arXiv:2606.19935v1 Announce Type: new Abstract: Humanoid robots require co-speech motions that are not only expressive and speech-aligned, but also physically executable under embodiment constraints. Existing co-speech generation pipelines are predominantly human-centric: motions are first generated in human-body representations such as SMPL-X and subsequently retargeted to humanoid robots. In this work, we identify a fundamental embodiment gap in this paradigm, where the mismatch between human motion manifolds and humanoid embodiment constraints disrupts embodiment consistency during motion t
This work addresses a critical technical hurdle in making humanoid robots interact naturally by bridging the existing gap between human motion generation and robot embodiment constraints, suggesting a maturation in robotics research.
Achieving physically executable and expressive co-speech motion is crucial for the widespread adoption and successful integration of humanoid robots into social and work environments, making them more natural and effective collaborators.
The previous paradigm of human-centric motion generation with subsequent retargeting will be refined or replaced by methods that directly account for humanoid embodiment, leading to more realistic and robust robot movements.
- · Humanoid robotics manufacturers
- · AI motion generation research labs
- · Entertainment industries developing virtual agents
- · Developers reliant solely on human-centric motion capture
- · Companies with less sophisticated retargeting algorithms
Humanoid robots will exhibit more natural and less awkward movements, improving human-robot interaction.
Increased realism in robot motion could accelerate public acceptance and commercial deployment of humanoids in various sectors.
The enhanced embodiment consistency might open new avenues for robot learning from human demonstration, driving further AI advancements in robotics.
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Read at arXiv cs.AI