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Details of Grant 

EPSRC Reference: EP/L015897/1
Title: EPSRC Centre for Doctoral Training in Autonomous Intelligent Machines and Systems (AIMS)
Principal Investigator: Osborne, Dr M A
Other Investigators:
Researcher Co-Investigators:
Project Partners:
ABB Group Ascending Technologies GmbH BAE Systems
BP Google Honeywell
InfoSys Technologies Ltd Microsoft QinetiQ
Schlumberger Xerox YouGov
Department: Engineering Science
Organisation: University of Oxford
Scheme: Centre for Doctoral Training
Starts: 01 April 2014 Ends: 30 September 2023 Value (£): 4,597,032
EPSRC Research Topic Classifications:
Artificial Intelligence Image & Vision Computing
Robotics & Autonomy
EPSRC Industrial Sector Classifications:
Electronics Information Technologies
Transport Systems and Vehicles
Related Grants:
Panel History:
Panel DatePanel NameOutcome
23 Oct 2013 EPSRC CDT 2013 Interviews Panel K Announced
Summary on Grant Application Form
In the next decade our economy and society will be revolutionised by ubiquitous Autonomous, Intelligent Machines and Systems, which can learn, adapt, take decisions and act independently of human control. They will work for us and beside us, assist us, and interact and communicate with us. The UK has the opportunity to become a world-leader in developing these technologies for sectors as diverse as energy, transport, environment, manufacturing and aerospace. This CDT directly addresses the present need to train future leaders capable of accelerating innovation in autonomy, and promoting it to some of the UK's largest sectors. This requirement can be met by cohorts of highly-trained individuals versed in the underpinning sciences of robotics, embedded systems, machine learning, wireless networks, control, computer vision, statistics & data analysis, design and verification. These disciplines are intimately related via the application and development of mathematical models and techniques implemented on computers to make predictions, take optimal decisions, perform inference and actions that are robust in the face of uncertainties at all levels. The synthesis of a range of disciplines is absolutely essential to train individuals in all aspects of autonomy, who will then be able to credibly communicate with large technical teams, and pioneer disruptive technologies into industrial labs. This CDT is focused on student training in algorithms, devices, and data feeds inherent to autonomous, intelligent machines & systems. To create and understand these complex systems, students need to be trained to program, embed and design software, to implement established and novel algorithms efficiently and correctly and to develop and apply models and decompositions which lie at the core of approaches to control, communicate, learn from, interpret and distil the large volumes of data endemic to autonomous systems. We believe that for a training centre to achieve its full potential in the AIMS area, it must recognise and respond to the synthesis of a number of component technologies. Students belonging to this CDT will be trained in both the fundamentals of autonomous systems engineering and the latest approaches and perspectives.

The UK is faced with an increasing technology skills shortage, with a recent (2012) large-scale survey reporting that half of all key UK industries surveyed suffer from a worsening skills shortage (net.org.uk/news, June 2012). This is even more acute in high-tech industry and requires core investment in teaching highly-qualified cohorts. More specifically, the commercial potential of Autonomous Systems for the UK is tremendous, as demonstrated by the recent AAD KTN (Aerospace, Aviation & Defence Knowledge Transfer Network) study. Their research indicates "an untapped short term market value of circa £7bn per annum just for relatively low level autonomy products and services". Developing skills in designing and deploying autonomous systems will offer significant opportunities for growth to high priority sectors, as diverse as manufacturing, energy, smart buildings, intelligent transport systems, and defence. These sectors are in need of rapid change to reach targets of national importance, while still being able to compete in the global market. One of the main targets is the reduction of greenhouse gas emission (by 80% by 2050), which calls for energy-aware autonomous systems to become a cross-cutting technology in our society. Another driver of change is the growing and ageing population, which advocates the need for autonomous telecare, transport, efficient usage of public/private infrastructure, safety and security. Changing demographics, combined with strict emissions targets and budget cuts, raise unique challenges and opportunities for revolutionising key UK sectors.

Key Findings
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