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Welcome to Repository@Nottingham

The Repository@Nottingham is intended to be an Open Access showcase for the published research output of the university. Whenever possible, refereed documents accepted for publication, or finished artistic compositions presented in public, will be made available here in full digital format, and hyperlinks to standard published versions will be provided. See our Policies for further information.



Latest Additions

Optimal sampling of dynamical large deviations in two dimensions via tensor networks (2023)
Journal Article
Causer, L., BaƱuls, M. C., & Garrahan, J. P. (in press). Optimal sampling of dynamical large deviations in two dimensions via tensor networks. Physical Review Letters,

We use projected entangled-pair states (PEPS) to calculate the large deviation statistics of the dynamical activity of the two dimensional East model, and the two dimensional symmetric simple exclusion process (SSEP) with open boundaries, in lattices... Read More about Optimal sampling of dynamical large deviations in two dimensions via tensor networks.

Ghost Busting: A Novel On-Road Exploration of External HMIs for Autonomous Vehicles (2023)
Conference Proceeding
Large, D., Hallewell, M., Li, X., Harvey, C., & Burnett, G. (in press). Ghost Busting: A Novel On-Road Exploration of External HMIs for Autonomous Vehicles.

The absence of a human driver in future autonomous vehicles means that explicit pedestrian-driver communication is not possible. Building on the novel ‘Ghost Driver’ methodology to emulate an autonomous vehicle, we developed prototype external human-... Read More about Ghost Busting: A Novel On-Road Exploration of External HMIs for Autonomous Vehicles.

A Neural Network Separation Approach for the Inclusion of Static Friction in Nonlinear Static Models of Industrial Robots (2023)
Journal Article
Khanesar, M. A., Yan, M., Syam, W. P., Piano, S., Leach, R., & Branson, D. (in press). A Neural Network Separation Approach for the Inclusion of Static Friction in Nonlinear Static Models of Industrial Robots. IEEE/ASME Transactions on Mechatronics,

Static friction modelling is a critical task to have an accurate robot model. In this paper, a neural network separation approach to include nonlinear static friction in models of industrial robots is proposed. For this purpose, the terms correspondi... Read More about A Neural Network Separation Approach for the Inclusion of Static Friction in Nonlinear Static Models of Industrial Robots.