Affiliation:
1. South China University of Technology, Guangzhou, China
Abstract
The objective of this paper is to develop a novel human-manipulator interface which incorporates wearable-based and markerless tracking to interact with the continuous movements of a human operator's hand. Unlike traditional approaches, which usually include contacting devices or physical markers to track the human-limb movements, this interface enables registration of natural movement through a wireless wearable watch and a leap motion sensor. Due to sensor error and tracking failure, the measurements are not made with sufficient accuracy. Two Kalman filters are employed to compensate the noisy and incomplete measurements in real time. Furthermore, due to perceptive limitations and abnormal state signals, the operator is unable to achieve high precision and efficiency in robot manipulation; an adaptive multispace transformation method (AMT) is therefore introduced, which serves as a secondary treatment. In addition, in order to allow two-way human-robot interaction, the proposed method provides a vibration feedback mechanism triggered by the wearable watch to call the operator's attention to robot collision incidents or moments where the operator's hand is in a transboundary state. This improves teleoperation.
Subject
Artificial Intelligence,Computer Science Applications,Software
Cited by
6 articles.
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