From rats to robot navigation and beyond

Abstract: The brain circuitry involved in encoding space in rodents has been extensively tested over the past forty years, with an ever increasing body of knowledge about the components and wiring involved in navigation tasks. The learning and recall of spatial features is known to take place in and around the hippocampus of the rodent, where there is clear evidence of cells that encode the rodent's position and heading. RatSLAM is a primarily vision-based robotic navigation system based on current models of the rodent hippocampus, which has achieved several significant outcomes in vision-based Simultaneous Localization And Mapping (SLAM), including mapping of an entire suburb using only a low cost webcam, and navigation continuously over a period of two weeks in a delivery robot experiment. This research led to recent experiments demonstrating that impressive feats of vision-based navigation can be achieved at any time of day or night, during any weather, and in any season using visual images as small as 2 pixels in size. In our current research we are investigating the problem of place recognition and visual navigation from two angles. The first is from a neuroscience-inspired perspective, modelling the multi-scale neuronal map of space found in the mammalian brain and the variably tolerant and selective visual recognition process in the primate and human brain. The second is from an algorithmic perspective, utilizing state of the art deep learning techniques. I will discuss the insights from this research, as well as current and future areas of study with the aim of stimulating discussion and collaboration.

Bio: I hold a PhD in Electrical Engineering and a Bachelor of Mechanical and Space Engineering from the University of Queensland (UQ), awarded in 2006 and 2002 respectively. After a brief postdoc in robotics at UQ, I worked for three years at the Queensland Brain Institute as a Research Fellow on the Thinking Systems Project. In 2010 I moved to the Queensland University of Technology (QUT) to finish off my Thinking Systems postdoc, and then was appointed as a Lecturer in 2011. In 2012 I was awarded an inaugural Australian Research Council Discovery Early Career Researcher Award, which provides me with a research-intensive fellowship salary and extra funding support for 3 years. In 2013 I became a Microsoft Faculty Fellow and lived in Boston on sabbatical working with Harvard and Boston University. I am currently a Senior Lecturer and Australian Research Council Future Fellow at QUT with a research focus, although I continue to teach Introduction to Robotics every year. From 2014 to 2020 I am a Chief Investigator on a $19,000,000 Australian Research Council Centre of Excellence for Robotic Vision.

My research interests include vision-based mapping and navigation, computational modelling of the rodent hippocampus and entorhinal cortex, especially with respect to mapping and navigation, computational modelling of human visual recognition, biologically inspired robot navigation and computer vision and Simultaneous Localisation And Mapping (SLAM).

Friday, 17 April, 2015 - 13:30 to Saturday, 18 April, 2015 - 16:45
Michael Milford
Queensland University
EM.183 Earl Mountbatten Building, Heriot-Watt University, EH14 4AS