As embedded systems grow increasingly complex, there is a pressing need for diagnosing and monitoring capabilities that estimate the system state robustly. This paper is based on ...
Abstract--In the current environment of rapidly changing invehicle requirements and ever-increasing functional content for automotive EE systems, there are several sources of uncer...
Arkadeb Ghosal, Haibo Zeng, Marco Di Natale, Yakov...
This paper presents a probing-based method for probabilistic localization in automated robotic assembly. We consider peg-in-hole problems in which a needle-like peg has a single p...
Scene understanding is an important problem in intelligent robotics. Since visual information is uncertain due to several reasons, we need a novel method that has robustness to the...
The existence of good probabilistic models for the job arrival process and job characteristics is important for the improved understanding of grid systems and the prediction of th...
Michael Oikonomakos, Kostas Christodoulopoulos, Em...