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cs.RO2026
The Unexpired Plan: A Free Monitor for Accelerated Diffusion Policies
Yi Zhao, Sebastian Scherer
Training-free acceleration of a diffusion policy is accepted when an internal similarity signal reports that the shortcut changed nothing. We price every monitor a control loop can…
cs.RO2026
Recover, Discover, Plan: Learning Skills and Concepts from Robot Failures
Bowen Li, Mayank Mishra, Y. Isabel Liu +7
Intelligent robots should not only recover from failures, but also acquire the abstract knowledge needed to avoid them in the future. While reinforcement learning (RL) can learn re…
cs.RO2026
World2Rules: A Neuro-Symbolic Framework for Learning World-Governing Safety Rules for Aviation
Haichuan Wang, Jay Patrikar, Sebastian Scherer
Many real-world safety-critical systems are governed by explicit rules that define unsafe world configurations and constrain agent interactions. In practice, these rules are comple…