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arxiv: 2403.17367 · v5 · pith:ORDK5FKBnew · submitted 2024-03-26 · 💻 cs.RO

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

classification 💻 cs.RO
keywords whole-bodyloco-manipulationquadrupedroboduetcontrolframeworkmanipulationrobot
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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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  1. SigLoMa: Learning Open-World Quadrupedal Loco-Manipulation from Ego-Centric Vision

    cs.RO 2026-05 unverdicted novelty 6.0

    SigLoMa enables dynamic loco-manipulation on quadrupeds from ego-centric 5 Hz vision alone by using Sigma Points for scalable exteroception, an ego-centric Kalman Filter for high-rate state estimation, and an active s...