Robotics
Efficient Learning of Differentiable MPC Policies on the GPU via Smoothed ADMM and First-Order Reinforcement Learning
A GPU-focused approach combines Smoothed ADMM with first-order reinforcement learning to learn differentiable MPC policies.
Differentiable model predictive control (MPC) enables structured, constraint-aware policies to be optimized end-to-end.
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ArXiv CS.RO
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ArXiv CS.RO
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This approach combines structured, constraint-aware control with end-to-end policy optimization. Its focus on GPU learning and first-order reinforcement learning may make differentiable MPC more practical to train.
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