3-D Obstacle Detection Using Laser Range Finder with Polygonal Mirror for Powered Wheelchair

Kohei Kato; Hiroaki Seki; Masatoshi Hikizu

doi:10.20965/ijat.2015.p0373

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IJAT Vol.9 No.4 pp. 373-380

doi: 10.20965/ijat.2015.p0373

(2015)

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3-D Obstacle Detection Using Laser Range Finder with Polygonal Mirror for Powered Wheelchair

Kohei Kato, Hiroaki Seki, and Masatoshi Hikizu

School of Mechanical Engineering, College Science and Engineering, Kanazawa University
Kakuma, Kanazawa, Ishikawa 920-1192, Japan

Received:

January 15, 2015

Accepted:

June 1, 2015

Published:

July 5, 2015

Keywords:

steering support, obstacle detection, laser range finder, reflection

Abstract

Because a large number of accidents with electric wheelchairs are due to operational errors, steering assistance systems for wheelchairs have been studied in a variety of ways. One of the basic systems is 3-D obstacle detection around the wheelchair. One method uses a stereo camera for detecting obstacles by image processing. However, this method is less reliable under varying light conditions. A laser range sensor is another useful device for obstacle detection. However, it requires a complex swinging mechanism for 3-D positioning which makes the measuring time too long. Therefore, this paper presents a 3-D obstacle detection system for electric wheelchairs using a 2-D laser range sensor. We set up only one 2-D laser range sensor over the wheelchair, and attached mirrors around it to reflect the laser light obliquely downwards. Then, we gathered obstacle points while the electric wheelchair was moving and made a 3-D obstacle map to assist steering. We built a prototype device and confirmed by experimentation that it is able to detect obstacles in 3-D.

Cite this article as:

K. Kato, H. Seki, and M. Hikizu, “3-D Obstacle Detection Using Laser Range Finder with Polygonal Mirror for Powered Wheelchair,” Int. J. Automation Technol., Vol.9 No.4, pp. 373-380, 2015.

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References

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This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] A. C. Lopes, G. Pires, and U. Nunes, “Assisted navigation for a brain-actuated intelligent wheelchair,” Robotics and Autonomous Systems, Vol.61, pp. 245-258, 2013.

[2] [2] A. Nakamura, Y. Fujimoto, O. Nitta, and T. Yamaguchi, “Intelligent Powered Wheelchair Assistance in Daily Use,” Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.14, No.3, pp. 281-287, 2010.

[3] [3] P. F. Dieza, S. M. T. Müuller, V. A. Mut, E. Laciar, E. Avila, T. F. Bastos-Filho, and M. Sarcinelli-Filho, “Commanding a robotic wheelchair with a high-frequency steady-state visual evoked potential based brain–computer interface,” Medical Engineering & Physics, Vol.35, pp. 1155-1164, 2013.

[4] [4] N. Peixoto, H. G. Nik, and H. Charkhkar, “Voice controlled wheelchairs: Fine control by humming,” Computer methods and programs in biomedicine, Vol.112, pp. 156-165, 2013.

[5] [5] S. P. Parikh, V. Grassi Jr., V. Kumar, and J. Okamoto Jr., “Integrating Human Inputs with Autonomous Behaviors on an Intelligent Wheelchair Platform,” IEEE Intelligent Systems, pp. 33-41, 2007.

[6] [6] D. Vanhooydonck, E. Demeester, A. Hüntemann, J. Philips, G. Vanacker, H. V. Brussel, and M. Nuttin, “Adaptable navigational assistance for intelligent wheelchairs by means of an implicit personalized user model,” Robotics and Autonomous Systems, Vol.58, pp. 963-977, 2010.

[7] [7] J. Yang and T. Imura, “Design and Development of Human Interface System with 3D Measurement Functions (Concept and Basic Experiments),” Journal of Robotics and Mechatronics, Vol.24, No.1, pp. 235-243, 2012.

[8] [8] F. Leishman, O. Horn, and G. Bourhis, “Smart wheelchair control through a deictic approach,” Robotics and Autonomous Systems, Vol.58, pp. 1149-1158, 2010.

[9] [9] T. Ogino, M. Tomono, T. Akimoto, and A. Matsumoto, “Human Following by an Omnidirectional Mobile Robot Using Maps Built from Laser Range-Finder Measurement,” Journal of Robotics and Mechatronics, Vol.22, No.1, pp. 28-35, 2010.

[10] [10] I. Špacapan, J. Kocijan, and T. Bajd, “Simulation of Fuzzy-Logic-Based Intelligent Wheelchair Control System,” Journal of Intelligent and Robotic Systems, Vol.39, pp. 227-241, 2004.

[11] [11] M. R. M. Tomari, Y. Kobayashi, and Y. Kuno, “Development of Smart Wheelchair System for a User with Severe Motor Impairment,” Procedia Engineering, Vol.41, pp. 538-546, 2012.

[12] [12] M. Awai, A. Yamashita, T. Shimizu, T. Kaneko, Y. Kobayashi, and H. Asama, “Development of Mobile Robot System Equipped with Camera and Laser Range Finder Realizing HOG-Based Person Following and Autonomous Returning,” Journal of Robotics and Mechatronics, Vol.26, No.1, pp. 68-77, 2014.

[13] [13] K. Endou, T. Ikenoya, and R. Kurazume, “Development of 3D Scanning System Using Automatic Guiding Total Station,” Journal of Robotics and Mechatronics, Vol.24, No.6, pp. 992-999, 2012.

[14] [14] T. Emura, M. Kumagai, and L. Wang, “A Next-Generation Intelligent Car for Safe Drive,” Journal of Robotics and Mechatronics, Vol.12, No.5, pp. 545-551, 2000.