Research Article Open Access

Vision-Based Real-Time Positioning and Autonomous Navigation System Using Mobile Robot in Indoor Environments

Diop Mamadou1, Lim Chot Hun1, Lim Tien Sze1 and Ong Lee Yeng1
  • 1 Multimedia University, Malaysia
American Journal of Applied Sciences
Volume 13 No. 5, 2016, 593-608

DOI: https://doi.org/10.3844/ajassp.2016.593.608

Submitted On: 14 March 2016 Published On: 17 May 2016

How to Cite: Mamadou, D., Hun, L. C., Sze, L. T. & Yeng, O. L. (2016). Vision-Based Real-Time Positioning and Autonomous Navigation System Using Mobile Robot in Indoor Environments. American Journal of Applied Sciences, 13(5), 593-608. https://doi.org/10.3844/ajassp.2016.593.608

Abstract

Research toward unmanned mobile robot navigation has gained significant importance in the last decade due to its potential applications in the location-based services industry. The increase in construction of large space indoor buildings has made difficulty for humans to operate within such environments. In this study, a mobile robot's indoor navigation algorithm is developed with vision cameras. Using two monocular cameras (one looking forward and one looking downward), the developed algorithms make use of the salient features of the environments to estimate rotational and translational motions for real-time positioning of the mobile robot. At the same time, an algorithm based on artificial landmark recognition is developed. The artificial landmark is shaped arrow based signboards with different colors representing different paths. These algorithms are integrated into a designed framework for mobile robot real-time positioning and autonomous navigation. Experiments are performed to validate the designed system using the mobile robot PIONEER P3-AT. The developed algorithm was able to detect and extract artificial landmark information up to 3 m distance for the mobile robot guidance. Experiment results show an average error of 0.167 m deviation from the ideal path, signified the good ability and performance of the development autonomous navigation algorithm.

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Keywords

  • Real-Time
  • Vision-Aided Navigation
  • Artificial Landmark