Title: An integrative approach for tracking of mobile robot with vision sensor

Authors: Sangram Keshari Das; Sabyasachi Dash; B.K. Rout

Addresses: Centre for Robotics and Intelligent Systems (CRIS), Birla Institute of Technology and Science, Pilani, Rajasthan, 333031, India ' Centre for Robotics and Intelligent Systems (CRIS), Birla Institute of Technology and Science, Pilani, Rajasthan, 333031, India ' Centre for Robotics and Intelligent Systems (CRIS), Birla Institute of Technology and Science, Pilani, Rajasthan, 333031, India

Abstract: Current work addresses an experimental approach which incorporates feature-based object detection, KLT algorithm-based tracking method and Kalman filter-based de-noising technique in a real-time environment. In the detection phase, the mobile robot is detected using Viola-Jones algorithm which extracts detectable features. Then the position of the mobile robot is computed with homography constraints and a region of interest window is set up to accommodate the mobile robot. In the tracking phase, the region of interest window is dealt with using KLT algorithm. The proposed method is of practical importance when the mobile robot is tracked while moving on a predetermined (specified) path as the size of the image of the mobile robot is small relative to the captured image of the environment. Thus the analysis of captured image of environment becomes unnecessary for tracking and thereby the approach reduces computational load. The proposed approach accurately detects and tracks the mobile robot with error percentage ranging from 0.5% to 10% in different parts of the specified path.

Keywords: mobile robot; Viola-Jones algorithm; KLT algorithm; Kalman filter; vision-based tracking.

DOI: 10.1504/IJCVR.2019.098795

International Journal of Computational Vision and Robotics, 2019 Vol.9 No.2, pp.111 - 131

Received: 01 May 2018
Accepted: 22 Jun 2018
Published online: 02 Apr 2019 *

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