The theory of compressive sampling involves making random linear projections of a signal. Provided signal is sparse in some basis, small number of such measurements preserves the ...
— This paper presents significant steps towards the online integration of 3D perception and manipulation for personal robotics applications. We propose a modular and distributed...
Radu Bogdan Rusu, Ioan Alexandru Sucan, Brian P. G...
— This paper describes a model-based probabilistic framework for tracking a fleet of laboratory-scale underwater vehicles using multiple fixed cameras. We model the target moti...
In this paper, we describe the design steps of extending LAOS, a five-layer framework for generic adaptive web learning authoring, by adding a social layer to capture (and adapt) i...
In this paper, we present a least square kernel machine with box constraints (LSKMBC). The existing least square machines assume Gaussian hyperpriors and subsequently express the ...