Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold...
— In nature, animal groups achieve robustness and scalability with each individual executes a simple and adaptive strategy. Inspired by this phenomenon, we propose a decentralize...
The distribution of data in large dynamic wireless sensor networks presents a difficult problem due to node mobility, link failures, and traffic congestion. In this paper, we pr...
David Dorsey, Bjorn Jay Carandang, Moshe Kam, Chri...
Abstract— Human-robot collaboration requires both communicative and decision making skills of a robot. To enable flexible coordination and turn-taking between human users and a ...
— We propose a novel control framework for bilateral teleoperation of a pair of multi-degree-of-freedom (DOF) nonlinear robotic systems under constant communication delays. The p...