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Range-only fuzzy Voronoi-enhanced localization of mobile robots in wireless sensor networks

Published online by Cambridge University Press:  12 December 2011

D. Herrero  and
H. Martínez
D. Herrero*
Affiliation:
Department of Information and Communications Engineering, University of Murcia, 30100 Espinardo, Murcia, Spain
H. Martínez
Affiliation:
Department of Information and Communications Engineering, University of Murcia, 30100 Espinardo, Murcia, Spain
*
*Corresponding author. E-mail: dherrero@um.es
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Summary

Wireless Sensor Network (WSN) localization has shown a growing research interest, thanks to the expected proliferation of WSN applications. This work is focused on indoor localization of a mobile robot in a WSN using only inter-node range measurements, which are estimated by radio frequency signal strength attenuation. These measurements are affected by different sources of uncertainty that make them highly noisy and unreliable. The proposed approach makes use of fuzzy logic for modeling and dealing with such uncertain information. Besides, the position estimation is enhanced using a rough description of indoor environment. The experiments show that the proposed localization approach (i) is fault-tolerant, (ii) results feasible in low-density WSNs, and (iii) provides better position estimations than well-known localization methods when the position measurements are affected by high uncertainty.

Keywords

Self-localizationFuzzy logicAutonomous robotsWireless sensor networks
Type
Articles
Information
Robotica , Volume 30 , Issue 7 , December 2012 , pp. 1063 - 1077
Copyright
Copyright © Cambridge University Press 2011

