Accelerating Visual Policy Learning with Sampling-Based Model Predictive Control
Learning visual policies for locomotion and manipulation requires coordinating contact with the environment and can incur substantial computation and GPU memory costs. First-order policy gradients (FoPG) reduce training cost through differentiable simulation, but local optimization can converge to unintended contact pa...
Yi-Lang Liu, Hao-Xiang You, Qian Wang et al.
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