Towards robotic decommissioning of legacy nuclear plant: Results of human-factors experiments with tele-robotic manipulation, and a discussion of challenges and approaches for decommissioning

Muhammad Talha, Amir Masoud Ghalamzan Esfahani, Chie Takahashi, Jeffrey Kuo, Wayne Ingamells, Rustam Stolkin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)

Abstract

This paper explores the problems of developing robotic systems for decommissioning legacy nuclear infrastructure, such as the many contaminated gloveboxes present in UK, USA and other countries. We begin with a discussion of these decomissioning challenges. We review the current manual methods for decommissioning alpha-contaminated plant, and review robotic approaches which might replace such direct human interventions. We then present our initial experiments with human test-subjects, exploring the ability of humans to control a remote robot to perform complex manipulation tasks. Our preliminary results reveal a number of interesting lessons: conventional tele-manipulation is very difficult and very slow without significant training; metrics for usability of such technology can be conflicting and hard to interpret; aptitude for tele-manipulation varies significantly between individuals; however such aptitude may be predicted by using spatial awareness tests to select prospective robot operators; additionally the abilities of people with different initial aptitudes appear to converge somewhat as learning progresses. An additional contribution of this paper is to show how rigorous scientific methodologies, drawn from the psychology and human-factors research fields, can be used to analyse the performance of humans using robots to perform practical tasks.
Original languageEnglish
Title of host publication2016 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)
PublisherIEEE Xplore
ISBN (Electronic)9781509043491
ISBN (Print)9781509043507
DOIs
Publication statusPublished - 15 Dec 2016

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