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arXiv · 2403.17367

RoboDuet: Learning a Cooperative Policy for Whole-body Legged Loco-Manipulation

Guoping Pan·Qingwei Ben·Zhecheng Yuan·Guangqi Jiang·Yandong Ji·Shoujie Li·Jiangmiao Pang·Houde Liu·Huazhe Xu
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Abstract

Fully leveraging the loco-manipulation capabilities of a quadruped robot equipped with a robotic arm is non-trivial, as it requires controlling all degrees of freedom (DoFs) of the quadruped robot to achieve effective whole-body coordination. In this letter, we propose a novel framework RoboDuet, which employs two collaborative policies to realize locomotion and manipulation simultaneously, achieving whole-body control through mutual interactions. Beyond enabling large-range 6D pose tracking for manipulation, we find that the two-policy framework supports zero-shot transfer across quadruped robots with similar morphology and physical dimensions in the real world. Our experiments demonstrate that RoboDuet achieves a 23% improvement in success rate over the baseline in challenging loco-manipulation tasks employing whole-body control. To support further research, we provide open-source code and additional videos on our website: locomanip-duet.github.io.

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Guoping Pan, Qingwei Ben, Zhecheng Yuan, Guangqi Jiang, Yandong Ji, Shoujie Li, Jiangmiao Pang, Houde Liu, Huazhe Xu. 2024-03-26. RoboDuet: Learning a Cooperative Policy for Whole-body Legged Loco-Manipulation. https://arxiv.org/abs/2403.17367

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