Wearable Technology For Robotic Manipulation And Learning

November 11, 2020|
Wearable Technology For Robotic Manipulation And Learning by Bin Fang
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In the next few decades, millions of people, from various backgrounds and with differing levels of technical expertise, will have to effectively interact with robotic technologies on a daily basis. This means it will have to be possible to modify robot behavior without explicitly writing code, but instead via a small number of wearable devices or visual demonstrations. At the same time, robots should try to infer and predict the human''s intentions and internal objectives from past interactions in order to provide assistance before it is explicitly requested; this is the basis of imitation learning for robotics.

 

This book introduces robotic imitation learning based on human demonstration with wearable devices. It presents an advanced calibration method for wearable sensors and fusion approaches under the Kalman filter framework, as well as a novel wearable device for capturing gestures motions. Furthermore it describes the wearable-device-based and vision-based imitation learning method for robotic manipulation. It is a valuable reference book for graduate students with a basic knowledge of machine learning, as well as researchers interested in wearable computing and robotic learning.

Bin Fang is an Assistant Researcher at the Department of Computer Science and Technology, Tsinghua University. His research interests include wearable device and human-robot interaction. He is a guest editor for a number of journals, includingFrontiers in Neurorobotics, and has served as a reviewer for various journals and conferences,...
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Title:Wearable Technology For Robotic Manipulation And LearningFormat:HardcoverProduct dimensions:9.25 X 6.1 X 0 inShipping dimensions:9.25 X 6.1 X 0 inPublished:November 11, 2020Publisher:Springer NatureLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:9811551235

ISBN - 13:9789811551239

Appropriate for ages: All ages

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