Reconfigurable Autonomy

Lead Research Organisation: University of Liverpool
Department Name: Computer Science


As computational and engineering applications become more sophisticated, the need for autonomous systems that can act intelligently without direct human intervention increases. Yet the autonomous control at the heart of many such systems is often ad-hoc and opaque. Since the cost of failure in critical systems is high, a more reliable, understandable and consistent approach is needed. Thus, in this project we aim to provide a rational agent architecture that controls autonomous decision-making, is re-usable and generic, and can be configured for many different autonomous platforms. In partnership with the industrial collaborators we aim to show how such "reconfigurable autonomy" can be achieved in relevant applications.

Planned Impact

Regardless of any industrial sponsorship for this Call, there is a clear industrial need for this technology. Industries involved in developing robotics, autonomous vehicles, or remote exploration systems will be interested in our developments. Yet the generic architecture potentially extends beyond these, more obvious, areas to any autonomous system that must intelligently deal with a stochastic, continuous environment. This then can cover very many software, embedded, pervasive, or autonomic systems. So, to industry, the proposed approach (if demonstrated successfully) can help to reduce future autonomy software and system development costs (including speeding up the development process).

The development of a generic, yet reconfigurable, core for autonomous systems will bring many potential benefits to academic and industrial researchers:

* improved reliability;
* cost-effective re-use;
* applicability of solutions to wider areas;
* improved clarity and user interaction; and, potentially,
* reduced vulnerabilities.

Clearly, we will collaborate with academics and the industrial sponsors of this Call in order to explore some of these advantages. Through our wider network of industrial collaborators, we will also target more general exploitation within the broad area of autonomous systems.


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Aitken J (2018) Autonomous Nuclear Waste Management in IEEE Intelligent Systems

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Aitken J (2018) Autonomous Nuclear Waste Management in IEEE Intelligent Systems

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Dennis L (2016) Formal verification of ethical choices in autonomous systems in Robotics and Autonomous Systems

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Dennis L (2014) Reconfigurable Autonomy in KI - Künstliche Intelligenz

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Dennis L (2018) Two-stage agent program verification in Journal of Logic and Computation

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Fisher M (2015) Misplaced Trust? in Engineering & Technology Reference

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Fisher Michael (2013) Verifying Autonomous Systems in COMMUNICATIONS OF THE ACM

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Patchett C (2015) Safety and Certification of Unmanned Air Systems in Engineering & Technology Reference

Description Research carried out on this "Reconfigurable Autonomy" project provided an architecture for incorporating vision, control, and reliable decision-making, in order to provide effective autonomous systems. This collaboration brought together expertise in autonomy from the University of Liverpool, on control from the University of Sheffield, and on vision from the Universty of Surrey. This work successfully produced and demonstrated new autonomous system technologies that are highly suitable for nuclear waste processing, hence the collaboration with industrial partners Sellafield and National Nuclear Laboratories.

The second key research advance concerns the theory, development and demonstration of sophisticated "reconfigurability". Here, the autonomous system is not only self-aware but can autonomously make decisions to recover from problems. This is essential in either extreme environments, where human operatives cannot easily venture, or in facilities working 24/7, where human operatives cannot be expected to be onsite at all times. Nuclear waste processing scenarios actually involve both of these aspects.
Exploitation Route When demonstrator provided at NNL Workington, there is potential for other stakeholders to utilise apprach.
Sectors Digital/Communication/Information Technologies (including Software),Energy,Other

Description Sellafield Ltd (and their government partner, National Nuclear Laboratories [NNL]) are looking for efficient, safe, and flexible ways to dismantle, manipulate, sort, and package nuclear facilities and equipment that are past their operational life. Nuclear waste processing experience has demonstrated that there is an urgent need to integrate novel automation methods in these processes. For the nuclear industry to fully benefit from our recent advances, the technology requires further TRL progression. By using a full-scale industrial waste processing facility now being developed at NNL Workington, the costs and time scales for such TRL progression can be minimized. We have begun working with both Sellafield and NNL to introduce autonomous robots into this area that has previously been totally human controlled. Through Impact Acceleration funding we are in the process of developing a demonstrator of research produced within the "Reconfigurable Autonomy" project and are beginning to port it to the NNL's new facility at Workington. We are also involved in discussion regarding Sellafield's future robotics strategy and potential routes to further exploitation.
First Year Of Impact 2016
Sector Energy,Environment
Impact Types Economic

Description Britis Standards Institution: Robot Safety and Robot Ethics
Geographic Reach National 
Policy Influence Type Membership of a guideline committee
Description Demonstrating Automated Nuclear Waste Processing
Amount £20,000 (GBP)
Organisation University of Liverpool 
Sector Academic/University
Country United Kingdom
Start 09/2016 
End 03/2017
Description Network on the Verification and Validation of Autonomous Systems
Amount £107,725 (GBP)
Funding ID EP/M027309/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Academic/University
Country United Kingdom
Start 08/2015 
End 08/2018
Description Nuclear regulation/certification 
Organisation Department for Work and Pensions
Department Office for Nuclear Regulation
Country United Kingdom 
Sector Public 
PI Contribution Initial series of meetings.
Collaborator Contribution Initial series of meetings.
Impact Collaboration between Univ. Liverpool, ONR and RACE (Culham Fusion) looking at future regulation for nuclear robotics.
Start Year 2017
Description Robots at Tate Liverpool 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Public/other audiences
Results and Impact From Summer 2016 to Spring 2017 we worked with the artist Cecile B. Evans to produce an exhibit comprising robotic performances. This was hosted by the Tate Gallery at Liverpool and currently has had over 130,000 visitors.

In addition to the exhibit, involving 2 humanoid robots, a robot dog, and many videos, we held a talk/workshop at which the artist and Prof. Fisher engaged with members of the public about both the exhibit and about future developments. See:
Year(s) Of Engagement Activity 2016,2017