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AutoInspect: Towards Long-Term Autonomous Industrial Inspection

Autor: Staniaszek, Michal, Flatscher, Tobit, Rowell, Joseph, Niu, Hanlin, Liu, Wenxing, You, Yang, Skilton, Robert, Fallon, Maurice, Hawes, Nick

We give an overview of AutoInspect, a ROS-based software system for robust and extensible mission-level autonomy. Over the past three years AutoInspect has been deployed in a variety of environments, including at a mine, a chemical plant, a mock oil

Externí odkaz: http://arxiv.org/abs/2404.12785

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Sim-to-Real Deep Reinforcement Learning with Manipulators for Pick-and-place

Autor: Liu, Wenxing, Niu, Hanlin, Skilton, Robert, Carrasco, Joaquin

When transferring a Deep Reinforcement Learning model from simulation to the real world, the performance could be unsatisfactory since the simulation cannot imitate the real world well in many circumstances. This results in a long period of fine-tuni

Externí odkaz: http://arxiv.org/abs/2309.09247

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Akademický článek

Feasibility of a new ‘balanced binocular viewing’ treatment for unilateral amblyopia in children aged 3–8 years (BALANCE): results of a phase 2a randomised controlled feasibility trial

Autor: Amanda Davis, Daniel Baker, Mohamed Abbas, Hakim-Moulay Dehbi, Annegret Hella Dahlmann-Noor, John A Greenwood, Andrew Skilton, Siobhan Ludden, Steven C Dakin, Emma Clay, Payal Khandelwal, Denise Dunham

Publikováno v: BMJ Open, Vol 14, Iss 7 (2024)

Objectives This study aimed to evaluate the safety of dichoptic balanced binocular viewing (BBV) for amblyopia in children, plus feasibility, adherence, acceptability, trial methodology and clinical measures of visual function.Design We carried out a

Externí odkaz: https://doaj.org/article/613a24e3a80f4537b4d6546eac6c045b