Jeeseop Kim

Reasoning Uncertainty and Safety

Uncertainty and Safety are the imporant considerations when deploying robots in human-centered environments. While both are critical issues that need to be addressed, they involve countless parameters to model. To overcome this limitation, this thread focuses on employing various data-driven methods, including learning frameworks, to address inevitable uncertainties and ensure critical safety during system deployment.

Research Aims

Research thread aims at developing systematic reasoning to address uncertainty and ensure critical safety when operating the robots.