Design of an Intelligent Self Balancing Inspection Robot for Industrial Monitoring

Mohammed Abaker, Zeashan Khan, Samir Mekid

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper describes the design steps of an intelligent segway robot for monitoring an industrial plant, and detecting corrosion and leakages using camera video. The self-balancing inspection robot (SBIR) integrates robotics, embedded control systems, and computer vision based mobile platform for autonomous inspection. The design cycle involves theoretical modeling and empirical analysis to select hardware components and develop a Segway robot platform using a PID control architecture for stable operation in industrial settings. Moreover, a WebSocket-based remote control system allows the operator to control the robot from a distance. The robot is able to detect real-time gas leakages using YOLOv8. The study demonstrates the efficacy of the mobile robots in enhancing safety and efficiency in industrial inspections. The project video can be seen here: https://youtu.be/aieaBv4d5k

Original languageEnglish
Title of host publication2024 2nd International Conference on Computing and Data Analytics, ICCDA 2024 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331542573
DOIs
StatePublished - 2024
Event2nd International Conference on Computing and Data Analytics, ICCDA 2024 - Shinas, Oman
Duration: 12 Nov 202413 Nov 2024

Publication series

Name2024 2nd International Conference on Computing and Data Analytics, ICCDA 2024 - Proceedings

Conference

Conference2nd International Conference on Computing and Data Analytics, ICCDA 2024
Country/TerritoryOman
CityShinas
Period12/11/2413/11/24

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

Keywords

  • PID control
  • Segway robot
  • computer vision
  • corrosion detection
  • industrial inspection
  • leak detection
  • manufacturing process monitoring

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Artificial Intelligence
  • Computer Science Applications
  • Decision Sciences (miscellaneous)
  • Statistics, Probability and Uncertainty
  • Computational Mathematics
  • Health Informatics
  • Education

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