5 papers · 1 filter
SQ-CBF: Signed Distance Functions for Numerically Stable Superquadric-Based Safety Filtering
Haocheng Zhao, Lukas Brunke, Oliver Lagerquist +2
Ensuring safe robot operation in cluttered and dynamic environments remains a fundamental challenge. While control barrier functions provide an effective framework for real-time sa…
Where Did I Leave My Glasses? Open-Vocabulary Semantic Exploration in Real-World Semi-Static Environments
Benjamin Bogenberger, Oliver Harrison, Orrin Dahanaggamaarachchi +4
Robots deployed in real-world environments, such as homes, must not only navigate safely but also understand their surroundings and adapt to changes in the environment. To perform…
Improving Drone Racing Performance Through Iterative Learning MPC
Haocheng Zhao, Niklas Schlüter, Lukas Brunke +1
Autonomous drone racing presents a challenging control problem, requiring real-time decision-making and robust handling of nonlinear system dynamics. While iterative learning model…
Semantically Safe Robot Manipulation: From Semantic Scene Understanding to Motion Safeguards
Lukas Brunke, Yanni Zhang, Ralf Römer +4
Ensuring safe interactions in human-centric environments requires robots to understand and adhere to constraints recognized by humans as "common sense" (e.g., "moving a cup of wate…
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…