SOURCE-LINKED INTELLIGENCE
HIGenNTO: Scalable Humanoid Interaction Generation via Noise-Space Trajectory Optimization
Humanoid robots can acquire complex skills by imitating kinematic humanoid motion references, yet reliable references for contact-rich interactions remain difficult to obtain: motion capture deteriorates under occlusion and close physical contact, while retargeting introduces additional contact and geometric inconsistencies. We present HIGenNTO, a framework that synthesizes humanoid-scene interaction motion references by optimizing the initial noise of a pretrained text-conditioned motion model under sparse spatiotemporal and scene constraints. The same formulation satisfies desired contacts,
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-18T21:52:56.000Z
First collected: 2026-09-23T12:01:45.602Z. This is not the publication date.