LIBERO-Pro (Product): news timeline & CVEs

RAPID: Robot Agentic Programming from Demonstrations

RAPID turns one visual human demonstration into verified, reusable robot programs via an agentic coding loop.

RAPID generates, verifies, and refines robot programs from a single visual human demonstration by inferring a task specification, action primitives, and an interactive test environment. Programs are object-centric and relational: primitives are trajectory-optimization problems for object-level effects, composed with run-time geometric constraints. It is evaluated in simulation on eight contact-rich nonprehensile tasks and on LIBERO-Pro prehensile tasks, and deployed on a real Franka arm for all eight nonprehensile tasks. Results report generalization across object pose, shape, material, and environment.

arXiv cs.AI / cs.LG / cs.CLSep 24, 17:58 UTC · 2d agoAI research

Grounded Action Model: 3D Grounding as a Foundation for Robotics

Grounded Action Models use 3D object grounding and beat prior robot policies on RoboTwin and LIBERO-PRO.

Grounded Action Models build robot policies around explicit 3D object grounding rather than learning metric location only from demonstrations. Language, point, or box prompts become a shared object-centric representation that a multi-stream transformer mixes with robot state to predict action chunks. On RoboTwin 2.0, GAM averages 55.3% success across 50 tasks and 47.6% under scene randomization. It reaches 61% on LIBERO-PRO and, on real robots, 17 of 20 successes under visual shift on a bimanual YAM, with a Molmo2 planner scoring 64.7% in-distribution step completion on a Franka.

Hugging Face daily papersSep 19, 20:00 UTC · 7d agoAI research

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RAPID: Robot Agentic Programming from Demonstrations

Grounded Action Model: 3D Grounding as a Foundation for Robotics