TANGO: Whole-Body VLA Maps RGB to 29-DoF Actions for Humanoid Navigation, Trained Fully in Simulation
berkeley_ai · x · 2026-09-24
TANGO, a CoRL 2026 work, is a whole-body VLA for humanoid navigation that directly predicts 29-DoF joint actions from RGB observations, enabling coordinated arm, torso, and gait control to traverse cluttered 3D spaces. Trained entirely in simulation, it transfers zero-shot to the real world. Project page and paper are public.
Related event: TANGO: Full-Body Humanoid Navigation from Berkeley and Princeton(3 posts)→
More from Embodied
- 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
- HT-Policy Uses Heavy-Tailed Student-t Regression to Close Robot Policy Gap — chris_j_paxton · 2026-11-12