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:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009428423206719
Tabla de Contenidos:
  • 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.