Building an Intelligent Home Space for Service Robot Based on Multi-Pattern Information Model and Wireless Sensor Networks

Fei Lu, Guohui Tian, Fengyu Zhou, Yinghua Xue, Baoye Song

School of Control Science and Engineering, Shandong University, Jinan, China.

DOI: 10.4236/ica.2012.31011                

Abstract

This paper is concerned with constructing a prototype intelligent home environment for home service robot. In this environment, multi-pattern information can be represented by some intelligent artificial marks. Light-packs service robots can provide reliable and intelligent service by interacting with the environment through the wireless sensor networks. The intelligent space consists the following main components: smart devices with intelligent artificial mark; home server that connects the smart device and maintains the information through wireless sensor network; and the service robot that perform tasks in collaboration with the environment. In this paper, the multi-pattern information model is built, the construction of wireless sensor networks is presented, the smart and agilely home service is introduced. Fi- nally, the future direction of intelligent space system is discussed.

Keywords

Intelligent Home Environment; Service Robot; Artificial Mark; Wireless Sensor Networks

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	G. H. Tian, “Wide Future for Home Service Robot Research,” International Academic Developments, No. 1, 2007, pp. 28-29.
[2]	S.-H. Baeg, J.-H. Park, J. Koh, et al., “Building a Smart Home Environment for Service Robots Based on RFID and Sensor Networks,” International Conference on Control, Automation and Systems, Seoul Korea, 17-20 October 2007, pp. 1078-1082.
[3]	G. H. Tian, X. L. Li, S. P. Zhao, et al., “Research and Development of Intelligent Space Technology for Home Service Robot,” Journal of Shandong University: Engineering Science, Vol. 37, No. 5, 2007, pp. 53-59.
[4]	J.-H. Lee and H. Hashimoto, “Intelligent Space,” Proceedings of the IEEE International Conference on Intelligent Robots and Systems, Takamatsu, October 30-5 November 2000, pp. 1358-1363.
[5]	J.-H. Lee, N. Ando and H. Hashimoto, “Design Policy of Intelligent Space,” Proceedings of the IEEE International Conference on Systems, Man, and Cyberneticsi, Tokyo, 12-15 October 1999, pp. 1077-1082.
[6]	R. Katsuki, J. Ota, T. Mizuta, T. Kito, T. Arai, et al., “Design of an Artificial Mark to Determine 3D Pose by Monocular Vision,” IEEE International Conference on Robotics and Automation, Taipei, 14-19 September 2003, pp. 995-1000.
[7]	R. Katsuki, J. Ota, Y. Tamura, T. Mizuta, T. Kito, et al., “Handling of Objects with Marks by a Robot,” IEEE/RSJ International Conference on Intelligent Robots and Systems, Las Vegas, 27-31 October 2003, pp. 130-135.
[8]	H.-T. Xue, G.-H. Tian, X.-L. Li and F. Lu, “Application of the QR Code for Various Object Identification and Manipulation,” Journal of Shandong University (Engineering Science), Vol. 37, No. 6, 2007, pp. 25-30.
[9]	D. Scharstein and A. J. Briggs, “Real-time Recognition of Self-Similar Landmarks,” Image and Vision Computing, Vol. 19, No. 11, 2001, pp. 763-772. doi:10.1016/S0262-8856(00)00105-0
[10]	B. Zitova and J. Flusser, “Landmark Recognition Using Invariant Features,” Pattern Recognition Letters, Vol. 20, No. 5, 1999, pp. 541-547. doi:10.1016/S0167-8655(99)00031-8
[11]	D. Liu and X.-Q. Gao, “Research on Algorithm of Processing and Identification of QR Barcode Image,” Information Technology, Vol. 28, No. 1, 2004, pp. 61-63.
[12]	N. Strobel, S. Spors and R. Rabenstein, “Joint AudioVideo Object Localization and Tracking,” IEEE Signal Processing Magazine, Vol. 18, No. 1, 2001, pp. 22-31. doi:10.1109/79.911196
