A learned predictor of the delayed state change reduces the soft robot arm's tracking error by up to 64% compared to a baseline sliding-mode controller.
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Learning-based Delay Compensation for Enhanced Control of Assistive Soft Robots
A learned predictor of the delayed state change reduces the soft robot arm's tracking error by up to 64% compared to a baseline sliding-mode controller.