Hostname: page-component-cd9895bd7-gxg78 Total loading time: 0 Render date: 2024-12-25T17:16:21.932Z Has data issue: false hasContentIssue false
  • English
  • Français

Increasing wireless reliability for autonomous mobile robots

Published online by Cambridge University Press:  08 August 2012

Joaquín López ,
Rafael Sanz ,
Miguel D. Cacho  and
Amador R. Diéguez
Joaquín López
Affiliation:
Department of Ingeniería de Sistemas y Automática, University of Vigo, 36200 Vigo, Spain
Rafael Sanz*
Affiliation:
Department of Ingeniería de Sistemas y Automática, University of Vigo, 36200 Vigo, Spain
Miguel D. Cacho
Affiliation:
Department of Ingeniería de Sistemas y Automática, University of Vigo, 36200 Vigo, Spain
Amador R. Diéguez
Affiliation:
Department of Ingeniería de Sistemas y Automática, University of Vigo, 36200 Vigo, Spain
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

There is an increasing popularity of mobile robot applications over the Internet. Robots need some kind of wireless communication to receive commands and transmit information to users. This paper describes the problems encountered to keep the mobile robots connected and the solutions adopted. The first problem was related to delays and the very low throughput that occur when the robot roams to a new access point. Most commercial systems currently installed implement proprietary solutions with different behaviors. Here, a simple and device-independent solution for mobile robot applications is proposed. The second problem is the lack of wireless coverage in some areas of buildings. The solutions adopted for these problems are based on coverage maps.

