Design and development of a mobile robotics module with ROS/Gazebo twin for flexible, adaptive hands-on learning: in-campus/remote/hybrid

Mario Mata*, Ryan M. Gibson

*Corresponding author for this work

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


Robotics is a strongly interdisciplinary, exciting field, common in Engineering degrees. Setting up a suitable lab environment to accommodate practical work for a number of students is a demanding and costly aspect in any Robotics module. Shifting from classic in-campus learning towards fully remote or hybrid models adds an additional challenge. Rigid hybrid models, requiring students to take specific parts of the module in campus (usually practical contents) cannot adapt to students unable to come to campus on unpredictable weeks due to illness or work commitments. Ideally, all module contents including the full practical should allow a flexible learning modality, while keeping the remote version of the practical as close as possible to the in-campus one. This paper, based on a 6-year
module development experience, discusses ideas that can be helpful for lecturers developing a new Robotics module or adapting an existing one for flexible hybrid learning. The Robot Operating System (ROS) has proven to be a highly flexible and effective tool in his context. The NVidia’s “robotics teaching kit” (Jet robots) we use for the practical presented a number of limitations, but once fixed it has proven to be a capable platform; other robotic platforms can be used instead as long as they satisfy certain requirements. Finally, Gazebo physics simulation engine allows using a dual real/simulated environment. Combined with a careful theory/practical contents matching, our approach provides flexibility for in-campus or remote learning on any delivery week to support students (or lecturers) facing unexpected attendance issues.
Original languageEnglish
Title of host publicationIntelligent Computing: Proceedings of the 2023 Computing Conference, Volume 2
EditorsKohei Arai
PublisherSpringer International Publishing AG
Number of pages19
ISBN (Electronic)9783031379635
ISBN (Print)9783031379628
Publication statusPublished - 20 Aug 2023
EventComputing Conference 2022 - Online
Duration: 14 Jul 202215 Jul 2022 (Link to conference website)

Publication series

NameLecture Notes in Networks and Systems
Volume739 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389


ConferenceComputing Conference 2022
Internet address


  • Robotics
  • Adaptive Hybrid Learning
  • ROS
  • Module Development
  • Gazebo
  • NVidia Jet

ASJC Scopus subject areas

  • Signal Processing
  • Control and Systems Engineering
  • Computer Networks and Communications


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