Autonomy, Simulation and Networks

autonomous systems research

Our Autonomy, Simulation and Networks research falls into multiple themes including Autonomous Systems, Big Data, Information Computing Technologies, Modelling, Network Science and Technology, and Sensors. Several of these can be explored below:

Autonomous Systems

Autonomy is at the core of modern complex systems as, increasingly, these systems are required to decide for themselves what to do and when to do it. Such decisions are left to the systems when direct human control becomes infeasible (since the environments are too distant or dangerous), impossible (since humans are not capable of reacting quickly enough), or too expensive.

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Academic Lead: Professor Michael Fisher

Autonomous systems now extend well beyond the traditional area of robotics, covering unmanned vehicles and robots, sensor networks, medical devices, intelligent buildings, smarter cities and applications that can operate without human control and make crucial decisions.

These technologies have the potential to revolutionise society by offering great benefits, replacing humans in tasks that are mundane, dangerous and dirty, or detailed and precise. They also have potential in allowing the remote performance of various functions, from farming or construction, to monitoring the ill or housebound.

Consequently, the study of autonomy and its use in controlling complex software and hardware systems is vital to its safe, reliable, and effective exploitation.

Key Centres and Facilities

The Centre for Autonomous Systems (CAST) brings together experts from a wide range of disciplines, from Computer Science, Electrical Engineering & Electronics and Engineering to Law, Philosophy, Psychology and Environmental Sciences.

Its core focus is on software autonomy, verification, agreement technologies, reliability and safety, autonomous sensors, communications, data fusion, machine learning, vehicle dynamics, and aerospace and robotics applications. But activity spreads beyond these technological aspects, for example to regulation and compliance of autonomous vehicles, critical decision-making and social robotics, and machine ethics.

The Centre comprises a range of expertise developing practical autonomous systems spanning across industrial, military, healthcare and environmental areas and involving a rich network of collaborations. The Virtual Engineering Centre is the principal conduit for this interaction with external organisations.

Big Data

Being able to analyse large datasets and capture value from doing so will become of vital importance to business, underpinning new waves of productivity, operational efficiency, innovation and growth. But it will also benefit society in ways as diverse as preventing pandemics and running government services more efficiently.

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Academic Lead: Professor Simon Maskell

The University has relevant strengths in various disciplines, ranging from electrical engineering and computer science to biostatistics, physics, sociology, psychology, ethics and geography.

By sharing expertise and best practice, underpinned by a strong technological base, we can develop solutions that can be rapidly applied by industry and government. We also have access to Sci-Tech Daresbury, one of the world’s leading centres for high-performance computing, as well the modelling and simulation facilities of the Virtual Engineering Centre.

This puts us in the ideal place for these cross-fertilisations of ideas to happen, fostering connections between research expertise, technologies and facilities that might not have existed before, and enabling us to embrace innovation to the benefit of the UK.

Find out about our MSc in Big Data

Modelling

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Modelling research is concerned with embedding the physical and chemical processes into a numerical simulation package to predict the performance of devices which generate electrical plasmas for processing materials, interrupting fault current etc. The physics and chemistry is encoded into bespoke software and embedded into computational fluid dynamics (CFD) software. Simulations are in 2 and 3D and are validated with experimental results. We have produced software packages to reduce the development time for new products and are being used by multi-national companies. Our high capacity computing facilities support this type of research. The Virtual Engineering Centre is the principal conduit for this interaction with external organisations.

Network Science and Technology

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Academic Lead: Professor Paul Spirakis

Networks are naturally embedded in biological, chemical, physical and digital systems, the economy, social relationships and many human-made complex structures such as the Internet. A network-based approach to modelling, understanding and processing surrounding environments has a strong foundation in mathematical and computational sciences and has a strong history of research in electrical engineering.

Companies are forming relationships with many different groups, often creating complex networks and connections that aren’t always visible to the organisation. Science and technology are continuously developing to respond to this trend, enabling the creation, identification, mapping and analysis of networks, including how to make them more effective and profitable.

Tapping into our knowledge and expertise can provide these companies with a better understanding of who they are connected with and how to link with these networks with the aim to, ultimately, identify and utilise sales opportunities and to increase their efficiency and business performance.

Key Facilities and Centres

The Centre for Networks Sciences and Technologies (NeST) provides a vehicle for advancing science and stimulates applications of foundational research in network sciences and technologies.

Apart from high-quality, foundational research explorations, the Centre will target knowledge exchange, including interdisciplinary research activities that will involve academics from our University, partnering institutions in the UK and overseas, industry and members of the public.