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
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.
BibTeX
@inproceedings{ral2025_roboduetlearning,
title = {RoboDuet: Learning a Cooperative Policy for Whole-Body Legged Loco-Manipulation},
author = {Guoping Pan and Qingwei Ben and Zhecheng Yuan and Guangqi Jiang and Yandong Ji and Shoujie Li and Jiangmiao Pang and Houde Liu and Huazhe Xu},
booktitle = {RA-L 2025},
year = {2025}
}