JRM Vol.19 No.1 pp. 42-51
doi: 10.20965/jrm.2007.p0042


Detecting Feature of Haptic Interaction Based on Distributed Tactile Sensor Network on Whole Body

Tomoyuki Noda*,***, Takahiro Miyashita**,
Hiroshi Ishiguro*,**,***, Kiyoshi Kogure****,
and Norihiro Hagita**

*Pioneering Integrated Engineering, Osaka University

**Intelligent Robotics and Communication Laboratories, ATR

***Asada Synergistic Intelligence Project, ERATO, JST

****Knowledge Science Laboratories, ATR

November 1, 2005
September 25, 2006
February 20, 2007
distributed tactile sensor, haptic interaction, self-organized skin sensor network
To extract information about users contacting robots physically, the distribution density of tactile sensor elements, the sampling rate, and the resolution all must be high, increasing the volume of tactile information. In the self-organized skin sensor network we propose for dealing with a large number of tactile sensors embedded throughout a humanoid robot, each network node having a processing unit is connected to tactile sensor elements and other nodes. By processing tactile information in the network based on the situation, individual nodes process and reduce information rapidly in high sampling. They also secure information transmission routes to the host PC using a data transmission protocol for self-organizing sensor networks. In this paper, we verify effectiveness of our proposal through sensor network emulation and basic experiments in spatiotemporal calculation of tactile information using prototype hardware. As an emulation result of the self-organized sensor network, routes to the host PC are secured at each node, and a tree-like network is constructed recursively with the node as a root. As the basic experiments, we describe an edge detection as data processing and extraction for haptic interaction. In conclusion, local information processing is effective for detecting features of haptic interaction.
Cite this article as:
T. Noda, T. Miyashita, H. Ishiguro, K. Kogure, and N. Hagita, “Detecting Feature of Haptic Interaction Based on Distributed Tactile Sensor Network on Whole Body,” J. Robot. Mechatron., Vol.19 No.1, pp. 42-51, 2007.
Data files:
  1. [1] T. Miyashita, T. Tajika, K. Shinozawa, H. Ishiguro, K. Kogure, and N. Hagita, “Human Position and Posture Detection based on Tactile Information of the Whole Body,” In Proc. of IEEE/RSJ 2004 International Conference on Intelligent Robots and Systems Workshop (IROS’04 WS), Sep., 2004.
  2. [2] M. Inaba, Y. Hoshino, K. Nagasaka, T. Ninomiya, S. Kagami, and H. Inoue, “A Full-Body Tactile Sensor Suit Using Electrically Conductive Fabric and Strings,” Proc. 1996 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 96), Vol.2, pp. 450-457, 1996.
  3. [3] F. Naya, J. Yamato, and K. Shinozawa, “Recognizing Human Touching Behaviors using a Haptic Interface for a Pet-robot,” Proc. 1999 IEEE International Conference on Systems, Man, and Cybernetics (SMC’99), pp. II-1030-1034.
  4. [4] H. Iwata, H. Hoshino, T. Morita, and S. Sugano, “Force Detectable Surface Covers for Humanoid Robots,” Proc. 2001 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM’01), pp. 1205-1210, 2001.
  5. [5] H. Iwata and S. Sugano, “Whole-body covering tactile interface for human robot coordination,” Proceedings –IEEE International Conference on Robotics and Automation, Vol.4, pp. 3818-3824, 2002.
  6. [6] H. Shinoda, N. Asamura, T. Yuasa, M. Hakozaki, X. Wang, H. Itai, Y. Makino, and A. Okada, “Two-Dimensional Communication Technology Inspired by Robot Skin,” Proc. IEEE TExCRA 2004 (Technical Exhibition Based Conf. on Robotics and Automation), pp. 99-100, 2004.
  7. [7] A. Iwashita and M. Shimojo, “Development of a Mixed Signal LSI for Tactile Data Processing,” in Proc. of IEEE Int. Conf. on Systems, Man and Cybernetics 2004 (SMC2004), 2004.
  8. [8] Z. Pan, H. Cui, and Z. Zhu, “A Flexible Full-body Tactile Sensor of Low Cost and Minimal Connections,” Proc. 2003 IEEE International Conference on Systems, Man, and Cybernetics (SMC’03), Vol.3, pp. 2368-2373, 2003.
  9. [9] Y. Takahashi, K. Nishiwaki, S. Kagami, H. Mizoguchi, and H. Inoue, “High-speed Pressure Sensor Grid for Humanoid Robot Foot,” Proceedings of 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS2005), Edmonton, Canada, pp. 1097-1102, Aug., 2005.
  10. [10] H. Kawaguchi, T. Someya, T. Sekitani, and T. Sakurai, “Cut-and-Paste Customization of Organic FET Integrated Circuit and Its Application to Electronic Artificial Skin,” IEEE Journal of Solid-State Circuits, Vol.40, No.1, pp. 177-185, January, 2005.
  11. [11] D. B. Johnson, D. A. Maltz, A. Y. Hu, and J. G. Jetcheva, “The Dynamic Source Routing Protocol for Mobile Ad Hoc Networks,” Internet Draft, draft-ietf-manet-dsr-05.tst, 2001.
  12. [12] J. Heidemann, F. Silva, C. Intanagonwiwat, R. Govindan, D. Estrin, and D. Ganesan, “Building EfficientWireless Sensor Networks with Low-Level Naming,” Proceedings of SOSP 2001, Oct., 2001.
  13. [13] C. Intanagonwiwat, R. Govindan, and D. Estrin, “Directed diffusion: A scalable and robust communication paradigm for sensor networks,” In Proceedings of the Sixth Annual International Conference on Mobile Computing and Networking (MobiCOM ’00), Boston, Massachussetts, August, 2000.

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

Last updated on Apr. 19, 2024