Machine Learning and Robot Perception / Edition 1

Paperback (Print)


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.

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Product Details

  • ISBN-13: 9783642065866
  • Publisher: Springer Berlin Heidelberg
  • Publication date: 10/22/2014
  • Series: Studies in Computational Intelligence Series , #7
  • Edition description: Softcover reprint of hardcover 1st ed. 2005
  • Edition number: 1
  • Pages: 354

Table of Contents

Learning Visual Landmarks for Mobile Robot Topological Navigation.- Foveated Vision Sensor and Image Processing – A Review.- On-line Model Learning for Mobile Manipulations.- Continuous Reinforcement Learning Algorithm for Skills Learning in an Autonomous Mobile Robot.- Efficient Incorporation of Optical Flow into Visual Motion Estimation in Tracking.- 3-D Modeling of Real-World Objects Using Range and Intensity Images.- Perception for Human Motion Understanding.- Cognitive User Modeling Computed by a Proposed Dialogue Strategy Based on an Inductive Game Theory.
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