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cs.RO2026
Fine-Tuning of Neural Network Approximate MPC without Retraining via Bayesian Optimization
Henrik Hose, Paul Brunzema, Alexander von Rohr +3
Approximate model-predictive control (AMPC) aims to imitate an MPC's behavior with a neural network, removing the need to solve an expensive optimization problem at runtime. Howeve…
cs.RO2024★ 1 cited
Simulation-Aided Policy Tuning for Black-Box Robot Learning
Shiming He, Alexander von Rohr, Dominik Baumann +2
How can robots learn and adapt to new tasks and situations with little data? Systematic exploration and simulation are crucial tools for efficient robot learning. We present a nove…