MONOCULAR VISUAL ODOMETRY FOR IN-PIPE INSPECTION ROBOT

Authors

  • Herdawatie Abdul Kadir Department of Robotic & Mechatronic Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia (UTHM), Malaysia
  • M. R. Arshad Underwater, Control and Robotics Group (UCRG), School of Electrical and Electronic Engineering, Engineering Campus, Universiti Sains Malaysia (USM), Malaysia
  • Hamed Habibi Aghdam Underwater, Control and Robotics Group (UCRG), School of Electrical and Electronic Engineering, Engineering Campus, Universiti Sains Malaysia (USM), Malaysia
  • Munir Zaman Dept. of Electrical and Electronic Engineering, Faculty of Engineering, University of Nottingham, Malaysia Campus, Selangor, Malaysia

DOI:

https://doi.org/10.11113/jt.v74.4806

Keywords:

Visual odometry, monocular, culverts, localize, image displacement

Abstract

This paper describes a monocular visual odometry technique for low texture environment localization. Estimating the pose of a robot in a small time interval is one of the challenging problems in robotics. Localization, mapping and motion planning are three fundamental problems which directly use the pose information of the robot to achieve their goal. In this work, we extract the pose information by processing image inside a concrete culvert which is taken by a camera attached to a mobile robot. We analyze different motion scenario using correlation based image to find displacement vector between two images. Real image data from the displacement of the robot are used to demonstrate the propose method. The experimental results show that the selected method proven efficient for the in-pipe inspection robot localization.

References

Mitchell, G. F., Masada, T., Sargand, S. M., & Tarawneh, B. 2005. Risk Assessment and Update of Inspection Procedures for Culverts (No. FHWA/OH-2005/002).

Beaver, J. L., & McGrath, T. J. 2005. Management of Utah Highway Culverts. Transportation Research Record. Journal of the Transportation Research Board. 1904(1): 113-123.

Perrin, J., & Dwivedi, R. 2006. Need For Culvert Asset Management. Transportation Research Record. Journal of the Transportation Research Board. 1957(1): 8-15.

Liu, Z., & Kleiner, Y. 2013. State of the Art Review of Inspection Technologies for Condition Assessment of Water Pipes. Measurement. 46(1): 1-15.

Scaramuzza, D., Fraundorfer, F. 2011. Visual Odometry [Tutorial]. Robotics & Automation Magazine, IEEE. 18(4): 80-92.

Scaramuzza, D., & Siegwart, R. 2008. Appearance-guided Monocular Omnidirectional Visual Odometry for Outdoor Ground Vehicles. Robotics, IEEE Transactions on. 24(5): 1015-1026.

Nistér, D., Naroditsky, O., & Bergen, J. 2006. Visual Odometry for Ground Vehicle Applications. Journal of Field Robotics. 23(1): 3-20.

Xiaojing Song, L. D. Seneviratne, K. Althoefer, Zibin Song, & Y. H. Zweiri. 2007. Visual Odometry for Velocity Estimation of UGVs. International Conference on Mechatronics and Automation. 5-8 August 2007. 1616.

Killpack, M., Deyle, T., Anderson, C. & Kemp, C. C. Visual Odometry and Control for an Omnidirectional Mobile Robot With a Downward-Facing Camera. International Conference on Intelligent Robots and Systems (IROS).18-22 October 2010. 139-146.

Lovegrove, S., Davison, A. J. & Ibanez-Guzman, J. Accurate Visual Odometry from a Rear Parking Camera. IEEE Intelligent Vehicles Symposium (IV). 5-9 June 2011. 788.

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Published

2015-06-21

Issue

Vol. 74 No. 9: Underwater System Technology: Theory and Applications

Section

Science and Engineering

License

Copyright of articles that appear in Jurnal Teknologi belongs exclusively to Penerbit Universiti Teknologi Malaysia (Penerbit UTM Press). This copyright covers the rights to reproduce the article, including reprints, electronic reproductions, or any other reproductions of similar nature.

How to Cite

MONOCULAR VISUAL ODOMETRY FOR IN-PIPE INSPECTION ROBOT. (2015). Jurnal Teknologi, 74(9). https://doi.org/10.11113/jt.v74.4806