Field Trial Results of Autonomous Road Crossing Mobile Robot

  • Aneesh Neeschal Chand
  • Shin’ichi Yuta
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 193)


We have developed a fully-integrated outdoor mobile robot that is capable of crossing roads autonomously in real world urban environments. To do this, the robot travels along pedestrian sidewalks autonomously, continually detects pedestrian push button boxes and navigates to it when one is detected. It then activates the push-button using an onboard-finger, moves to the crossing zone and crosses the road after detecting the zebra stripes and pedestrian lights. In this paper, we report the results of preliminary field trial experiments where the robot was deployed in a real world environment and its performance was evaluated.


road-crossing mobile robot real world outdoor environment 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Morales, Y., Takeuchi, E., Carballo, A., Tokunaga, W., Kuniyoshi, H., Aburadani, A., Hirosawa, A., Nagasaka, Y., Suzuki, Y., Tsubouchi, T.: 1Km Autonomous Robot Navigation on Outdoor Pedestrian Paths Running the Tsukuba Challenge 2007. In: 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, France, September 22-26, pp. 219–225 (2008)Google Scholar
  2. 2.
    Trulls, E., Corominas Murtra, A., Pérez-Ibarz, J., Ferrer, G., Vasquez, D., Mirats-Tur, J.M., Sanfeliu, A.: Autonomous navigation for mobile service robots in urban pedestrian environments. Journal of Field Robotics 28, 329–354, doi:10.1002/rob.20386Google Scholar
  3. 3.
    Viola, P., Jones, M.J.: Rapid Object Detection Using a Boosted Cascade of Simple Features. In: IEEE Conf. Computer Vision and Pattern Recognition, CVPR (2001)Google Scholar
  4. 4.
    Chand, A.N., Yuta, S.: Vision and Laser Sensor Data Fusion Technique for Target Approaching by Outdoor Mobile Robot. In: IEEE International Conference on Robotics and Biomemitics, Tianjin, China, December 14-18, pp. 1624–1629 (2010)Google Scholar
  5. 5.
    Chand, A.N., Yuta, S.: Design of an Intelligent Outdoor Mobile Robot with Autonomous Road-Crossing Function for Urban Environments. In: 2012 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (2012)Google Scholar
  6. 6.
    Duda, R.O., Hart, P.E.: Use of the hough transformation to detect lines and curves in pictures. Communications of the ACM 15(1), 11–15 (1972)CrossRefGoogle Scholar
  7. 7.
    Kuranov, A., Lienhart, R., Pisarevsky, V.: An Empirical Analysis of Boosting Algorithms for Rapid Objects Withan Extended Set of Haar-like Features. Tech. Rep. MR LTR, Intel Technical Report (July 2002)Google Scholar
  8. 8.
    Lidoris, G., Rohrmuller, F., Wollherr, D., Buss, M.: The Autonomous City Explorer Project – Mobile robot navigation in highly populated urban environments. In: IEEE International Conference on Robotics and Automation, Kobe, May12-17, pp. 1416–1422 (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.School of Electrical EngineeringFiji National UniversitySamabulaJapan
  2. 2.Department of Electrical EngineeringShibaura Institute of TechnologyTokyoJapan

Personalised recommendations