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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Detalles Bibliográficos
Autores principales:	Zhou, Xuefeng. author (author), Wu, Hongmin. author, Rojas, Juan. author, Xu, Zhihao. author, Li, Shuai. author
Formato:	Libro electrónico
Idioma:	Inglés
Publicado:	Singapore : Springer Nature 2020 2020.
Edición:	1st ed. 2020.
Materias:	Robotics. Automation. Statistics . Control engineering. Mechatronics. Machine learning. Mathematical models. Robotics and Automation. Bayesian Inference. Control, Robotics, Mechatronics. Machine Learning. Mathematical Modeling and Industrial Mathematics. 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
Ver en Biblioteca Universitat Ramon Llull:	https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009428423206719