Grounded Action Model: Building Robot Foundation Models on 3D Grounding, Hits 61% on LIBERO-PRO
DJiafei · x · 2026-09-22
Researchers propose Grounded Action Model (GAM), a new paradigm building robot foundation models on pretrained 3D grounding rather than language (VLA) or video (WAM) backbones.
- Language/point/box prompts are converted into an object-centric representation mixing target visual features and metric geometry, fused with robot state history via a multi-stream transformer to predict action chunks.
- Can act autonomously or serve as a low-level controller under a high-level planner (Molmo2); on Franka, GAM+Molmo2 achieves 64.7% in-distribution and 49.8% OOD step completion.
- RoboTwin 2.0: 55.3% average success across 50 tasks (vs 52.0% Spatial Forcing), 47.6% under scene randomization (vs 30.4% Abot-M0), trained only on clean-scene demos.
- LIBERO-PRO: 61% average across 16 settings (vs 53% for π0.5); 88% vs 1% on target-switch tasks.
- Limitations: grounding errors and omitted context remain. Paper, code, and project page are public.
Related event: GAM: Grounded Action Model Proposes 3D Grounding as Robot Foundation Base(6 posts)→
More from Embodied
- Team claims a robot priced like a modern smartphone, presale buyers get the best deal — R4nsack · 2026-11-12
- CoRL results show sim-only training now delivers top real-world robot performance — carlosdponx · 2026-11-12
- Robot fails at folding a towel, reassuring roboticists frontier models won't eat robotics yet — chris_j_paxton · 2026-11-12
- Nuro podcast: manufacturing, charging, and regulation gate robotaxi mass adoption — R_D · 2026-11-12
- Rodeo Robotics demos robot that changes your car tire — ycombinator · 2026-11-12
- Cybercab rear-ended by human driver, researcher quips: the problem is the humans — chris_j_paxton · 2026-11-12