Interactive Learning of Mobile Robots Kinematics Using ARCore

Abhidipta Mallik, Vikram Kapila

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

Abstract

Recent years have witnessed several educational innovations to provide effective and engaging classroom instruction with the integration of immersive interactions based on augmented reality and virtual reality (AR/VR). This paper outlines the development of an ARCore-based application (app) that can impart interactive experiences for hands-on learning in engineering laboratories. The ARCore technology enables a smartphone to sense its environment and detect horizontal and vertical surfaces, thus allowing the smartphone to estimate any position in its workspace. In this mobile app, with touch-based interaction and AR feedback, the user can interact with a wheeled mobile robot and reinforce the concepts of kinematics for a differential drive mobile robot. The user experience is evaluated and system performance is validated through a user study with participants. The assessment shows that the proposed AR interface for interacting with the experimental setup is intuitive, easy to use, exciting, and recommendable.

Original languageEnglish (US)
Title of host publication2020 5th International Conference on Robotics and Automation Engineering, ICRAE 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781728189819
DOIs
StatePublished - Nov 20 2020
Event5th International Conference on Robotics and Automation Engineering, ICRAE 2020 - Virtual, Singapore, Singapore
Duration: Nov 20 2020Nov 22 2020

Publication series

Name2020 5th International Conference on Robotics and Automation Engineering, ICRAE 2020

Conference

Conference5th International Conference on Robotics and Automation Engineering, ICRAE 2020
CountrySingapore
CityVirtual, Singapore
Period11/20/2011/22/20

Keywords

  • ARCore
  • augmented reality
  • mobile robot kinematics
  • robotics education

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering
  • Mechanical Engineering
  • Control and Optimization

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