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References

1. Yick, J., Mukherjee, B. and Ghosal, D., “Wireless sensor network survey,” Comput. Netw. 52 (12), 2292–2330 (2008).CrossRefGoogle Scholar
2. Reich, J. and Sklar, E., “Robot-Sensor Networks for Search and Rescue,” IEEE International Workshop on Safety, Security and Rescue Robotics (SSRR'06), Gaithersburg, MD, USA (2006).Google Scholar
3. Kumar, V., Rus, D. and Singh, S., “Robot and sensor networks for first responders,” IEEE Pervasive Comput. 3 (4), 24–33 (2004).CrossRefGoogle Scholar
4. Barbosa, M., Bernardino, A., Figueira, D., Gaspar, J., Goncalves, N., Lima, P. U., Moreno, P., Pahliani, A., Santos-Victor, J., Spaan, M. and Sequeira, J., “ISRobotNet: A Testbed for Sensor and Robot Network Systems,” In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'09), St. Louis, MO, USA (2009) pp. 2827–2833.Google Scholar
5. Broxvall, M., Gritti, M., Saffiotti, A., Seo, B. S. and Cho, Y. J., “PEIS Ecology: Integrating Robots into Smart Environments,” In: IEEE International Conference on Robotics and Automation (ICRA'06), Orlando, FL, USA (2006) pp. 212–218.Google Scholar
6. Ward, A., Jones, A. and Hopper, A., “A new location technique for the active office,” IEEE Pers. Commun. 4 (5), 42–47 (1997).CrossRefGoogle Scholar
7. Niculescu, D. and Nath, B., “Ad hoc Positioning System (APS) Using AOA,” In: IEEE INFOCOM 2003, San Francisco, CA, USA (2003) pp. 1734–1743.Google Scholar
8. Xu, Y., Ouyang, Y., Le, Z., Ford, J. and Makedon, F., “Mobile Anchor-Free Localization for Wireless Sensor Networks,” In: Proceedings of Distributed Computing in Sensor Systems (DCOSS'07), Santa Fe, NM, USA, Lecture Notes in Computer Science, vol. 4549 (2007) pp. 96–109.CrossRefGoogle Scholar
9. Menegatti, E., Zanella, A., Zilli, S., Zorzi, F. and Pagello, E., “Range-Only SLAM with a Mobile Robot and a Wireless Sensor Networks,” In: Proceedings of IEEE International Conference on Robotics and Automation (ICRA'09), Kobe, Japan (2009) pp. 1699–1705.Google Scholar
10. Batalin, M. A., Sukhatme, G. S. and Hattig, M., “Mobile Robot Navigation Using a Sensor Network,” In: Proceedings of IEEE International Conference on Robotics and Automation (ICRA'04), New Orleans, LA, USA (2004) pp. 636–641.Google Scholar
11. Enriquez, G. and Hashimoto, S., “Wireless Sensor Network-Based Navigation for Human-Aware Guidance Robot,” In: Proceedings of IEEE International Conference on Robotics and Biomimetics (ROBIO'08), Bangkok, Tailand (2008) pp. 2034–2039.Google Scholar
12. Gao, J., “Geometric Routing in Wireless Sensor Networks,” In: Guide to Wireless Sensor Networks (Misra, S., Woungang, I. and Misra, S. C., eds.) (Springer, London, 2009) pp. 113–157.CrossRefGoogle Scholar
13. Yang, C., Li, C. and Xiao, J., “Location-based design for secure and efficient wireless sensor networks,” Comput. Netw. 52 (16), 3119–3129 (2008).CrossRefGoogle Scholar
14. Saffiotti, A., “The uses of fuzzy logic in autonomous robot navigation,” Soft Comput. 1 (4), 180–197 (1997).CrossRefGoogle Scholar
15. Saffiotti, A., Konolige, K. and Ruspini, E. H., “A multivalue-logic approach to integrating planning and control,” Artif. Intell. 76 (1–2), 481–526 (1995).CrossRefGoogle Scholar
16. Herrero-Pérez, D. and Martínez-Barberá, H., “Indoor fuzzy self-localization using fuzzy segments,” J. Phys. Agents 1 (1), 45–54 (2007).Google Scholar
17. Lorincz, K. and Welsh, M., “MoteTrack: A Robust, Decentralized Approach to RF-Based Location Tracking,” In: Proceedings of Conference on Location and Context-Awareness (LoCA'05), Munich, Germany (2005) pp. 489–503.Google Scholar
18. Herrero-Pérez, D., Martínez-Barberá, H., Leblanc, K. and Saffiotti, A., “Fuzzy uncertainty modeling for grid-based localization of mobile robots,” Int. J. Approx. Reason. 51 (8), 912–932 (2010).CrossRefGoogle Scholar
19. Buschka, P., Saffiotti, A. and Wasik, Z., Fuzzy Landmark-Based Localization for a Legged Robot,” In: Proceedings of IEEE/RSJ International Conference on Intelligent Robotic Systems (IROS'00), Takamatsu, Japan (2000) pp. 1205–1210.Google Scholar
20. Herrero-Pérez, D., Martínez-Barberá, H. and Saffiotti, A., “Fuzzy Self-Localization Using Natural Features in the Four-Legged League,” In: Proceedings of Conference on Robot Soccer World Cup VIII, Lisbon, Portugal, Lecture Notes in Artificial Intelligence, vol. 3276 (2005) pp. 110–121.Google Scholar
21. Lazos, L. and Poovendran, R., “SeRLoc: Robust localization for wireless sensor networks,” ACM Trans. Sensor Netw. 1 (1), 73–100 (2005).CrossRefGoogle Scholar
