JRM Vol.28 No.4 pp. 500-507
doi: 10.20965/jrm.2016.p0500


Oncoming Human Avoidance for Autonomous Mobile Robot Based on Gait Characteristics

Tetsuo Tomizawa and Yuya Shibata

The University of Erectro-Communications
1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan

February 26, 2016
April 27, 2016
August 20, 2016
pedestrian avoidance, gait characteristics, landing timing
When two pedestrians pass one another on busy intersections or pedestrian crossings, they may try to avoid each other by moving in the same direction. Such behavior becomes a factor hindering a smooth walking. When robots will come to be used in our immediate environment in the future, similar situations are likely to occur. The objective of this study is to determine the appropriate avoidance action (direction and timing) that a robot should take in order to minimize the risk of coming face to face with a pedestrian, in situations where the two parties, who share a common travel line, pass one another. First, two experiments were conducted using human subjects to investigate the walking tendencies (gait characteristics) when a person walks past another oncoming person. Here, we examined the relationship between the landed foot and the direction in which it is easier to move and the tendencies of the avoidance direction when a person makes a sudden move to avoid another oncoming person. Based on the results, we proposed the avoidance action that the robot must take when it passes a human pedestrian, and confirmed its effectiveness through a verification experiment.
Overview of oncoming human avoidance

Overview of oncoming human avoidance

Cite this article as:
T. Tomizawa and Y. Shibata, “Oncoming Human Avoidance for Autonomous Mobile Robot Based on Gait Characteristics,” J. Robot. Mechatron., Vol.28 No.4, pp. 500-507, 2016.
Data files:
  1. [1] T. Tomizawa, S. Muramatsu, M. Sato, M. Hirai, S. Kudoh, and T. Suehiro, “Development of an Intelligent Senior-Car in a Pedestrian Walkway,” Advanced Robotics, Vol.26, No.14, pp. 1577-1602, 2012.
  2. [2] S. Ohkawa, Y. Takita, H. Date, and K. Kobayashi, “Development of Autonomous Mobile Robot Using Articulated Steering Vehicle and Lateral Guiding Method,” J. of Robotics and Mechatronics, Vol.27, No.4, pp. 337-345, 2015.
  3. [3] J. Eguchi and K. Ozaki, “Development of Autonomous Mobile Robot Based on Accurate Map in the Tsukuba Challenge 2014,” J. of Robotics and Mechatronics, Vol.27, No.4, pp. 346-355, 2015.
  4. [4] K. Okawa, “Three Tiered Self-Localization of Two Position Estimation Using Three Dimensional Environment Map and Gyro-Odometry,” J. of Robotics and Mechatronics, Vol.26, No.2, pp. 196-203, 2014.
  5. [5] D. Fox, W. Burgard, and S. Thrun, “The Dynamic Window Approach to Collision Avoidance,” IEEE Robotics and Automation Magazine, pp. 23-33, 1997.
  6. [6] Y. Tamura, S. Hamasaki, A. Yamashita, and H. Asama, “Collision avoidance of mobile robot based on prediction of human movement according to environments.” Trans. of the Japan Society of Mechanical Engineers, Series C, Vol.79, No.799, pp. 617-628, 2013.
  7. [7] H. Noguchi, T. Yamada, T. Mori, and T. Sato, “Human Avoidance Path Planning based on Massive People Trajectories,” J. of the Robotics Society of Japan, Vol.30, No.7, pp. 684-694, 2012 (in Japanese).
  8. [8] S. Thompson, T. Horiuchi, and S. Kagami, “A Probabilistic Model of Human Motion and Navigation Intent for Mobile Robot Path Planning,” Proc. of the Int. Conf. on Autonomous Robots and Agents (ICARA) 2009, pp. 663-668, 2009.
  9. [9] M. Yoda and Y. Shiota, “A Study on the Mobile Robot which Passes a Man,” J. of the Robotics Society of Japan, Vol.17, No.2, pp. 202-209, 1999 (in Japanese).
  10. [10] D. Helbing and P. Molnar, “Social Force Model for Pedestrian Dynamics,” Physical Review E, Vol.51, No.5, pp. 4282-4286, 1995.
  11. [11] Y. Shibata and T. Tomizawa, “A Study of the Adaptive Avoidance Behavior Based on Human Gait Features,” The Proc. of the 16th SICE System Integration Division Annual Conf., pp. 1373-1376, 2015 (in Japanese).

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on May. 19, 2024