Can embodied task agents use tactile experience to perform fine manipulation without task-specific model training? We investigate this capability through Tactile-ETA, a system that incorporates tactile experience into an embodied task agent through in-context learning.
ORIGINAL PAPER
Embodied Task Agents Can Perform Fine Manipulation through Tactile In-Context Learning
WHAT WE KNOW
Successful expert demonstrations show how contact changes during manipulation. We pair each recorded robot movement with its camera views and bilateral tactile observations. We keep tactile observations at the start and end of each movement and add two neighboring time points when the tactile images change markedly in between.
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EVIDENCE
What the evidence supports so far
Research signals
Classification pending.
What remains unverified
The full methodology, effect size, and limitations still require analyst review.
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