We are not condemned to a future of congestion, accidents and time wasting. We will eventually have cars that can drive themselves, interacting safely with other road users and using roads efficiently, thus freeing up our precious time. But to do this the machines need life-long infrastructure-free navigation, and that, alongside autonomous perception, is a real focus of our work.
TICSync is an extremely efficient algorithm for learning the mapping between distributed clocks, which typically achieves better than millisecond accuracy ...Read More
Simple, open-source, cross-platform software for mobile robotics research. We use MOOS on all of our robots and applications including the ...Read More
FABMAP is an approach to topological appearance based SLAM. For an overview of the work (including papers and data sets) ...Read More
We have published a number of datasets. Under each heading you will find the associated paper, as well as links ...Read More
RobotCar is a modified Nissan LEAF. Lasers and cameras are subtly mounted around the vehicle and taking up some of ...Read More
Our approach We use the mathematics of probability and estimation to allow computers in robots to interpret data from sensors ...Read More
This work is about metric localisation across extreme lighting and weather conditions. The typical approach in robot vision is to ...Read More
This work is about extending the reach and endurance of outdoor localisation using stereo vision. At the heart of the ...Read More
This work addresses the challenging problem of vision-based pose estimation in busy and distracting urban environments. By leveraging laser-generated 3D ...Read More
This work addresses the difficult problem of navigation in changing, dynamic environments. Assuming the world is static in appearance results in brittle ...Read More
For downloadable photos and video please visit our online repository or visit our Media page.
Department of Engineering Science, University of Oxford