Recover, Discover, Plan: Learning Skills and Concepts from R
Overview
Source roundup from published reports. Claims below are attributed to their publishers, not independently verified. arXiv Robotics — research abstracts: Recover, Discover, Plan: Learning Skills and Concepts from Robot Failures. This research proposes ReSYNC, a method that allows robots to progressively discover and refine state abstractions from failure-recovery experiences, enabling abstract planning. The approach combines skill learning via r…
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Environment: simulation
“obot discovers new relational predicates and refines its abstract planning model to explain and generalize the learned recovery behaviors. This interaction enables ReSYNC to convert local recoveries seen during training into global failure avoidance at test time. Across four simulated domains, we show that ReSYNC's ability to continually expand and refine its abstraction library allows it to solve long-horizon, previ”
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- arXiv Robotics — research abstractsRecover, Discover, Plan: Learning Skills and Concepts from Robot Failures
This research proposes ReSYNC, a method that allows robots to progressively discover and refine state abstractions from failure-recovery experiences, enabling abstract planning. The approach combines skill learning via reinforcement learning with concept refinement through dual-learning, achieving over 50% performance improvements in simulated domains and demonstrating sim-to-real transfer for real-world manipulation tasks.
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