Human SLAM, Indoor localization using particle filters

A key problem (or challenge) within smart spaces is indoor localization: making estimates of users’ whereabouts. Without such information, systems are unable to react on the presence of users or, sometimes even more important, their absence. This can range from simply turning the lights on when someone enters a room to customizing the way devices interact with a specific user. Even more important for a system to know where users exactly are, is to know where users are relative to the devices it can control or use to sense the environment....

Diving in into the Model with GPy

Lately we looked at GPy using some simple examples. Now we’ll dive deeper and look more closely to the inner workings of models. We’ll start with the basics and continue further by decomposing the Guassian Process Latent Variable model (GPLVM). Note: This post is fairly specific to GPy and the chosen model. Investigating parameters All GPy models extend the Parameterized class. This base class gives us several useful functions for interacting with the model parameters....

First steps with GPy

A random process, a collection of random variables, is said to be a Gaussian process (GP)1 if any finite number of these variables have a joint Gaussian distribution; i.e. the relation between variables follows a Gaussian distribution, this says something about the smoothness of functions generated by these processes. Guassian processes are used for many tasks in machine learning; from classification to regression and latent variable models. A lot of work on this subject is done by the machine learning group at the University of Sheffield which maintain and develop the GPy package: a framework, written in python, for GP’s....

Simple WSN Simulation with Matplotlib Animations

My internship and thesis revolves around WSNs: Wireless Sensor Networks. To get some more insights in the workings of these networks and I built a small simulator in Python. The full source can be found on the SLACTest1 repository on GitHub. The setup of the simulation is simple: a fixed world (without obstructions) contains a set of nodes. A subset of these nodes are fixed (i.e. Access Points or AP’s) and the rest is moving (e....