Localizing Pipe inspection robot using visual odometry

Hamed Habibi Aghdam, Herdawatie Abdul Kadir, Mohd Rizal Arshad, Munir Zaman

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

7 Citations (Scopus)

Abstract

There is a special type of concrete pipe beneath the roads in Malaysia which is called culvert. Detecting the place of damages in these pipes is important for maintenance operations. Pipe inspection robots are one of the most reliable ways to achieve this goal. Because of the wheel slippage, low speed motion and dynamic changes in kinematic of the robot, the INS and wheel encoder methods are not accurate enough for localizing the robot inside a culvert. In this paper, we propose a solution based on monocular visual odometry. We show that although the surface of the culvert is not flat, nevertheless, by selecting an appropriate camera the optical flow of the pixels inside a small area near the center of the image is almost equal and for this reason the 3D motion of the robot can be estimated using the derivative of camera parameters. The experimental result shows this method is reliable and can be successfully used for localizing the robot inside the culverts.

Original languageEnglish
Title of host publicationProceedings - 4th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages245-250
Number of pages6
ISBN (Electronic)9781479956869
DOIs
Publication statusPublished - 30 Mar 2014
Externally publishedYes
Event4th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2014 - Batu Ferringhi, Penang, Malaysia
Duration: 28 Nov 201430 Nov 2014

Publication series

NameProceedings - 4th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2014

Conference

Conference4th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2014
Country/TerritoryMalaysia
CityBatu Ferringhi, Penang
Period28/11/1430/11/14

Keywords

  • features detection
  • inspection robot
  • pipe damage
  • Visual odometry

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