Machine Learning and Robot Perception

✍ Scribed by Mario Mata, Jose Maria Armingol (auth.), Professor Bruno Apolloni, Professor Ashish Ghosh, Professor Ferda Alpaslan, Professor Lakhmi C. Jain, Professor Srikanta Patnaik (eds.)

Publisher: Springer-Verlag Berlin Heidelberg
Year: 2005
Tongue: English
Leaves: 357
Series: Studies in Computational Intelligence 7
Edition: 1
Category: Library

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✦ Synopsis

This book presents some of the most recent research results in the area of machine learning and robot perception. The chapters represent new ways of solving real-world problems. The book covers topics such as intelligent object detection, foveated vision systems, online learning paradigms, reinforcement learning for a mobile robot, object tracking and motion estimation, 3D model construction, computer vision system and user modelling using dialogue strategies. This book will appeal to researchers, senior undergraduate/postgraduate students, application engineers and scientists.

✦ Table of Contents

Learning Visual Landmarks for Mobile Robot Topological Navigation....Pages 1-55
Foveated Vision Sensor and Image Processing – A Review....Pages 57-98
On-line Model Learning for Mobile Manipulations....Pages 99-135
Continuous Reinforcement Learning Algorithm for Skills Learning in an Autonomous Mobile Robot....Pages 137-165
Efficient Incorporation of Optical Flow into Visual Motion Estimation in Tracking....Pages 167-202
3-D Modeling of Real-World Objects Using Range and Intensity Images....Pages 203-264
Perception for Human Motion Understanding....Pages 265-324
Cognitive User Modeling Computed by a Proposed Dialogue Strategy Based on an Inductive Game Theory....Pages 325-351

✦ Subjects

Automation and Robotics; Artificial Intelligence (incl. Robotics)

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