arXiv:2606.29209v1 Announce Type: cross Abstract: We present AnyBody, a unified whole-body humanoid controller driven by an arbitrary subset of body keypoints chosen at deploy time. Prior physics-based trackers either rely on expensive full-body motion capture and error-prone trajectory retargeting, which bottleneck scalable data collection and policy learning, or decompose upper- and lower-body control into separate hierarchical representations, sacrificing the coordinated whole-body motions that loco-manipulation requires. We close this gap by learning a single latent motion representation t
The development of AnyBody reflects ongoing advancements in AI and robotics, specifically addressing limitations in scalable data collection and policy learning for humanoids.
This breakthrough simplifies the control of complex humanoid robots, allowing for more intuitive and scalable training, which directly accelerates the practical deployment of these robots.
Traditional reliance on expensive motion capture or segmented control is replaced by a unified, flexible keypoint-driven system, making humanoid control more accessible and adaptable.
- · Humanoid robotics developers
- · AI research institutions
- · Logistics and manufacturing sectors
- · Robotics hardware manufacturers
- · Traditional motion capture service providers
- · Companies reliant on bespoke or highly specialized robotics control systems
More efficient and adaptable humanoid robot behaviors will emerge, enabling new applications.
Reduced development costs and faster deployment cycles could accelerate commercialization and widespread adoption of humanoid robots.
The increased capability of humanoid robots could lead to significant labor force reallocations in physical tasks.
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Read at arXiv cs.AI