News Feed

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ORI is recruiting!

ORI is growing and we are looking to appoint a PostDoctoral Research Assistant and a Junior Systems Administrator.  See our Jobs page for more details.  

Legged Robots at ORI

  ORI is starting a major new research direction into legged robots. Drs. Ioannis Havoutis and Maurice Fallon have recently joined as academic staff with research expertise in control, planning and state estimation on dynamic walking robots such as the IIT Hydraulic Quadruped and the Boston Dynamics Atlas. Below are upcoming papers in this research [...]

Mapping the city

We used a NABU sensor attached to a street sweeper to map the streets of Oxford, in an innovative data gathering project which will help the City Council to plan and manage its services.  Read the Council's Press Release here:   PRESS RELEASE 11 March 2017 Innovative new city mapping could transform council services A [...]

CDT Week 2017

        Ten of Oxford’s AIMS (Autonomous Intelligent Machines and Systems) CDT students joined us for our annual robotics challenge.  Divided into three teams, the students had to programme a Husky robot to work its way around obstacles to reach a goal.   There was some careful planning.            

Mobile Autonomy Workshop

    “The machines are coming and it's going to be good ... it all comes together in a glorious bit of robotics science."   "In this talk I pull apart some of the competencies needed to build “intelligent” self driving vehicles. I’ll explain what makes it hard, what makes it exciting and how it [...]

Boldness in Business Awards 2017

Graeme Smith, CEO, Oxbotica receives their Boldness in Business Award from Lionel Barber and Lakshmi Mittal. Oxbotica wins the Boldness in Business award in the smaller company category, amidst tough competition from the other shortlisted companies, depicted here...

ORI wins best student paper award at IROS

Congratulations to Markus Wulfmeier, Dominic Wang and Ingmar Posner on winning the best student paper award for their work on Deep IRL: Watch This: Scalable Cost-Function Learning for Path Planning in Urban Environments - an approach to learning cost maps for driving in complex urban environments.  The authors used an ambitious dataset collected over the course of a year [...]