Abstract
The paper experimentally compares six visual oscillation sensing approaches for a three degrees of freedom flexible link robot arm with an eye-in-hand RGB-D camera. The comparison includes five representative scenarios. Based upon the results the authors propose a novel scene adaptive camera motion reconstruction scheme. The scheme adaptively selects the best approach according to the actual scene texture and depth profile. Experiments in indoor scenarios with sparse texture, poor depth profiles as well as dynamic scene contents approve the obtained signal quality to be well suited for visual vibration damping of flexible link robot arms in a great variety of frequently observed scenarios.
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