JRM Vol.34 No.5 pp. 956-964
doi: 10.20965/jrm.2022.p0956


Development of Air Hockey Robot with High-Speed Vision and High-Speed Wrist

Koichiro Tadokoro, Shotaro Fukuda, and Akio Namiki

Chiba University
1-33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan

March 31, 2022
July 6, 2022
October 20, 2022
air hockey robot, high-speed vision, human-robot interaction
Development of Air Hockey Robot with High-Speed Vision and High-Speed Wrist

Overview of robot arm

Our research group has developed an air hockey robot with high-speed vision capable of visual recognition at 500 Hz, which exceeds that of humans. Although this robot uses high-speed vision to increase its reaction speed and improve its performance, it has a low speed to compete with humans because its hand speed is still not sufficiently fast. In this study, a high-speed wrist rotation mechanism using a direct drive motor was introduced to the air hockey robot to improve the hitting speed through the snapping motion of the wrist. Furthermore, we developed a hitting motion algorithm that utilizes high-speed visual feedback. The effectiveness of the proposed system was verified experimentally. The proposed system exhibits an improved motion performance.

Cite this article as:
K. Tadokoro, S. Fukuda, and A. Namiki, “Development of Air Hockey Robot with High-Speed Vision and High-Speed Wrist,” J. Robot. Mechatron., Vol.34, No.5, pp. 956-964, 2022.
Data files:
  1. [1] R. L. Andersson, “Aggressive trajectory generator for a robot ping-pong player,” IEEE Control Systems Magazine, Vol.9, No.2, pp. 15-21, 1989.
  2. [2] M. Takeuchi, J. Shimodaira, Y Amaoka, S. Hamatani, H. Hirai, and F. Miyazaki, “Reconstruction of human skills by using pca and transferring them to a robot,” J. Robot. Mechatron., Vol.26, No.1, pp. 51-58, 2014.
  3. [3] Z. Wang, A. Boularias, K. Mülling, B. Schölkopf, and J. Peters, “Anticipatory action selection for human-robot table tennis,” Artificial Intelligence, Vol.247, pp. 399-414, 2017.
  4. [4] K. Yamada, “Robot table tennis tutor as an example of “harmony between human and robot”,” J. of The Institute of Electrical Engineers of Japan, Vol.137, No.2, pp. 81-84, 2017 (in Japanese).
  5. [5] S. Mori, K. Tanaka, S. Nishikawa, R. Niiyama, and Y. Kuniyoshi, “High-speed and lightweight humanoid robot arm for a skillful badminton robot,” IEEE Robotics and Automation Letters, Vol.3, No.3, pp. 1727-1734, 2018.
  6. [6] W. Chen, T. Liao, Z. Li, H. Lin, H. Xue, L. Zhang, J. Guo, and Z. Cao, “Using ftoc to track shuttlecock for the badminton robot,” Neurocomputing, Vol.334, pp. 182-196, 2019.
  7. [7] A. Namiki and F. Takahashi, “Motion generation for a sword-fighting robot based on quick detection of opposite player’s initial motions,” J. Robot. Mechatron., Vol.27, No.5, pp. 543-551, 2015.
  8. [8] B. E. Bishop and M. W. Spong, “Vision-based control of an air hockey playing robot,” IEEE Control Systems Magazine, Vol.19, No.3, pp. 23-32, 1999.
  9. [9] M. W. Spong, “Impact controllability of an air hockey puck,” Systems & Control Letters, Vol.42, No.5, pp. 333-345, 2001.
  10. [10] J. I. Park, C. B. Partridge, and M. W. Spong, “Neural network-based state prediction for strategy planning of an air hockey robot,” J. of Robotic Systems, Vol.18, No.4, pp. 187-196, 2001.
  11. [11] M. Ogawa, K. Ikeuchi, Y. Sato, S. Kudoh, T. Tomizawa, T. Suehiro, and S. Shimizu, “Towards air hockey robot with tactics – statistical analysis from measurement of eye movement,” 2012 IEEE Int. Conf. on Mechatronics and Automation, pp. 34-39, 2012.
  12. [12] H. Shimada, Y. Kutsuna, S. Kudoh, and T. Suehiro, “A two-layer tactical system for an air-hockey-playing robot,” 2017 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), pp. 6985-6990, 2017.
  13. [13] A. AlAttar, L. Rouillard, and P. Kormushev, “Autonomous air-hockey playing cobot using optimal control and vision-based bayesian tracking,” Annual Conf. Towards Autonomous Robotic Systems, pp. 358-369, 2019.
  14. [14] A. Namiki, S. Matsushita, T. Ozeki, and K. Nonami, “Hierarchical processing architecture for an air-hockey robot system,” 2013 IEEE Int. Conf. on Robotics and Automation, pp. 1187-1192, 2013.
  15. [15] T. Senoo, Y. Yamakawa, Y. Watanabe, H. Oku, and M. Ishikawa, “High-speed vision and its application systems,” J. Robot. Mechatron., Vol.26, No.3, pp. 287-301, 2014.
  16. [16] S. Hu, M. Jiang, T. Takaki, and I. Ishii, “Real-time monocular three-dimensional motion tracking using a multithread active vision system,” J. Robot. Mechatron., Vol.30, No.3, pp. 453-466, 2018.
  17. [17] T. Senoo, Y. Yamakawa, S. Huang, K. Koyama, M. Shimojo, Y. Watanabe, L. Miyashita, M. Hirano, T. Sueishi, and M. Ishikawa, “Dynamic intelligent systems based on high-speed vision,” J. Robot. Mechatron., Vol.31, No.1, pp. 45-56, 2019.
  18. [18] A. Namiki and T. Ozeki, “Vision-based optimal control for an air-hockey robot system,” 2017 IEEE 7th Annual Int. Conf. on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER), pp. 1176-1181, 2017.
  19. [19] K. Igeta and A. Namiki, “Algorithm for optimizing attack motions for air-hockey robot by two-step look ahead prediction,” 2016 IEEE/SICE Int. Symposium on System Integration (SII), pp. 465-470, 2016.
  20. [20] M. Kaneko and A. Namiki, “Real-time player’s posture measurement system for air-hockey robot,” 2018 IEEE Int. Conf. on Robotics and Biomimetics (ROBIO), pp. 1353-1358, 2018.
  21. [21] S. Fukuda, K. Tadokoro, and A. Namiki, “Motion strategy using opponent player’s serial learning for air-hockey robots,” 2021 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), pp. 952-957, 2021.
  22. [22] A. Sharon, N. Hogan, and D. E. Hardt, “High bandwidth force regulation and inertia reduction using a macro/micro manipulator system,” Proc. of 1988 IEEE Int. Conf. on Robotics and Automation, pp. 126-132, 1988.
  23. [23] K. Nagai and T. Yoshikawa, “Grasping and manipulation by arm/multifingered-hand mechanisms,” Proc. of 1995 IEEE Int. Conf. on Robotics and Automation, pp. 1040-1047, 1995.
  24. [24] S. Huang, N. Bergström, Y. Yamakawa, T. Senoo, and M. Ishikawa, “High-performance robotic contour tracking based on the dynamic compensation concept,” 2016 IEEE Int. Conf. on Robotics and Automation (ICRA), pp. 3886-3893, 2016.

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

Last updated on Dec. 01, 2022