Augmented reality assisted calibration of digital twins of mobile robots

Richard Williams, John Ahmet Erkoyuncu, Tariq Masood, Rok Vrabic

Research output: Contribution to journalConference articlepeer-review

15 Citations (Scopus)
65 Downloads (Pure)


In this age of globalisation and digitalisation, industry is evolving from a physical space information flow towards a two-way communication between virtual and physical space. The challenge that this research aims to resolve is: 'how can a virtual system adjust itself to the constantly changing conditions of the physical space of information that influences the operational dynamics of maintenance in industry?'. This article presents an augmented reality (AR) assisted digital twin (DT) solution that can be used to calibrate mobile robots in maintenance environments. This DT solution was achieved by providing the user the ability to predict the battery charge of the mobile robot by using historic data as the input and providing the user a visual representation of the mobile robot's movements using an AR device as a medium to display this digital data. Overall, the trial demonstration was a success in implementing a DT to calibrate a mobile robot with AR assistance. Therefore, this DT solution can be implemented into niche areas of industrial environments. With the capability of predicting the battery charge enabling the user to know when the mobile robot will be empty, the user can maximise its use before recalling it for the charge. This would improve the accuracy of scheduling when mobile robots can be deployed and maximise the utilization of the robot and reduce the running cost of mobile robots in the long term.

Original languageEnglish
Pages (from-to)203-208
Number of pages6
Issue number3
Publication statusPublished - 18 Dec 2020
Event4th IFAC Workshop on Advanced Maintenance Engineering, Services and Technologies, AMEST 2020 - Cambridge, United Kingdom
Duration: 10 Sept 202011 Sept 2020


  • AR
  • augmented reality
  • digital twin
  • DT
  • mobile robot
  • prediction


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