14 citations · 14 across the 5 of their papers we have counts for
5 papers
ProDapt: Proprioceptive Adaptation using Long-term Memory Diffusion
Federico Pizarro Bejarano, Bryson Jones, Daniel Pastor Moreno +3
Diffusion models have revolutionized imitation learning, allowing robots to replicate complex behaviours. However, diffusion often relies on cameras and other exteroceptive sensors…
Safety Filtering While Training: Improving the Performance and Sample Efficiency of Reinforcement Learning Agents
Federico Pizarro Bejarano, Lukas Brunke, Angela P. Schoellig
Reinforcement learning (RL) controllers are flexible and performant but rarely guarantee safety. Safety filters impart hard safety guarantees to RL controllers while maintaining fl…
Multi-Step Model Predictive Safety Filters: Reducing Chattering by Increasing the Prediction Horizon
Federico Pizarro Bejarano, Lukas Brunke, Angela P. Schoellig
Learning-based controllers have demonstrated superior performance compared to classical controllers in various tasks. However, providing safety guarantees is not trivial. Safety, t…
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…
Deep Reinforcement Learning for Decentralized Multi-Robot Exploration With Macro Actions
Aaron Hao Tan, Federico Pizarro Bejarano, Yuhan Zhu +2
Cooperative multi-robot teams need to be able to explore cluttered and unstructured environments while dealing with communication dropouts that prevent them from exchanging local i…