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Wearable Technology for Robotic Manipulation and Learning (Paperback, 1st ed. 2020)
Loot Price: R4,465
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Wearable Technology for Robotic Manipulation and Learning (Paperback, 1st ed. 2020)
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Over the next few decades, millions of people, with varying
backgrounds and 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
will need to infer and predict humans' intentions and internal
objectives on the basis of past interactions in order to provide
assistance before it is explicitly requested; this is the basis of
imitation learning for robotics. This book introduces readers to
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 and other motions. Furthermore it describes the
wearable-device-based and vision-based imitation learning method
for robotic manipulation, making it a valuable reference guide for
graduate students with a basic knowledge of machine learning, and
for researchers interested in wearable computing and robotic
learning.
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