mlsanityData to 14 Oct 2026

CA-AC-MPC: CUDA-Accelerated Actor-Critic Model Predictive Control

arXiv 2605.29155 ↗First posted 27 May 2026cs.RO cs.AI cs.DCcited by 0

On the map: Deep reinforcement learning methods → RL for autonomous driving and traffic

Abstract (arXiv)

In the literature, actor-critic model predictive control (AC-MPC) integrates MPC with reinforcement learning to enable high-performance control of complex dynamical systems. However, its differentiable MPC layer requires repeatedly solving an optimization problem in both the forward and backward passes, leading to substantial training and inference latency. This paper tackles this bottleneck introducing a CUDA-accelerated variant that significantly reduces end-to-end execution time while preserving the control performance of the baseline formulation. Simulation results on an agile drone racing task show that our approach achieves state-of-the-art lap times and near-limit dynamic behaviour with markedly reduced training and inference time.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in RL for autonomous driving and traffic, one of 15 directions in Deep reinforcement learning methods. Builds on 11 of its 24 references that are in the map. First posted on arXiv 27 May 2026.

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11 of 24 references.

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  1. 2025Differentiable Model Predictive Control on the GPU7 Oct

Other references · 10

  1. 2015End-to-End Training of Deep Visuomotor Policiescited by 875
  2. 2017OptNet: Differentiable Optimization as a Layer in Neural Networkscited by 599
  3. 2019Differentiable Convex Optimization Layerscited by 465
  4. 2017Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuningcited by 297
  5. 2018Differentiable MPC for End-to-end Planning and Controlcited by 189
  6. 2023Reaching the Limit in Autonomous Racing: Optimal Control versus Reinforcement Learningcited by 111
  7. 2023A Survey on Transformers in Reinforcement Learningcited by 50
  8. 2021Model Predictive Contouring Control for Time-Optimal Quadrotor Flightcited by 21
  9. 2023Actor-Critic Model Predictive Control: Differentiable Optimization meets Reinforcement Learning for Agile Flightcited by 19
  10. 2025Primal-Dual iLQR for GPU-Accelerated Learning and Control in Legged Robotscited by 8

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  1. 2024AC4MPC: Actor-Critic Reinforcement Learning for Nonlinear Model Predictive Control
  2. 2025Residual MPC: Blending Reinforcement Learning with GPU-Parallelized Model Predictive Control
  3. 2025Synthesis of Model Predictive Control and Reinforcement Learning: Survey and Classification
  4. 2026TurboMPC: Fast, Scalable, and Differentiable Model Predictive Control on the GPU
  5. 2025On Architectures for Combining Reinforcement Learning and Model Predictive Control with Runtime Improvements
  6. 2024Faster Model Predictive Control via Self-Supervised Initialization Learning
  7. 2025MPC4RL -- A Software Package for Reinforcement Learning based on Model Predictive Control
  8. 2025MPCritic: A plug-and-play MPC architecture for reinforcement learning