Edge accelerated AI for robotic teleoperation

Keary, Alphonsus; Amer, Nehal; Emam, Masoud; Dunne, Alan; Torres, Javier; O’Riordan, Kate; Walsh, Michael; O’Flynn, Brendan

Edge accelerated AI for robotic teleoperation

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Files

20250826 Edge AI for Robotic Teleoperation (FINAL PDF eXpress Passed) (002).pdf(404.84 KB)

Accepted Version

Date

2025

Authors

Keary, Alphonsus

Amer, Nehal

Emam, Masoud

Dunne, Alan

Torres, Javier

O’Riordan, Kate

Walsh, Michael

O’Flynn, Brendan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Abstract

This paper presents a body of work on the development of edge accelerated AI hardware and software components related to robotic teleoperations. In particular, the paper proposes a system based architecture incorporating teleoperations communications layers in the form of a local to remote edge based stack, along with a Time of Flight (ToF) sensor layer, delivering user controls via real time hand and gesture signals for robotic teleoperations. Typical use cases include, remote skills delivery, precision robot manipulation, factory of the future, dangerous work environments and many other Industry 4.0/5.0 scenarios.

Keywords

Industrial automation , Artificial Intelligence , Industry 4.0 , Industry 5.0 , Edge computing , PLCs , Profinet , RapID

Citation

Keary, A., Amer, N., Emam, M., Dunne, A., Torres, J., O’Riordan, K., Walsh, M. and O’Flynn, B. (2025) 'Edge accelerated AI for robotic teleoperation', IEEE Sensors 2025, Vancouver, Canada, 19-22 October. [Forthcoming]