TANGO from UC Berkeley and Princeton brings whole-body AI control to humanoid robot navigation
shahdhruv_ · x · 2026-09-25
Researchers at UC Berkeley and Princeton University introduced TANGO, a vision-language robot navigation framework for unpredictable real-world settings.
- Led by Anqi Li, with collaborators including Yuxin Chen, Zhaobo Li, Zhuo Cao, Junli Ren, Masayoshi Tomizuka (UC Berkeley) and Dhruv Shah (Princeton).
- Posted to arXiv (2026, DOI: 10.48550/arxiv.2609.09158).
- Key idea: most navigation research treats the task as drawing a 2D line on the floor; TANGO instead uses whole-body AI control, letting humanoids squeeze through narrow gaps and around obstacles in cluttered, dynamic environments.
- Aimed at homes, offices, and healthcare settings as a step toward reliable humanoid deployment.
Related event: TANGO: Full-Body Humanoid Navigation from Berkeley and Princeton(3 posts)→
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