【论文速递】Pixel: A Co-Designed Full-Stack Robot System for Learning General-Purpose Mobile

英文标题：Pixel: A Co-Designed Full-Stack Robot System for Learning General-Purpose Mobile Manipulation

arXiv编号：2611.03648
作者：Tony Tao, Jason Jingzhou Liu, Ruslan Salakhutdinov
来源：arXiv
原文链接：https://arxiv.org/abs/2611.03648

中文摘要：
General-purpose mobile manipulation requires a combination of capable robot hardware, scalable demonstration collection, expressive whole-body control, and effective policy learning. Yet these components are often developed independently, creating mismatches that limit the capabilities of the complete system. We present Pixel, a co-designed full-stack system for learning general-purpose mobile manipulation. Pixel combines a low-cost wheeled humanoid with human-aligned kinematics and compliant grippers, multiple teleoperation and robot-free human data-collection interfaces, a unified whole-body controller, and a common policy learning pipeline across human and robot demonstrations. A hierarchical learning stack further enables language-conditioned visuomotor control and long-horizon task execution. We evaluate the system across hardware, data collection, and policy learning, and demonstrate mobile-manipulation behaviors requiring dexterity, active perception, navigation, and whole-body coordination. We hope that Pixel provides an integrated and extensible foundation for studying how robot hardware, data, control, and learning can be designed together for robot learning. More results at https://pixel-robot.com/pixel

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