Stereo Vision-based Autonomous Target Detection and Tracking on an Omnidirectional Mobile Robot

Wei Luo, Zhefei Xiao, Henrik Ebel, Peter Eberhard

2019

Abstract

In this paper, a mobile robot equipped with an onboard computing unit and a stereo camera for autonomous target detection and tracking is introduced. This system can figure out an interesting target and track it robustly in real time. It is based on the ROS framework and can handle multi-resource information, such as RGB images, depth information, and IMU data. To balance the performance of the machine learning based object detection algorithm and the algorithm for object tracking, the Hamming distance and the intersection over union are selected as criteria. The performance of the system is verified in a hardware experiment in two typical scenarios.

Paper Citation

in Harvard Style

Luo W., Xiao Z., Ebel H. and Eberhard P. (2019). Stereo Vision-based Autonomous Target Detection and Tracking on an Omnidirectional Mobile Robot.In Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-758-380-3, pages 268-275. DOI: 10.5220/0007835702680275

in Bibtex Style

@conference{icinco19,
author={Wei Luo and Zhefei Xiao and Henrik Ebel and Peter Eberhard},
title={Stereo Vision-based Autonomous Target Detection and Tracking on an Omnidirectional Mobile Robot},
booktitle={Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2019},
pages={268-275},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007835702680275},
isbn={978-989-758-380-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - Stereo Vision-based Autonomous Target Detection and Tracking on an Omnidirectional Mobile Robot
SN - 978-989-758-380-3
AU - Luo W.
AU - Xiao Z.
AU - Ebel H.
AU - Eberhard P.
PY - 2019
SP - 268
EP - 275
DO - 10.5220/0007835702680275