Applications are now OPEN for 2023 graduate access programmes at Oxford.
Explore UNIQ+, our paid research internship programme for UK students from under-represented and disadvantaged backgrounds. Apply by 17 February to join us this summer: http://ox.ac.uk/uniqplus
The RTI’s project in UNIQ+
Data recorders for social robots
Professor Marina Jirotka
To improve robot safety and trust, robots should be equipped with a standard device which continuously records a time stamped log of the internal state of the system, key decisions, and sampled input or sensor data. In effect this is the robot equivalent of an aircraft flight data recorder (aka black box). Without such a device, finding out what the robot was doing and why in the moments leading up to an accident, is more or less impossible. However, it is not the black box on its own, that forms the safety and trust mechanism; it is its inclusion within a social process of accident/incident investigation. An investigation will draw on data recorder information and information from human witnesses and experts to determine the reason for an accident – and lessons to be learnt from it. This project aims to develop and demonstrate both technologies and processes (and ultimately policy recommendations) for robot accident investigation.
Participants will be involved in interdisciplinary activities concerning the design, development and enactment of a robot related accident scenario and investigation, which will be conducted in the framework of the EPSRC funded project RoboTIPS. They will participate in the design of the scenario, conducting online research and stakeholders’ interviews to define a meaningful robot accident scenario; they will participate in the technical implementation of the EBB on the robot selected for the accident, by collaborating with the RoboTIPS project engineers; they will participate in the enactment of the scenario, by playing roles during the mock accident investigation process; and finally they will collaborate with researchers on the data collection and analysis, by conducting qualitative and quantitative analysis.
None. Preferable: Knowledge/ prior education in computer science, robotics, law, social sciences, possibly performing arts.
This internship may be funded by an external partner and may in this case be offered for either seven weeks or for an extended duration of ten weeks with an associated scholarship stipend of £4,200. If you express an interest for this project in the application form, you will be asked to confirm if you can undertake the internship for seven weeks only, or seven weeks or ten weeks.
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