TANGO: Sim-Only Trained Whole-Body VLA Gives Humanoids Zero-Shot Navigation on Unitree G1
chris_j_paxton · x · 2026-09-24
CoRL 2026 paper TANGO introduces a whole-body vision-language navigation framework that predicts 29-DoF joint-space actions directly from egocentric RGB, letting humanoids navigate cluttered 3D spaces with coordinated arms, torso, and gait.
- Treats navigation as a whole-body problem requiring continuous geometry-aware adaptation, not a 2D abstraction
- Plan-Edit-Track pipeline synthesizes diverse collision-free traversal data in simulation via global path planning, kinematic motion generation, obstacle-aware editing, and RL-based tracking
- Triple-system model (vision-language backbone + action expert) outputs executable whole-body action chunks
- Trained entirely in simulation, transfers zero-shot to a real Unitree G1 with no real-world training data
The authors note large-scale sim for training policies is really starting to work.
Related event: TANGO: Full-Body Humanoid Navigation from Berkeley and Princeton(3 posts)→
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