Mobile Robotics Group
The original group in what is now the ORI, the Mobile Robotics Group is about building robots and systems which answer “where am I and what surrounds me?” On real vehicles in real-hard places.
It has a proud systems heritage, taking on ambitious field deployments which shine a light on what doesn’t work and has to be fixed by smart application of machine learning, AI and robotics expertise.
MRG has been running since 2005. Its focus is and has always been on hard problems in mobile robotics. In its early days it worked on large scale SLAM and derivative problems. In the 2010’s it worked on large scale localisation techniques using vision and laser. It built and ran large scale autonomous systems and in 2014 it ran the UK’s first Autonomous Vehicle on public roads. That vehicle is now with the National Science Museum and the group’s attention has moved onto the next set of hard problems.
RT @d_d_martini: Here is a brief clip of our teleoperation test from last week @UofGSciEng with @GuodongZhao4 and his team! The @clearpathr…
RT @d_d_martini: Great week spent @UofGSciEng working with @GuodongZhao4 and his team. The first trial of pure-#5G teleoperation of a @clea…
RT @TarlanS: A quick tour in #Oxford city centre from @MansfieldOxford to @KebleOxford via @TrinityOxford ...or part of the video collage…
RT @mtt_gdd: https://t.co/v7hRZ8vLDZ a collage of scenery and annotations from our #robotcar #RoadBoundary dataset @TarlanS @MRG_Oxford @…
RT @kula78: Following in the footsteps of James Bond (@007) - Our research vehicle in the #ScottishHighlands as part of the Sense-Assess-eX…
RT @oxfordrobots: @MRG_Oxford @TarlanS 'Oxford Road Boundaries Dataset' presentation for the 3D-DLAD workshop #IV21. The research is desi…
[2/2] First solution of BOTH lidar place recognition and metric localisation using only publicly available overhead imagery - no prior maps -expressing overhead imagery a 2D point collection, allowing for cross-modal comparison with range sensors [video] https://t.co/tvMfVQtwqs
[1/2] How can we solve outdoor lidar localisation without a prior sensor map? See our recent paper by @TimYQTang: "Get to the Point: Learning Lidar Place Recognition and Metric Localisation Using Overhead Imagery", upcoming at @RoboticsSciSys'21 [paper] https://t.co/4x11YulDF1
