Estimating the location of people using a network of sensors placed throughout an environment is a fundamental challenge in smart environments and ubiquitous computing. Id-sensors...
This article introduces a scheme for clustering complex and linearly non-separable datasets, without any prior knowledge of the number of naturally occurring groups in the data. T...
Abstract— Particle filters are a frequently used filtering technique in the robotics community. They have been successfully applied to problems such as localization, mapping, o...
Cyrill Stachniss, Giorgio Grisetti, Wolfram Burgar...
This paper introduces a method for clustering complex and linearly non-separable datasets, without any prior knowledge of the number of naturally occurring clusters. The proposed ...
– In Bayesian based approaches to mobile robot simultaneous localization and mapping, Rao-Blackwellized particle filters (RBPF) enable the efficient estimation of the posterior b...