Towards Human-level Intelligence via Human-like Whole-Body Manipulation

Guang Gao; Jianan Wang; Jinbo Zuo; Junnan Jiang; Jingfan Zhang; Xianwen Zeng; Yuejiang Zhu; Lianyang Ma; Ke Chen; Minhua Sheng; Ruirui Zhang; Zhaohui An

arXiv · 2507.17141

Towards Human-level Intelligence via Human-like Whole-Body Manipulation

Guang Gao·Jianan Wang·Jinbo Zuo·Junnan Jiang·Jingfan Zhang·Xianwen Zeng·Yuejiang Zhu·Lianyang Ma·Ke Chen·Minhua Sheng·Ruirui Zhang·Zhaohui An

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Abstract

Building general-purpose intelligent robots has long been a fundamental goal of robotics. A promising approach is to mirror the evolutionary trajectory of humans: learning through continuous interaction with the environment, with early progress driven by the imitation of human behaviors. Achieving this goal presents three core challenges: (1) designing safe robotic hardware with human-level physical capabilities; (2) developing an intuitive and scalable whole-body teleoperation interface for data collection; and (3) creating algorithms capable of learning whole-body visuomotor policies from human demonstrations. To address these challenges in a unified framework, we propose Astribot Suite, a robot learning suite for whole-body manipulation aimed at general daily tasks across diverse environments. We demonstrate the effectiveness of our system on a wide range of activities that require whole-body coordination, extensive reachability, human-level dexterity, and agility. Our results show that Astribot's cohesive integration of embodiment, teleoperation interface, and learning pipeline marks a significant step towards real-world, general-purpose whole-body robotic manipulation, laying the groundwork for the next generation of intelligent robots.

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Guang Gao, Jianan Wang, Jinbo Zuo, Junnan Jiang, Jingfan Zhang, Xianwen Zeng, Yuejiang Zhu, Lianyang Ma, Ke Chen, Minhua Sheng, Ruirui Zhang, Zhaohui An. 2025-07-23. Towards Human-level Intelligence via Human-like Whole-Body Manipulation. https://arxiv.org/abs/2507.17141

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