Top > JRM > Motion Generation for a Sword-Fighting Robot Based on Quick De ...

single-rb.php

JRM Vol.27 No.5 pp. 543-551
doi: 10.20965/jrm.2015.p0543
(2015)

Paper:

Views over last 60 days: 1,419

Motion Generation for a Sword-Fighting Robot Based on Quick Detection of Opposite Player’s Initial Motions

Akio Namiki and Fumiyasu Takahashi

Graduate School of Engineering, Chiba University
1-33 Yayoi-cho, Inage-ku, Chiba-shi, Chiba 263-8522, Japan

Received:
April 8, 2015
Accepted:
August 20, 2015
Published:
October 20, 2015
Creative Commons License
Keywords:
entertainment robot, high-speed vision, human-robot interaction, ChangeFinder
Abstract
Defensive motion against attack
In this paper, we discuss how to generate defensive motions for a sword-fighting robot based on quick detection of the opposite player’s initial motions. Our sword-fighting robot system, which has a stereo high-speed vision system, recognizes both the position of a human player and that of the sword grasped by the robot’s hand. Further, it detects the moment when the human player initiates a move using ChangeFinder, which is a method of detecting change points. Next, using least squares method, it predicts the possible trajectories of the sword of the human player from the moment when the attack starts. Finally, it judges the type of the attack and generates an appropriate defensive motion. The effectiveness of the proposed algorithm is verified by experimental results.
Cite this article as:
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.
Data files:
References
  1. [1] M. Asada, M. Veloso, G. K. Kraetzschmar, and H. Kitano, “A review of robot world cup soccer research issues RoboCup: Today and tomorrow,” Experimental Robotics VI, Lecture Notes in Control and Information Sciences, Vol.250, pp. 369-378, 2000.
  2. [2] M. Matsushima, T. Hashimoto, M. Takeuchi, and F. Miyazaki, “A learning approach to robotic table tennis,” IEEE Trans. Robot. Autom., Vol.21, No.4, pp. 767-771, 2005.
  3. [3] Z. Zhang, D. Xu, and J. Yu, “Research and latest development of ping-pong robot player,” 7th World Congress on Intelligent Control Automation, pp. 4881-4886, 2008.
  4. [4] T. Senoo, A. Namiki, and M. Ishikawa, “High-Speed Batting Using a Multi-Jointed Manipulator,” IEEE Int. Conf. on Robotics and Automation, pp. 1191-1196, 2004.
  5. [5] M. Ishikawa, A. Namiki, T. Senoo, and Y. Yamakawa, “Ultra High-speed Robot Based on 1 kHz Vision System,” IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 5460-5461, 2012.
  6. [6] B. E. Bishop and M. W. Spong, “Vision-Based Control of an Air Hockey Playing Robot,” IEEE Control Systems Magazine, pp. 23-32, 1999.
  7. [7] M. Ogawa, S. Shimizu, T. Kadogawa, T. Hashizume, S. Kudoh, T. Suehiro, Y. Sato, and K. Ikeuchi, “Development of air hockey robot improving with the human players,” 37th Annual Conf. IEEE Industrial Electronics Society, pp. 3364-3369, 2011.
  8. [8] A. Namiki, S. Matsushita, T. Ozeki, and K. Nonami, “Hierarchical processing architecture for an air-hockey robot system,” IEEE Int. Conf. Robotics and Automation, pp. 1187-1192, 2013.
  9. [9] F. Takahashi and A. Namiki, “Development of a Sword-Fighting Robot Controlled by High-Speed Vision,” JSME Conf. on Robotics and Mechatronics, 1A1-D06, 2014 (in Japanese).
  10. [10] Y. Watanabe, T. Komuro, S. Kagami, and M. Ishikawa, “Multi-Target Tracking Using a Vision Chip and its Applications to Real-Time Visual Measurement,” J. of Robotics and Mechatronics, Vol.17, No.2, 2005.
  11. [11] H. Yang, T. Takaki, and I. Ishii, “Simultaneous Dynamics-Based Visual Inspection Using Modal Parameter Estimation,” J. of Robotics and Mechatronics, Vol.23, No.1, 2011.
  12. [12] Y. Liu, H. Gao, Q. Gu, T. Aoyama, T. Takaki, and I. Ishii, “High-Frame-Rate Structured Light 3-D Vision for Fast Moving Objects,” J. of Robotics and Mechatronics, Vol.26, No.3, 2014.
  13. [13] T. Senoo, Y. Yamakawa, Y. Watanabe, H. Oku, and M. Ishikawa, “High-Speed Vision and its Application Systems,” J. of Robotics and Mechatronics, Vol.26, No.3, 2014.
  14. [14] T. Kunz, P. Kingston, M. Stilman, and M. Egerstedt, “Dynamic Chess; Strategic Planning for Robot Motion,” IEEE Int. Conf. Robotics and Automation, pp. 3796-3803, 2011.
  15. [15] T. Kroger, K. Oslund, T. Jenkins, D. Torczynski, N. Hippenmeyer, R. B. Rusu, and O. Khatib, “JediBot-Experiments in Human-Robot Sword-Fighting,” ISER, Vol.88 of Springer Tracts in Advanced Robotics, pp. 155-166, 2012.
  16. [16] T. Kizaki and A. Namiki, “Two Ball Juggling with High-Speed Hand-Arm and High-Speed Vision System,” IEEE Int. Conf. on Robotics and Automation, pp. 1372-1377, 2012.
  17. [17] A. Namiki and N. Ito, “Ball Catching in Kendama Game by Estimating Grasp Conditions Based on a High-Speed Vision System and Tactile Sensors,” IEEE-RAS Int. Conf. on Humanoid Robots, pp. 634-639, 2014.
  18. [18] Y. Yamakawa, A. Namiki, and M. Ishikawa, “Dynamic High-speed Knotting of a Rope by a Manipulator,” Int. J. of Advanced Robotic Systems, Vol.10, 2013.
  19. [19] I. Ishii, T. Tatebe, Q. Gu, Y. Moriue, T. Takaki, and K. Tajima, “2000 fps Real-time Vision System with High-frame-rate Video Recording,” IEEE Int. Conf. Robotics and Automation, pp. 1536-1541, 2010.
  20. [20] G. R. Bradski, “Computer Vision Face Tracking For Use in a Perceptual User Interface,” Intel Technology Journal, 2nd Quarter, 1998.
  21. [21] J. Takeuchi and K. Ymanishi, “A Unifying framework for detecting outliners and change points from time series,” IEEE Trans. Knowledge and Data Engineering, Vol.18, No.4, pp. 482-492, 2006.

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

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

Last updated on Dec. 02, 2024