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RoboDuet: Learning a Cooperative Policy for Whole-body Legged Loco-Manipulation
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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.
Forward citations
Cited by 7 Pith papers
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Human2LocoMan: Learning Versatile Quadrupedal Manipulation with Human Pretraining
Pretraining a modular transformer policy on human demonstrations then finetuning on a small robot dataset improves success on six real quadruped manipulation tasks, including out-of-distribution objects.
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Versatile Loco-Manipulation through Flexible Interlimb Coordination
ReLIC lets a robot dog dynamically reassign its legs between walking and manipulating, achieving 78.9% average success across 12 real-world loco-manipulation tasks.
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SLIM: Sim-to-Real Legged Instructive Manipulation via Long-Horizon Visuomotor Learning
A single policy trained purely in simulation with a hierarchical teacher-student pipeline solves long-horizon search-grasp-transport-drop tasks on a low-cost quadruped with about 78% real-world success.
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WildLMa: Long Horizon Loco-Manipulation in the Wild
WildLMa combines VR teleoperation with whole-body control, CLIP-based language-conditioned imitation learning, and an LLM planner to give a quadruped robot reusable manipulation skills that generalize to unseen object...
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Mobile-TeleVision: Predictive Motion Priors for Humanoid Whole-Body Control
A decoupled humanoid controller combines IK-based arm control with an RL locomotion policy conditioned on a CVAE motion prior, improving manipulation precision while maintaining walking stability.
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