Machine Learning and Robotics Group (MLAIR)

A project with the law firm Moorcrofts LLP is funded by InnovateUK with £284.000. 

The group contributed machine learning and natural language processing solutions for contract law analysis. 

The commercial outcome is ContrAI, a smart contract management suit in which AI helps to identify important clauses in contracts to make their processing better and more cost-effective. 

A Knowledge Transfer Partnership with UNESCO World Heritage site Blenheim Palace funded by InnovateUK with a total worth of £260.000. 

The project makes use of AI and machine learning for smart visitor management and flow prediction, and is done in collaboration with the Oxford Brookes Business School.

A main research focus of the group is efficient motor learning with Goal Babbling, which was initially described by Rolf, Steil, and Gienger in 2010. 

Recent experiments include:

• a research student project on learning aimed-throwing skills (MSc by Research, Jamie Pierce, 2020)
• a collaboration with the Humanoid and Cognitive Robotics group at CTU Prague investigating the learning of tactile body models by means of goal babbling (Gama, Shcherban, Rolf, Hoffman, 2020 & 2021).

The group is pioneering novel methods to make reinforcement learning intuitive and safe by means of multi-objective learning. 

The new MORE method allows for a balanced achievement of multiple objectives (Rolf, 2020) as well as an effective prioritization of needs when necessary (Al-Husaini & Rolf, 2021, PhD project Yusuf Al-Husaini).

A key research area of the group, and frequent application context of the machine learning methods is autonomous decision making in moral contexts. 

An ongoing PhD project by Rebecca Raper investigates learning architectures for autonomous moral agents. 

A particular focus is the formation of social norms (Matthew Wilson), as well as particular social norms in the context of robotic applications such as proxemics (Vaswani Bhavnani & Rolf, 2020). 

This Innovate UK-funded ABLE DOC project, led by Cognitant Group had OBU and Hospital Universitario San Ignacio, Colombia as partners. The project aim was to improve the self-management of health among people with diabetes in Colombia. This was achieved by conducting a human-centred design study to evaluate the potential of an avatar-based educational programme to improve awareness and understanding of the condition, the effects of treatment, and strategies for effective management of blood-glucose control. The OBU team was responsible for interdisciplinary research to understand whether an AI system could potentially recommend training material by analysing blood glucose patterns.

Research impact:

The 2016 OECD review of Colombia’s health system emphasises the strategy of prevention and treatment of non-communicable diseases such as diabetes. The outputs from the ABLE DOC project could have an enormous social impact since improving the self-management of patients can only lead to better glycaemic control and improvement in quality of life.

This project was funded by the Academy of Medical Sciences and was a partnership between OBU and Universidad Antonio Nariño, Colombia. The aim of the project was to explore the feasibility of a cloud-based platform for diabetes management and research. It focused on the specific needs in the Colombian population and considered the potential for embedding AI within an open source cloud-based platform. The work has led to the development of a bespoke Spanish language platform (CLOUDI) that is currently been evaluated in a large-scale clinical study.

Research impact:

Although cloud-monitoring is already an integral part of clinical management, there is no platform that takes into account the specific needs in Colombia. The platform could be made widely accessible in order to create impact and benefit to Colombian society.