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3D Depth Camera-based Obstacle Detection in the Active Safety System of an Electric Wheelchair

전동휠체어 주행안전을 위한 3차원 깊이카메라 기반 장애물검출

  • Received : 2016.04.18
  • Accepted : 2016.06.13
  • Published : 2016.07.01

Abstract

Obstacle detection is a key feature in the safe driving control of electric wheelchairs. The suggested obstacle detection algorithm was designed to provide obstacle avoidance direction and detect the existence of cliffs. By means of this information, the wheelchair can determine where to steer and whether to stop or go. A 3D depth camera (Microsoft KINECT) is used to scan the 3D point data of the scene, extract information on obstacles, and produce a steering direction for obstacle avoidance. To be specific, ground detection is applied to extract the obstacle candidates from the scanned data and the candidates are projected onto a 2D map. The 2D map provides discretized information of the extracted obstacles to decide on the avoidance direction (left or right) of the wheelchair. As an additional function, cliff detection is developed. By defining the "cliffband," the ratio of the predefined band area and the detected area within the band area, the cliff detection algorithm can decide if a cliff is in front of the wheelchair. Vehicle tests were carried out by applying the algorithm to the electric wheelchair. Additionally, detailed functions of obstacle detection, such as providing avoidance direction and detecting the existence of cliffs, were demonstrated.

Keywords

References

  1. M. J. Yoon, G. Y. Jeong, and K. H. Yu, "Detection of obstacle distribution and mapping for walking guide of the blind," Journal of Institute of Control, Robotics and Systems, vol. 15, no. 2, pp. 155-162, Feb. 2009. https://doi.org/10.5302/J.ICROS.2009.15.2.155
  2. I. Ulrich and J. Borenstein, "Reliable obstacle avoidance for fast mobile robots" International Conference on Robotics and Automation (ICRA), pp. 1572-1577, May 1998.
  3. B. J. Jung, J. H. Park, T. Y. Kim, D. Y. Kim, and H. Moon, "Lane marking detection of mobile robot with single laser rangefinder," Journal of Institute of Control, Robotics and Systems (in Korean), vol. 17, no. 6, pp. 521-525, Feb. 2009.
  4. S. Soumare, A. Ohya, and S. Yuta, "Real-time obstacle avoidance by an autonomous mobile robot using an active vision sensor and a vertically emitted laser slit," Intelligent Autonomous Systems, pp. 301-308, 2002.
  5. M. Kumano, A. Ohya, and S. Yuta, "Obstacle avoidance of autonomous mobile robot using stereo vision sensor," Proc. of International. Symp. Robot and Automation, pp. 497-502, 2000.
  6. M. Bai, Y. Zhuang, and W. Wang, "Stereovision based obstacle detection approach for mobile robot navigation," Proc. of International Conference on Intelligent Control and Information Processing (ICICIP), Aug. 2010.
  7. A. Sanna, F. Lamberti, G. Paravati, and F. Manuri, "A Kinect-based natural interface for quadrotor control," Entertainment Computing, vol. 4, no. 3, pp. 179-186, Aug. 2013. https://doi.org/10.1016/j.entcom.2013.01.001
  8. R. Mojtahedzadeh, "Robot obstacle avoidance using the Kinect," Master's thesis, KTH Computer Science and Communication, 2011.
  9. H. Pham, T. Le, and N. Vuillerme, "Real-time obstacle detection system in indoor environment for the visually impaired using Microsoft Kinect sensor," Journal of Sensors, vol. 2016, Article ID 3754918, 13 pages, 2016.
  10. R. Coupec, R. Grbic, K. E. Nyarko, K. Sabo, and R.Scitovski, "Detection of planar surfaces based on RANSAC and LAD plane fitting," Proc. of the 4th European Conf. on Mobile Robots, ECMR'09, 2009.
  11. S. Se and M. Brady, "Ground plane estimation, error analysis and applications," Robotics and Autonomous Systems, vol. 39, no. 13, pp. 59-71, 2002. https://doi.org/10.1016/S0921-8890(02)00175-6
  12. Y. Y. Michael and F. Wolfgang, "Plane detection in point cloud data," Technical Report Nr. 1, 2010.
  13. J. Woo and N. Kim, "Vision-based obstacle collision risk estimation of an unmanned surface vehicle," Journal of Institute of Control, Robotics and Systems (in Korean), vol. 21, no. 12, pp. 1089-1099, 2015. https://doi.org/10.5302/J.ICROS.2015.15.0161
  14. T. J. Lee, H. Lee, and D. I. Cho, "Obstacle detection algorithm using forward-viewing mono camera," Journal of Institute of Control, Robotics and Systems (in Korean), vol. 21, no. 9, pp. 858-862, 2015. https://doi.org/10.5302/J.ICROS.2015.15.0104