Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection

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...

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Asıl Yazarlar: Zhou, Xuefeng, Wu, Hongmin, Rojas, Juan, Xu, Zhihao, Li, Shuai
Materyal Türü: Online
Dil:İngilizce
Baskı/Yayın Bilgisi: Springer Nature 2021
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Online Erişim:ONIX_20200813_9789811562631_42
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author Zhou, Xuefeng
Wu, Hongmin
Rojas, Juan
Xu, Zhihao
Li, Shuai
author_browse Li, Shuai
Rojas, Juan
Wu, Hongmin
Xu, Zhihao
Zhou, Xuefeng
author_facet Zhou, Xuefeng
Wu, Hongmin
Rojas, Juan
Xu, Zhihao
Li, Shuai
author_sort Zhou, Xuefeng
collection Directory of Open Access Books
description 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.
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spelling doab-20.500.12854ir-269522025-07-30T08:59:30Z Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection Zhou, Xuefeng Wu, Hongmin Rojas, Juan Xu, Zhihao Li, Shuai Robotics and Automation Bayesian Inference Control, Robotics, Mechatronics Machine Learning Mathematical Modeling and Industrial Mathematics Robotic Engineering Control, Robotics, Automation Collaborative Robot Introspection Nonparametric Bayesian Inference Anomaly Monitoring and Diagnosis Multimodal Perception Anomaly Recovery Human-robot Collaboration Robot Safety and Protection Hidden Markov Model Robot Autonomous Manipulation open access Robotics Bayesian inference Automatic control engineering Electronic devices & materials Machine learning Mathematical modelling Maths for engineers thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering::TJFM1 Robotics thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics::PBTB Bayesian inference thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics::PBWH Mathematical modelling thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering::TJFM1 Robotics thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics::PBTB Bayesian inference thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics::PBWH Mathematical modelling 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. 2021-02-10T13:08:14Z 2021-02-10T13:08:14Z 2020-08-13T11:54:30Z 2020 book ONIX_20200813_9789811562631_42 OCN: 1182513908 https://library.oapen.org/handle/20.500.12657/41300 https://directory.doabooks.org/handle/20.500.12854/26952 eng open access image/jpeg image/jpeg image/jpeg n/a n/a n/a https://library.oapen.org/bitstream/20.500.12657/41300/1/2020_Book_NonparametricBayesianLearningF.pdf https://library.oapen.org/bitstream/20.500.12657/41300/1/2020_Book_NonparametricBayesianLearningF.pdf https://library.oapen.org/bitstream/20.500.12657/41300/1/2020_Book_NonparametricBayesianLearningF.pdf Springer Nature Springer Singapore 10.1007/978-981-15-6263-1 10.1007/978-981-15-6263-1 9fa3421d-f917-4153-b9ab-fc337c396b5a Springer Singapore 137 open access
spellingShingle Robotics and Automation
Bayesian Inference
Control, Robotics, Mechatronics
Machine Learning
Mathematical Modeling and Industrial Mathematics
Robotic Engineering
Control, Robotics, Automation
Collaborative Robot Introspection
Nonparametric Bayesian Inference
Anomaly Monitoring and Diagnosis
Multimodal Perception
Anomaly Recovery
Human-robot Collaboration
Robot Safety and Protection
Hidden Markov Model
Robot Autonomous Manipulation
open access
Robotics
Bayesian inference
Automatic control engineering
Electronic devices & materials
Machine learning
Mathematical modelling
Maths for engineers
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering::TJFM1 Robotics
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics::PBTB Bayesian inference
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics::PBWH Mathematical modelling
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering::TJFM1 Robotics
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics::PBTB Bayesian inference
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics::PBWH Mathematical modelling
Zhou, Xuefeng
Wu, Hongmin
Rojas, Juan
Xu, Zhihao
Li, Shuai
Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection
title Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection
title_full Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection
title_fullStr Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection
title_full_unstemmed Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection
title_short Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection
title_sort nonparametric bayesian learning for collaborative robot multimodal introspection
topic Robotics and Automation
Bayesian Inference
Control, Robotics, Mechatronics
Machine Learning
Mathematical Modeling and Industrial Mathematics
Robotic Engineering
Control, Robotics, Automation
Collaborative Robot Introspection
Nonparametric Bayesian Inference
Anomaly Monitoring and Diagnosis
Multimodal Perception
Anomaly Recovery
Human-robot Collaboration
Robot Safety and Protection
Hidden Markov Model
Robot Autonomous Manipulation
open access
Robotics
Bayesian inference
Automatic control engineering
Electronic devices & materials
Machine learning
Mathematical modelling
Maths for engineers
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering::TJFM1 Robotics
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics::PBTB Bayesian inference
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics::PBWH Mathematical modelling
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering::TJFM1 Robotics
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics::PBTB Bayesian inference
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics::PBWH Mathematical modelling
topic_facet Robotics and Automation
Bayesian Inference
Control, Robotics, Mechatronics
Machine Learning
Mathematical Modeling and Industrial Mathematics
Robotic Engineering
Control, Robotics, Automation
Collaborative Robot Introspection
Nonparametric Bayesian Inference
Anomaly Monitoring and Diagnosis
Multimodal Perception
Anomaly Recovery
Human-robot Collaboration
Robot Safety and Protection
Hidden Markov Model
Robot Autonomous Manipulation
open access
Robotics
Bayesian inference
Automatic control engineering
Electronic devices & materials
Machine learning
Mathematical modelling
Maths for engineers
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering::TJFM1 Robotics
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics::PBTB Bayesian inference
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics::PBWH Mathematical modelling
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering::TJFM1 Robotics
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics::PBTB Bayesian inference
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics::PBWH Mathematical modelling
url ONIX_20200813_9789811562631_42
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