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Research questionHow can mission-critical robots learn from verified post-deployment experience on limited onboard compute without forgetting prior skills?Mission-critical robots encounter novel situations after deployment, but field data are scarce and onboard resources constrain adaptation. Updating behavior can also degrade skills acquired before deployment.
AI
Machine Learning
Robotics
Small / On-device Models
Latest papersRecent research connected to this question, newest first.Continual Field-Adaptive Models (CFAMs) for Post-Deployment Physical AIThe evidence covers physical AI across manipulators, quadrupeds, humanoids, quadrotors, and off-road vehicles, with few-shot skill learning in the lab and continual updates in the field. It reports autonomous capture of verified near-out-of-distribution cases and sequential-simulation retention results; open-world novelty is outside the stated scope.research paper · Sep 3, 2026
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