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Robust Artificial Intelligence for Neurorobotics

Robust Artificial Intelligence for Neurorobotics

Bayes Centre (5th floor) and School of Informatics, University of Edinburgh (26 – 28 August 2019)

Author information

Neural computing is a powerful paradigm that has revolutionised machine learning. However, robotics brings stringent constraints on size, weight and power constraints (SWaP), which challenges the developers of these technologies in new ways. Equally, the fact that learning and adaptation might happen on a real physical platform implies a significantly greater emphasis on ensuring safety and rendering automated decisions verifiable and explainable. RAI-NR is a 3 day meeting featuring invited and contributed talks exploring issues of reliability, safety and resource efficiency in neurorobotic systems.

To this end, we invite contributed 4-6 page extended abstract submissions in line with the following themes:

Robotics and Robot Learning: How are neural network based methods and neuromorphic design principles driving advances in robotics?

Hardware for AI: How are new advances in neurally inspired computing and electronic sensing hardware enabling these advances?

Safety, verification and explainability: How are we developing the new techniques required to ensure the safety of learning, perception and control in real world settings?

Neuroscience for perception and action: How can perspectives on how animals/humans solve problems be used to drive advances in robotics?

Selected papers will be invited for inclusion in a special issue in the journal Frontiers in Neurorobotics.

Papers should be formatted using the latex template below, and submissions will be via the Microsoft conference management system.

Extended abstract submission

Frontiers in Neurorobotics

A special research topic will be published in Frontiers in Neurorobotics. To this end, the research topic will welcome submissions of Original Research and Reviews or Conference papers*** in line with the workshop themes.

*** Please note that Conference Paper must be expanded upon if they are to be considered as original work with a 30% extension of original content (for more information, see Author Guidelines here) ”


For further information/ any submission difficulties please contact either:


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