10 citations · 12 across the 5 of their papers we have counts for
5 papers
Exploiting Differential Flatness for Efficient Learning-based Model Predictive Control of Constrained Multi-Input Control Affine Systems
Tobias A. Farger, Adam W. Hall, Angela P. Schoellig
Learning-based control techniques use data from past trajectories to control systems with uncertain dynamics. However, learning-based controllers are often computationally ineffici…
What is the Impact of Releasing Code with Publications? Statistics from the Machine Learning, Robotics, and Control Communities
Siqi Zhou, Lukas Brunke, Allen Tao +4
Open-sourcing research publications is a key enabler for the reproducibility of studies and the collective scientific progress of a research community. As all fields of science dev…
Differentially Flat Learning-based Model Predictive Control Using a Stability, State, and Input Constraining Safety Filter
Adam W. Hall, Melissa Greeff, Angela P. Schoellig
Learning-based optimal control algorithms control unknown systems using past trajectory data and a learned model of the system dynamics. These controllers use either a linear appro…
safe-control-gym: a Unified Benchmark Suite for Safe Learning-based Control and Reinforcement Learning in Robotics
Zhaocong Yuan, Adam W. Hall, Siqi Zhou +4
In recent years, both reinforcement learning and learning-based control -- as well as the study of their safety, which is crucial for deployment in real-world robots -- have gained…
Safe Learning in Robotics: From Learning-Based Control to Safe Reinforcement Learning
Lukas Brunke, Melissa Greeff, Adam W. Hall +4
The last half-decade has seen a steep rise in the number of contributions on safe learning methods for real-world robotic deployments from both the control and reinforcement learni…