RoboGesture: Real-Time Semantic-aligned Co-Speech Gestures Generation for Humanoid Interaction
Enabling humanoid robots to respond to human speech with synchronized and semantically meaningful gestures is fundamental to natural human-robot interaction. However, this task faces three critical barriers: the scarcity of semantically rich datasets, the "modality eclipse" where models ignore audio cues in favor of kinematic inertia, and the sim-to-real gap regarding physical safety. We propose RoboGesture, a robot-centric framework that co-designs data, modeling, and control to power a complete interactive human-humanoid system in which the robot listens, responds, and gestures in real time. We first establish the RoboGesture dataset featuring over 300 gesture categories and develop an ...
| Authors | Zifan Wang, Ziang Ren, Pengyang Shi et al. |
|---|---|
| Primary category | cs.RO |
| Published | 27 August 2026 |
| Last updated at source | 27 August 2026 |
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