State estimation consists of updating an agent’s belief given executed actions and observed evidence to date. In single agent environments, the state estimation can be formalize...
— Location tracking in wireless networks has many applications, including enhanced network performance. In this work we investigate the experimental use of “particle filter”...
Particle filters are used extensively for tracking the state of non-linear dynamic systems. This paper presents a new particle filter that maintains samples in the state space a...
We describe a novel method whereby a particle filter is used to create a potential field for robot control without prior clustering. We show an application of this technique to ...
Abstract— Bayesian filtering is a general framework for recursively estimating the state of a dynamical system. The most common instantiations of Bayes filters are Kalman filt...