Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection is popular PDF and ePub book, written by Xuefeng Zhou in 2020-01-01, it is a fantastic choice for those who relish reading online the Automatic control genre. Let's immerse ourselves in this engaging Automatic control book by exploring the summary and details provided below. Remember, Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection can be Read Online from any device for your convenience.
Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection Book PDF Summary
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.
Detail Book of Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection PDF
- Author : Xuefeng Zhou
- Release : 01 January 2020
- Publisher : Springer Nature
- ISBN : 9789811562631
- Genre : Automatic control
- Total Page : 149 pages
- Language : English
- PDF File Size : 21,5 Mb
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