3 papers
cs.RO2026
When Robots Sleep: Offline Skill Consolidation for Shared-Policy Robot Learning
Nethmi Jayasinghe, Diana Gontero, Amit Ranjan Trivedi
Robots that learn over long deployments must add new skills without losing the shared policy structure that makes earlier skills reusable. We study sequential robot skill learning,…
cs.RO2026
Residual Control for Fast Recovery from Dynamics Shifts
Nethmi Jayasinghe, Diana Gontero, Francesco Migliarba +4
Robotic systems operating in real-world environments inevitably encounter unobserved dynamics shifts during continuous execution, including changes in actuation, mass distribution,…
cs.LG2026
Cerebellar-Inspired Residual Control for Fault Recovery: From Inference-Time Adaptation to Structural Consolidation
Nethmi Jayasinghe, Diana Gontero, Spencer T. Brown +3
Robotic policies deployed in real-world environments often encounter post-training faults, where retraining, exploration, or system identification are impractical. We introduce an…