Abstract

Abstract: The Speech Source Tracking (my PhD work) and Robotic Localisation and Mapping problems (my PostDoc work) have been characterized using a very similar probabilistic framework. Nonetheless the techniques used to solve the problems are strikingly different – as a result of the vastly different input sensor data. The first part of talk concerns speaker localization, detection and tracking using noisy recordings from low cost microphones. The approach taken utilizes Particle Filtering techniques drawn from the target tracking community. Meanwhile, robotic mapping is characterised by high-rate, high-quality ranging sensors on mobile autonomous platforms – in this case a robotic kayak where optimization and adjustment are more pressing issues. Results are presented for the vehicle exploring in a uncertain natural environment.

Biography: Maurice Fallon is a Research Scientist with Professor John Leonard’s Marine Robotics Group, in the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT . His current research is mainly concerned with Localization and Mapping for Autonomous Robotic Systems — particularly in Marine and Riverine settings.

He completed his PhD in the Signal Processing Group of the Department of Engineering in Cambridge University and was advised by Simon Godsill. Maurice is originally from Ireland, with his undergraduate studies at University College Dublin.