4 papers · 1 filter
AC-DC: Adaptive Communication for Scalable Dynamic Average Consensus in Multi-Robot Ergodic Search
Robin Inho Kee, Begum Cannataro, Vasileios Tzoumas
We study scalable peer-to-peer dynamic average consensus (DC) for multi-robot systems under finite-range, finite-rate, and interference-constrained communication. We introduce Adap…
Learning to Adapt Control Barrier Functions Under Epistemic and Aleatoric Uncertainty
Taekyung Kim, Robin Inho Kee, Dimitra Panagou
Control barrier functions (CBFs) provide a tractable mechanism for enforcing safety constraints in robotic systems, but their practical performance depends strongly on the choice o…
Vision-Ultrasound Robotic System based on Deep Learning for Gas and Arc Hazard Detection in Manufacturing
Jin-Hee Lee, Dahyun Nam, Robin Inho Kee +2
Gas leaks and arc discharges present significant risks in industrial environments, requiring robust detection systems to ensure safety and operational efficiency. Inspired by human…
Learning to Refine Input Constrained Control Barrier Functions via Uncertainty-Aware Online Parameter Adaptation
Taekyung Kim, Robin Inho Kee, Dimitra Panagou
Control Barrier Functions (CBFs) have become powerful tools for ensuring safety in nonlinear systems. However, finding valid CBFs that guarantee persistent safety and feasibility r…