Nonparametric Bayesian learning for collaborative robot multimodal introspection / Xuefeng Zhou, Hongmin Wu, Juan Rojas, Zhihao Xu, Shuai Li.
2020
TJ211
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Title
Nonparametric Bayesian learning for collaborative robot multimodal introspection / Xuefeng Zhou, Hongmin Wu, Juan Rojas, Zhihao Xu, Shuai Li.
Author
Zhou, Xuefeng.
ISBN
9789811562631 (electronic book)
9811562636 (electronic book)
9811562628
9789811562624
9811562636 (electronic book)
9811562628
9789811562624
Publication Details
Singapore : Springer, 2020.
Language
English
Description
1 online resource
Item Number
10.1007/978-981-15-6263-1 doi
10.1007/978-981-15-6
10.1007/978-981-15-6
Call Number
TJ211
Dewey Decimal Classification
629.8/92
Summary
This open access book focuses on robot introspection, which has a direct impact on physical human-robot interaction and long-term autonomy, and which can benefit from autonomous anomaly monitoring and diagnosis, as well as anomaly recovery strategies. In robotics, the ability to reason, solve their own anomalies and proactively enrich owned knowledge is a direct way to improve autonomous behaviors. To this end, the authors start by considering the underlying pattern of multimodal observation during robot manipulation, which can effectively be modeled as a parametric hidden Markov model (HMM). They then adopt a nonparametric Bayesian approach in defining a prior using the hierarchical Dirichlet process (HDP) on the standard HMM parameters, known as the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM). The HDP-HMM can examine an HMM with an unbounded number of possible states and allows flexibility in the complexity of the learned model and the development of reliable and scalable variational inference methods. This book is a valuable reference resource for researchers and designers in the field of robot learning and multimodal perception, as well as for senior undergraduate and graduate university students.
Bibliography, etc. Note
Includes bibliographical references.
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Access limited to authorized users.
Added Author
Wu, Hongmin.
Rojas, Juan.
Xu, Zhihao.
Li, Shuai, 1983-
Rojas, Juan.
Xu, Zhihao.
Li, Shuai, 1983-
Available in Other Form
Print version: 9789811562624
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Table of Contents
Introduction to Robot Introspection
Nonparametric Bayesian Modeling of Multimodal Time Series
Incremental Learning Robot Complex Task Representation and Identification
Nonparametric Bayesian Method for Robot Anomaly Monitoring
Nonparametric Bayesian Method for Robot Anomaly Diagnose
Learning Policy for Robot Anomaly Recovery based on Robot.
Nonparametric Bayesian Modeling of Multimodal Time Series
Incremental Learning Robot Complex Task Representation and Identification
Nonparametric Bayesian Method for Robot Anomaly Monitoring
Nonparametric Bayesian Method for Robot Anomaly Diagnose
Learning Policy for Robot Anomaly Recovery based on Robot.