[13]	C. Cerrada, S. Salamanca, A. Adan, E. Perez, J.-A. Cerrada and I. Abad, “Improved Method for Object Recognition in Complex Scenes by Fusioning 3-D Information and RFID Technology,” IEEE Transactions on Instrumentation and Measurement, Vol. 58, No. 10, 2009, pp. 3473-3480. doi:10.1109/TIM.2009.2018000
[14]	T. Kim, J. Shin and S. Tak, “Cell Planning for Indoor Object Tracking Based on RFID,” International Conference on Mobile Data Management: Systems, Services and Middleware, Taipei, 18-21 May 2009, pp. 709-713.
[15]	S. Roh, H. and R. Choi, “3-D Tag-Based RFID System for Recognition of Object,” IEEE Transactions on Automation Science and Engineering, Vol. 6, No. 1, 2009, pp. 55-65. doi:10.1109/TASE.2008.2008119
[16]	P. Kamol, S. Nikolandis, R. Ueda and T. Arai, “RFID Based Object Localization System Using Ceiling Cameras with Particle Filter,” International Conference on Future Generation Communication and Networking, Jeju Island, 6-8 December 2007, pp. 37-42.
[17]	Y. H. Xue, G. H. Tian, R. K. Li and H. T. Jiang, “A New Object Search and Recognition Method Based on Artificial Object Mark in Complex Indoor Environment,” The 8th World Congress on Intelligent Control and Automation, Jinan, 7-9 July 2010, pp. 6648-6653.
[18]	D. Smith and S. Singh, “Approaches to Multisensor Data Fusion in Target Tracking: A Survey,” IEEE Transactions on Knowledge and Data Engineering, Vol. 18, No. 12, 2006, pp. 1696-1710. doi:10.1109/TKDE.2006.183
[19]	H. S. Carvalho, W. B. Heinzelman, A. L. Murphy, et al., “ A General Data Fusion Architecture,” Proceedings of the IEEE International Conference on Information Fusion, Queensland, 8-11 July 2003, pp. 1465-1472.
[20]	I. F. Akyildiz, W. Su and Y. Sankarasubramaniam, “Wireless Sensor Networks: A Survey,” Computer Networks, Vol. 38, No. 4, 2001, pp. 393-422. doi:10.1016/S1389-1286(01)00302-4
[21]	J.-S. Lee, Y.-W. Su and C.-C. Shen, “A Comparative Study of Wireless Protocols: Bluetooth, UWB, ZigBee, and Wi-Fi,” Proceedings of 33rd Annual Conference of the IEEE Industrial Electronics Society, Taipei, 5-8 November 2007, pp. 46-51.
[22]	D. Y. He, “The ZigBee Wirelesss Sensor Network in Medical Care Application,” International Conference on Computer, Mechatronics, Control and Electronic Engineering, Changchun, 24-26 August 2010, pp. 497-500.
[23]	E. Callaway, P. Gorday, L. Hester, et al., “Home Networking with IEEE 802.15.4 Developing Standard for Low-Rate Wireless Personal Area Networks,” IEEE Communications Magazine, Vol. 40, No. 8, 2002, pp. 70-77. doi:10.1109/MCOM.2002.1024418
[24]	K. Gill, S.-H. Yang, F. Yao and X. Lu, “A ZigBee-Based Home Automation System,” IEEE Transactions on Consumer Electronics, Vol. 55, No. 2, 2009, pp. 422-430. doi:10.1109/TCE.2009.5174403
[25]	M. Brejl and M. Sonka, “Object Localization and Border Detection Criteria Design in Edge-Based Image Segmentation: Automated Learning from Examples,” IEEE Transactions on Medical Imaging, Vol. 19, No. 10, 2000, pp. 973-985. doi:10.1109/42.887613
[26]	S. Ekvall, D. Kragic and F. Hoffmann, “Object Recognition and Pose Estimation Using Color Cooccurrence Histograms and Geometric Modeling,” Image and Vision Computing,” Vol. 23, No. 11, 2005, pp. 943-955. doi:10.1016/j.imavis.2005.05.006
[27]	M. Ulrich, C. Steger and A. Baumgartner, “Real-Time Object Recognition Using a Modified Generalized Hough Transform,” Pattern Recognition, Vol. 36, No. 11, 2003, pp. 2557-2570. doi:10.1016/S0031-3203(03)00169-9
[28]	P. Viola and M. Jones, “Rapid Object Detection Using a Boosted Cascade of Simple Features,” Proceedings. of International Conference on Computer Vision and Pattern Recognition, Kauai, 8-14 December 2001, pp. 511518.