End-to-end QP-based policies: A unified perspective on robust control and robot learning

arXiv:2609.31905 · cs.RO · Submitted 2026-09-25 · Read on arXiv

cs.RO

Submitted: 2026-09-25

Updated: 2026-09-25

Project page: https://roboticexplorationlab.org/e2eqp

Terminology

• Robustness — 10× in this paper · explained in 5 episodes
• Abstraction — 4× in this paper · explained in 1 episode
• Interpretability — 3× in this paper · explained in 15 episodes
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• IEEE International Conference on Robotics and Automation — 2× in this paper
• World Model — 2× in this paper · explained in 7 episodes
• Core — 1× in this paper · explained in 2 episodes
• Modular Architecture — 1× in this paper · explained in 4 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes

Sources

• World Model for Robot Learning: A Comprehensive Survey
• On the Differentiability of the Primal-Dual Interior-Point Method
• TurboMPC: Fast, Scalable, and Differentiable Model Predictive Control on the GPU
• A Differentiable Interior-Point Method in Single Precision
• Differentiating Through a Cone Program
• Approximation of risk-averse optimal feedback control
• Koopman based data-driven predictive control
• Choose Wisely: Data-driven Predictive Control for Nonlinear Systems Using Online Data Selection

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