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ReCo: Response-Consistent Locomotion with Policy-Aware MPC for Legged Manipulation
Continuous legged manipulation requires accurate end-effector tracking while the base keeps walking. Combining reinforcement learning (RL) with model predictive control (MPC) suits this task: the learned policy provides robust locomotion, while MPC coordinates the base and arm to compensate for trac
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