A little blast from the past here. Several years ago I built something very like a Google Street View car to gather data for my PhD thesis. At the time I wrote up a blog post about the experience, as a guide for anyone else who might want to build such a thing. But I never quite finished it. Upgrading WordPress today, I came across this old post sitting in my drafts folder from years ago, and decided to rescue it. So here it is. The making of a DIY StreetView car.
Today’s edition of the New Scientist news feed includes an article about my PhD research. How nice! They called the article ‘Chaos filter stops robots getting lost’. This is kind ofÂ a bizarre title – ‘chaos filter’ seems to be a term of their own invention :).Â Still, they mostly got things mostly right. I guess that’s journalism!
Whatever about the strange terminology, it’s great to see the research getting out there. It’s also nice to see the feedback from Robert Sim, who made a rather impressive vision-only robotic system with full autonomy a few years ago, still quite a rare accomplishment.
For anyone interested in the details of the system, have a look at my publications page. New Scientist’s description more or less resembles how our system works, but many of the specifics are a little wide of the mark. In particular, we’re not doing hierarchical clustering of visual words as the article describes – instead we learn a Bayesian network that captures the visual word co-occurrence statistics. This achieves a similar effect in that we implicitly learn about objects in the world, but with none of the hard decisions and awkward parameter tuning involved in clustering.
For the next week I’ll be at the International Conference on Robotics and Automation in Pasadena. For Monday and Tuesday I’m going to the Future of Visual Navigation workshop. For the main conference I’ll be presenting my paper “Accelerated Appearance-Only SLAM“, with some new ideas for very fast inference in our FAB-MAP framework. We’ve also just released the software.
If you’re at the conference, come say hi!