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cs.RO2026
Pixels to Proofs: Probabilistically-Safe Latent World Model Control via Parallel Conformal Robust MPC
Devesh Nath, Anutam Srinivasan, Haoran Yin +3
We present SLS^2, a framework for safe feedback motion planning from pixels using robust model predictive control (MPC) in learned latent world models. Our approach trains an actio…
cs.RO2026
Robustness without Wrinkles: Parallel Simulation and Robust MPC for Certified Deformable Manipulation
Wei-Chen Li, Jeffrey Fang, Sasanka Polisetti +2
We present CORD-SLS, a real-time control method for safe deformable object manipulation, with a focus on ropes and cloth. At its core is a GPU-parallel differentiable simulator wit…
cs.RO2026
Safe Large-Scale Robust Nonlinear MPC in Milliseconds via Reachability-Constrained System Level Synthesis on the GPU
Jeffrey Fang, Glen Chou
We present GPU-SLS, a GPU-parallelized framework for safe, robust nonlinear model predictive control (MPC) that scales to high-dimensional uncertain robotic systems and long planni…