sn.pub/extras

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Date de parution :

Ouvrage de 294 p.

15.5x23.5 cm

Disponible chez l'éditeur (délai d'approvisionnement : 15 jours).

158,24 €

Ajouter au panier