Adaptive Compensation for Robotic Joint Failures Using Partially Observable Reinforcement Learning
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DOI: 10.3390/a17100436
Abstract: Robotic manipulators are widely used in various industries for complex and repetitive tasks. However, they remain vulnerable to unexpected hardware failures. In this study, we address the challenge of enabling a robotic manipulator to complete… read more here.
Keywords: partially observable; adaptive compensation; joint failures; reinforcement learning ... See more keywords