82 citations · 229 across the 29 of their papers we have counts for
6 papers · 1 filter
Iterative Tuning of Nonlinear Model Predictive Control for Robotic Manufacturing Tasks
Deepak Ingole, Valentin Bhend, Shiva Ganesh Murali +2
Manufacturing processes are often perturbed by drifts in the environment and wear in the system, requiring control re-tuning even in the presence of repetitive operations. This pap…
Differentiable Material Point Method for the Control of Deformable Objects
Diego Bolliger, Gabriele Fadini, Markus Bambach +1
Controlling the deformation of flexible objects is challenging due to their non-linear dynamics and high-dimensional configuration space. This work presents a differentiable Materi…
Bayesian Optimization for Automatic Tuning of Torque-Level Nonlinear Model Predictive Control
Gabriele Fadini, Deepak Ingole, Tong Duy Son +1
This paper presents an auto-tuning framework for torque-based Nonlinear Model Predictive Control (nMPC), where the MPC serves as a real-time controller for optimal joint torque com…
Guided Multi-Fidelity Bayesian Optimization for Data-driven Controller Tuning with Digital Twins
Mahdi Nobar, Jürg Keller, Alessandro Forino +2
We propose a \textit{guided multi-fidelity Bayesian optimization} framework for data-efficient controller tuning that integrates corrected digital twin simulations with real-world…
Learning from Simulation, Racing in Reality
Eugenio Chisari, Alexander Liniger, Alisa Rupenyan +2
We present a reinforcement learning-based solution to autonomously race on a miniature race car platform. We show that a policy that is trained purely in simulation using a relativ…
Optimization-Based Hierarchical Motion Planning for Autonomous Racing
José L. Vázquez, Marius Brühlmeier, Alexander Liniger +2
In this paper we propose a hierarchical controller for autonomous racing where the same vehicle model is used in a two level optimization framework for motion planning. The high-le…