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Reseach Article

A Study on Techniques of Person Following Robot

by Muhammad Najib Abu Bakar, Mohd Fahmi Mohamad Amran
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 125 - Number 13
Year of Publication: 2015
Authors: Muhammad Najib Abu Bakar, Mohd Fahmi Mohamad Amran
10.5120/ijca2015906165

Muhammad Najib Abu Bakar, Mohd Fahmi Mohamad Amran . A Study on Techniques of Person Following Robot. International Journal of Computer Applications. 125, 13 ( September 2015), 27-30. DOI=10.5120/ijca2015906165

@article{ 10.5120/ijca2015906165,
author = { Muhammad Najib Abu Bakar, Mohd Fahmi Mohamad Amran },
title = { A Study on Techniques of Person Following Robot },
journal = { International Journal of Computer Applications },
issue_date = { September 2015 },
volume = { 125 },
number = { 13 },
month = { September },
year = { 2015 },
issn = { 0975-8887 },
pages = { 27-30 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume125/number13/22494-2015906165/ },
doi = { 10.5120/ijca2015906165 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:15:58.836770+05:30
%A Muhammad Najib Abu Bakar
%A Mohd Fahmi Mohamad Amran
%T A Study on Techniques of Person Following Robot
%J International Journal of Computer Applications
%@ 0975-8887
%V 125
%N 13
%P 27-30
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Robotic industry has evolved so much and has been a revolutionary in helping human being to complete certain task. Without the help of industrial robotics to produce car, cellphone or a computer, productions will suffer as time is a very important factor for businesses. Researchers around the world understand this, and there is already an artificial intelligent robot being produced. Each year, there will be new findings to create a robot that may one day behave similarly like a human being. However, this paper will only discuss about person following robot, a robot that should help human in an environment such as hospitals, schools, or shopping malls.

References
  1. P. Viola, M.J. Jones, and D. Snow. Detecting Pedestrians Using Patterns of Motion and Appearance. Int. J. of Computer Vision, Vol. 63, No. 2, pp. 153–161, 2005.
  2. N. Dalal and B. Briggs. Histograms of Oriented Gradients for Human Detection. In Proceedings of 2005 IEEE Conf. on Computer Vision and Patttern Recognition, pp. 886–893, 2005.
  3. B. Han, S.W. Joo, and L.S. Davis. Probabilistic Fusion Tracking Using Mixture Kernel-Based Bayesian Filtering. In Proceedings of the 11th Int. Conf. on Computer Vision, 2007.
  4. C.-Y. Lee, H. Gonzalez-Banos, and J.-C. Latombe. Real-Time Tracking of an Unpredictable Target Amidst Unknown Obstacles. In Proceedings of the 7th Int. Conf. on Control, Automation, Robotics and Vision, pp. 596–601, 2002
  5. D. Schulz, W. Burgard, D. Fox, and A.B. Cremers. People Tracking with a Mobile Robot Using Sample-Based Joint Probabilistic Data Association Filters. Int. J. of Robotics Research, Vol. 22, No. 2, pp. 99–116, 2003
  6. H. Koyasu, J. Miura, and Y. Shirai. Realtime Omnidirectional Stereo for Obstacle Detection and Tracking in Dynamic Environments. In Proceedings of the 2001 IEEE/RSJ Int. Conf. on Intelligent Robots and Sysetms, pp. 31–36, 2001.
  7. M. Kobilarov, G. Sukhatme, J. Hyams, and P. Batavia. People Tracking and Following with Mobile Robot Using Omnidirectional Camera and a Laser. In Proceedings of 2006 IEEE Int. Conf. on Robotics and Automation, pp. 557–562, 2006
  8. D. Beymer and K. Konolige. Real-Time Tracking of Multiple People Using Continuous Detection. In Proceedings of the 7th Int. Conf. on Computer Vision, 1999.
  9. S. Shaker, J.J. Saade, D. Asmar. Fuzzy Inference-Based Person-Following Robot. In Proceedings of International Journal of Systems Applications, Engineering & Development, Issue 1, Volume 2, 2008, pp. 29-34.
  10. J.J.Saade,O.Houalla,H.Merhi and J.Kabbani, Fuzzy Inference Based Car Following Collision Prevention Controller, WSEAS Transactions on Systems. Vol.5, October 2006, pp.2291-2298
  11. Z. Chen, S.T Birchfield, Person Following with a Mobile Robot Using Binocular Feature-Based Tracking, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) San Diego, California, October 2007
  12. M. A. Fischler, R. C. Bolles. Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Comm. of the ACM, 24: 381-395, 1981.
  13. J. Satake, J, Miura. Robust Stereo-Based Person Detection and Tracking for a Person Following Robot. Proceedings of the IEEE ICRA 2009, Workshop on People Detection and Tracking, Kobe, Japan, May 2009.
  14. J. Satake, M. Chiba, J. Miura. A SIFT-Based Person Identification using a Distance-Dependent Appearance Model for a Person Following Robot. Proceedings of the 2012 IEEE International Conference on Robotics and Biomimetics, December 11-14, 2012, Guangzhou, China, pp. 962-967.
  15. B. Ilias, S.A. Abdul Shukor, S. Yaacob, A.H. Adom and M.H. Mohd Razali. A Nurse Following Robot with High Speed Kinect Sensor. ARPN Journal of Engineering and Applied Sciences, vol. 9. No 12, December 2014, pp. 2454-2459.
Index Terms

Computer Science
Information Sciences

Keywords

Robots Technique