— In this paper we propose a SLAM framework which is based on an algorithm that combines an Unscented Particle Filter (UPF) and Unscented Kalman Filters (UKFs). A UPF is used to ...
In bio-medical domains there are many applications involving the modelling of multivariate time series (MTS) data. One area that has been largely overlooked so far is the particul...
Designing distributed controllers for self-reconfiguring modular robots has been consistently challenging. We have developed a reinforcement learning approach which can be used bo...
Despite voluminous previous research on adaptive compression, we found significant challenges when attempting to fully utilize both network bandwidth and CPU. We describe the Fine...
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...