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Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection

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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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Bibliographic Details
Main Authors: Zhou, Xuefeng (Author), Wu, Hongmin (Author), Rojas, Juan (Author), Xu, Zhihao (Author), Li, Shuai (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Singapore : Springer Nature Singapore : Imprint: Springer, 2020.
Edition:1st ed. 2020.
Subjects:
Robotics.
Statistics .
Control engineering.
Automation.
Machine learning.
Mathematical models.
Robotic Engineering.
Bayesian Inference.
Control, Robotics, Automation.
Machine Learning.
Mathematical Modeling and Industrial Mathematics.
Online Access:Link to Metadata
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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.

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