Machine Learning and Robot Perception
Title:
Machine Learning and Robot Perception
Author:
Apolloni, Bruno. editor.
ISBN:
9783540324096
Physical Description:
X, 354 p. online resource.
Series:
Studies in Computational Intelligence, 7
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.
Abstract:
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.
Added Corporate Author:
Electronic Access:
http://dx.doi.org/10.1007/b137627