We present ASENA, an embodied agent system that connects general-purpose coding agents to robot sensing, computation, supervised execution, and persistent experience. Agents can write and execute programs, inspect recorded outcomes, repair failures, and reuse notes and executable skills while keeping their model weight...
An-Chieh Cheng, Isabella Liu, Edmund Bu et al.· 0 citations
Manipulation failures can leave scenes in states from which a task policy cannot recover. Learning corrective behaviors requires scalable failure exploration and physical grounding. We present Recova, an agent-guided framework that jointly develops task execution and recovery in a reconstructed digital twin, then verif...
Isabella Liu, An-Chieh Cheng, Johan Bjorck et al.· 0 citations
RoboTTT, a robot model and training recipe that scale visuomotor context to 8K timesteps, three orders of magnitude beyond state-of-the-art policies, without growing inference latency, unlocks new robot capabilities: one-shot in-context imitation from human video demonstrations, on-the-fly policy improvement, robustnes...
Graph-as-Policy (GaP) is introduced, a multi-agent coding harness that generates directed computation graphs with perception, planning, and control nodes from a Modular Open Robot Skill Library (MORSL), and can achieve success rates that significantly outperform baselines.
Kai-Peng Chen, Shuang-Yu Xie, Letian Fu et al.· arXiv.org· 2 citations
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