We develop a novel localization theory for planar networks of nodes that measure each other’s relative position, i.e., we assume that nodes do not have the ability to perform me...
Giulia Piova, Iman Shames, Baris Fidan, Francesco ...
Abstract— Learning inverse kinematics has long been fascinating the robot learning community. While humans acquire this transformation to complicated tool spaces with ease, it is...
— In this paper we investigate the usage of persistent point feature histograms for the problem of aligning point cloud data views into a consistent global model. Given a collect...
Radu Bogdan Rusu, Nico Blodow, Zoltan Csaba Marton...
—We present an iterative joint scheduling-routing algorithm for characterizing the long-term performance of a cellular-relaying network. The physical layer model is based on idea...
This paper analyzes the potential advantages and theoretical challenges of “active learning” algorithms. Active learning involves sequential sampling procedures that use infor...