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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書誌詳細
第一著者:	Zhou, Xuefeng (auth)
その他の著者:	Wu, Hongmin (auth), Rojas, Juan (auth), Xu, Zhihao (auth), Li, Shuai (auth)
フォーマット:	電子媒体図書の章
言語:	英語
出版事項:	Springer Nature 2020
主題:	Robotics Bayesian inference Automatic control engineering Machine learning Mathematical modelling 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 Electronic devices & materials Maths for engineers
オンライン･アクセス:	OAPEN Library: download the publication OAPEN Library: description of the publication
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Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection

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