Keywords

Mobile roboticsWireless LANRoamingCoverage mapsNavigation
Type
Articles
Information
Robotica , Volume 31 , Issue 3 , May 2013 , pp. 405 - 416
Copyright
Copyright © Cambridge University Press 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Liu, P. X., Meng, M.Q-H. and Yang, S. X., “Data communications for Internet robots,” Auton. Robots 15 (3), 213–223 (2003).CrossRefGoogle Scholar
2.Simmons, R., Fernández, J. L., Goodwin, R., Koenig, S. and O'Sullivan, J., “Lessons learned from Xavier,” Robot. Autom. Mag. 7, 33–39 (2000).CrossRefGoogle Scholar
3.Wu, D., Ogai, H., Yeh, Y., Hirai, K., Abe, T. and Sato, G., “Pipe inspection robot using a wireless communication system,” Artif. Life Robot. 14, 154–159 (2009).CrossRefGoogle Scholar
4.Kim, Y.-G., Kim, H.-K., Yoon, S.-H., Lee, S.-G. and Lee, K.-D., “Home Security Robot Based on Sensor Network,” In: Proceedings of the. SICE-ICASE 2006 International Joint Conference, Seoul, Korea (2006) pp. 5977–5982.CrossRefGoogle Scholar
5.Burgard, W., Cremers, A. B., Fox, D., Hähnel, D., Lakemeyer, G., Schulz, D., Steiner, W. and Thrun, S., “Experiences with an interactive museum tour-guide robot,” Artif. Intell. 114, 3–55 (1999).CrossRefGoogle Scholar
6.Wang, Z., Liu, L. and Zhou, M., “Protocols and applications of ad-hoc robot wireless communication networks: An overview,” Int. J. Intell. Control Syst. 10, 296–303 (2005).Google Scholar
7.Wang, Z., Zhou, M. and Ansari, N., “Ad-hoc Robot Wireless Communication,” In: Proceedings of the. IEEE International Conference on Systems, Man and Cybernetics, Washington, D.C., USA (2003) pp. 4045–4050.Google Scholar
8.Kaemarungsi, K. and Krishnamurthy, P., “Modeling of Indoor Positioning Systems Based on Location Fingerprinting,” In: Proceedings of the IEEE Twenty-Third Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM '04), Hong Kong, China (2004) pp. 1012–1022.Google Scholar
9.IEEE Computer Society, ISO/IEC 8802-11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications (IEEE, New York, 1999).Google Scholar
10.Fernández, J. L., Losada, D. P. and Sanz, R., “Enhancing Building Security Systems with Autonomous Bobots,” In: Proceedings of the 2008 IEEE International Conference on Technologies for Practical Robot Applications, Boston, MA, USA (2008) pp. 19–25.Google Scholar
11.Fernández, J. L., Sanz, R., Paz, E. and Alonso, C., “Using hierarchical binary Petri nets to build robust mobile robot applications: RoboGraph,” In: Proceedings of the IEEE International Conference on Robotics and Automations (ICRA 2008), Pasadena, CA, USA (2008) pp. 1372–1377.Google Scholar
12.Yap, C., Qi, E., Sood, K., Bangolae, S. and Bell, C., “Issues with Real-Time Streaming Applications Roaming in QoS-Based Secure IEEE 802.11 WLANs,” In: Proceedings of the 2nd International Conference on Mobile Technology, Applications and Systems, Boston, MA, USA (2005) pp. 1–7.Google Scholar
13.Renjish Kumar, K. R., “Service Roaming over Mobile Networks: A Reality Check,” In: Proceedings of the IEEE International Conference on Communications, Glasgow, Scotland (2007) pp. 2058–2063.Google Scholar
14.Sarkar, T. K., Ji, Z., Kim, K., Medouri, A. and Salazar-Palma, M., “A survey of various propagation models for mobile communication,” IEEE Antennas Propag. Mag. 45, 51–82 (2003).CrossRefGoogle Scholar
15.Iskander, M. F. and Yun, Z., “Propagation prediction models for wireless communication systems,” IEEE Trans. Microw. Theory Tech. 50, 662–673 (2002).CrossRefGoogle Scholar
16.Hills, A., Schlegel, J. and Jenkins, B., “Estimating signal strengths in the design of an indoor wireless network,” IEEE Trans. Wirel. Comm. 3, 17–19 (2004).CrossRefGoogle Scholar
17.Cheon, C., Liang, G. and Bertoni, H. L., “Simulating radio channel statistics for different building environments,” IEEE J. Sel. Areas Commun. 19, 2191–2200 (2001).CrossRefGoogle Scholar
18.Bose, A. and Foh, C. H., “Practical Path Loss Model For indoor WiFi Positioning Enhancement,” In: Proceedings of the 6th International Conference on Information, Communications & Signal Processing, Singapore, Singapore (2007), pp. 1–5.Google Scholar
19.Matellán, V., Cañas, J. M. and Serrano, O., “WiFi localization methods for autonomous robots,” Robotica 24, 455–461 (2006).Google Scholar
20.Kotanen, A., Hännikäinen, M., Leppäkoski, H. and Hämäläinen, T. D., “Positioning with IEEE 802.11b Wireless LAN,” In: Proceedings of the 14th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC2003), Beijing, China (2003) pp. 2218–2222.Google Scholar
21.Bonasso, R. P., Kortenkamp, D., Miller, D. P. and Slack, M., “Experiences with an architecture for intelligent, reactive agents,” J. Exp. Theor. Artif. Intell. 9, 237–256 (1995).CrossRefGoogle Scholar
22.Montemerlo, M., Roy, N. and Thrun, S., “Perspectives on Standardization in Mobile Robot Programming: The Carnegie Mellon Navigation (CARMEN) Toolkit,” In: Proceedings of the. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003), Las Vegas, Nevada, USA (2003) pp. 2436–2441.Google Scholar
23.Diéguez, A. R., Sanz, R. and Fernández, J. L., “A global motion planner that learns from experience for autonomous mobile robots,” Robot. Comput. Integr. Manuf. 23, 544–552 (2007).CrossRefGoogle Scholar
24.Fernández, J. L., Sanz, R., Benayas, J. A. and Diéguez, A. R., “Improving collision avoidance for mobile robots in partially known environments: the beam curvature method,” Robot. Auton. Syst. 46, 205–219 (2004).CrossRefGoogle Scholar
25.Fernández, J. L., Souto, M. J., Losada, D. P., Sanz, R. and Paz, E., “Communication Framework or Sensor-Actuator Data in Mobile Robots,” In: Proceedings of the IEEE International Symposium on Industrial Electronics (ISIE 2007), Vigo, Spain (2007) pp. 1502–1507.CrossRefGoogle Scholar
26.Simmons, R., “The interprocess communications system (IPC),” available at: http://www.cs.cmu.edu//afs/cs/project/TCA/www/ipc/ipc.html (1998) online Accessed July 25, 2012.Google Scholar
27.IEEE Computer Society, LAN/MAN Standards Committee, IEEE Std 802.11-2007, Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications (IEEE, New York, Jun. 2007).Google Scholar
28.Zepernick, H.-J. and Wysocki, T. A., “Multipath Channel Parameters for the Indoor Radio at 2.4 GHz ISM band,” In: Proceedings of the IEEE 49th Vehicular Technology Conference, Houston, Texas, USA (1999) pp. 190–193.Google Scholar
29.Agelet, F. A., Formella, A., Rábanos, J. M. H., Vicente, F. I. and Fontán, F. P., “Efficient ray-tracing acceleration techniques for radio propagation modeling,” IEEE Trans. Veh. Technol. 49, 2089–2104 (2000).CrossRefGoogle Scholar
30.Iskander, M. F., Yun, Z. and Zhang, Z., “Outdoor/Indoor Propagation Modeling for Wireless Communications Systems,” In: Proceedings of the IEEE Antennas and Propagation Society International Symposium, Boston, MA, USA (2001) pp. 150–153.Google Scholar
31.Tarng, J. H. and Liu, T. R., “Effective models in evaluating radio coverage on single floors of multifloor building,” IEEE Trans. Veh. Technol. 48, 782–789 (1999).CrossRefGoogle Scholar
32.Neskovic, A., Neskovic, N. and Paunovic, G., “Modern approaches in modeling of mobile radio systems propagation environment,” IEEE Commun. Surv. 3, 2–12 (2000).CrossRefGoogle Scholar
33.Thrun, S., Fox, D., Burgard, W., and Dellaert, F., “Robust Monte Carlo localization for mobile robots,” Artif. Intell. 101, 99–141, 2000.Google Scholar
34.López, J., Perez, D. and Zalama, E., “A framework for building mobile single and multi-robot applications,” Robot. Auton. Syst. 59, 151–162, (2011) available at: http://webs.uvigo.es/vigobot/.CrossRefGoogle Scholar
35.Bose, A. and Foh, C. H., “Practical Path Loss Model for Indoor WiFi Positioning Enhancement,” In: Proceedings of the 6th International Conference on Information, Communications & Signal Processing, Singapore, Singapore (2007) pp. 1–5.Google Scholar