22. Peng, R. and Sichitiu, M. L., “Robust, Probabilistic, Constraint-Based Localization for Wireless Sensor Networks,” In: Proceedings of IEEE Conference on Sensor and Ad Hoc Communications and Networks (SECON'05), Santa Clara, CA, USA (2005) pp. 541–550.Google Scholar
23. Rudafshani, M. and Datta, S., “Localization in Wireless Sensor Networks,” In: Proceedings of International Conference on Information Processing in Sensor Networks (IPSN'07), Cambridge, MA, USA (2007) pp. 51–60.CrossRefGoogle Scholar
24. He, T., Huang, C., Blum, B. M., Stankovic, J. A. and Abdelzaher, T., “Range-Free Localization Schemes for Large Scale Sensor Networks,” In: Proceedings of International Conference on Mobile Computing and Networking (MobiCom'03), San Diego, CA, USA (2003) pp. 81–95.CrossRefGoogle Scholar
25. Priyantha, N., Chakraborty, A. and Balakrishnan, H., “The Cricket Location-Support System,” In: Proceedings of International Conference on Mobile Computing and Networking (MobiCom'00), Boston, MA, USA (2000) pp. 32–43.CrossRefGoogle Scholar
26. Teller, S., Chen, K. and Balakrishnan, H., “Pervasive pose-aware applications and infrastructure,” IEEE Comput. Graph. Appl. 23 (4), 14–18 (2003).CrossRefGoogle Scholar
27. Patwari, N., Ash, J. N., Kyperountas, S., Hero, A. O. III, Moses, R. L. and Correal, N. S., “Locating the nodes: Cooperative localization in wireless sensor networks,” IEEE Signal Process. Mag. 22 (4), 54–69 (2005).CrossRefGoogle Scholar
28. Fox, D., Burgard, W. and Thrun, S., “Markov localization for mobile robots in dynamic environments,” J. Artif. Intell. Res. 11, 391–427 (1999).CrossRefGoogle Scholar
29. Ramadurai, V. and Sichitiu, M. L., Localization in Wireless Sensor Networks: A Probabilistic Approach,” In: Proceedings of International Conference on Wireless Networks (ICWN'03), Las Vegas, NV, USA (2003) pp. 275–281.Google Scholar
30. Ladd, A. M., Bekris, K. E., Rudys, A., Kavraki, L. E. and Wallach, D. S., “On the feasibility of using wireless ethernet for indoor localization,” IEEE Trans. Robot. Autom. 20 (3), 555–559 (2004).CrossRefGoogle Scholar
31. Djugash, J., Singh, S. and Corke, P., “Further Results with Localization and Mapping Using Range from Radio,” In: Proceedings of International Conference on Field and Service Robotics (FSR'05), Port Douglas, Australia (2005) pp. 231–242.Google Scholar
32. Matellán-Olivera, V., Cañas-Plaza, J. M. and Serrano-Serrano, O., “Wifi localization methods for autonomous robots,” Robotica 24 (4), 455–461 (2006).CrossRefGoogle Scholar
33. Kurth, D., Kantor, G. and Singh, S., “Experimental Results in Range-Only Localization with Radio,” In: Proceedings of IEEE/RSJ International Conference on Intelligent Robotic Systems (IROS'03), Las Vegas, NV, USA (2003) pp. 974–979.Google Scholar
34. Letchner, J., Fox, D. and LaMarca, A., “Large-Scale Localization from Wireless Signal Strength,” In: Proceedings of AAAI Conference on Artificial Intelligence (AAAI'05), Pittsburgh, PA, USA (2005) pp. 15–20.Google Scholar
35. Canovas, J. P., LeBlanc, K. and Saffiotti, A., “Robust Multi-Robot Object Localization Using Fuzzy Logic,” In: Proceedings of Robot Soccer World Cup VIII, Lisbon, Portugal, Lecture Notes in Artificial Intelligence, vol. 3276 (2005) pp. 247–261.Google Scholar
36. Oriolo, G., Ulivi, G. and Venditelli, M., “Real-time map building and navigation for autonomous mobile robots in unknown environments,” IEEE Trans. Syst. Man Cybern. B: Cybern. 3 (28), 316–333 (1998).CrossRefGoogle Scholar
37. Astrain, J. J., Villadangos, J., Garitagoitia, J. R., de Mendívil, J. R. González and Cholvi, V., “Fuzzy Location and Tracking on Wireless Networks,” In: Proceedings of ACM International Workshop on Mobility Management and Wireless Access (MOBIWAC'06), Torremolinos, Spain (2006) pp. 84–91.CrossRefGoogle Scholar
38. LeBlanc, K. and Saffiotti, A., “Multirobot object localization: A fuzzy fusion approach,” IEEE Trans. Syst. Man Cybern. B: Cybern. 39 (5), 1259–1276 (2009).CrossRefGoogle ScholarPubMed
39. Teuber, A. and Eissfeller, B., “WLAN Indoor Positioning Based on Euclidean Distances and Fuzzy Logic,” In: Proceedings of Workshop on Positioning, Navigation and Communication (WPNC'06), Hannover, Germany (2006) pp. 158–168.Google Scholar
40. Jetto, L., Longhi, S. and Venturini, G., “Development and experimental validation of an adaptive extended Kalman filter for the localization of mobile robots,” IEEE Trans. Robot. Autom. 15 (2), 219–229 (1999).CrossRefGoogle Scholar
41. Lin, H. H. and Tsai, C. C., “Improved global localization of an indoor mobile robot via fuzzy extended information filtering,” Robotica 26 (2), 241–254 (2008).CrossRefGoogle Scholar
42. Bahl, P. and Padmanabhan, V., “RADAR: An In-Building RF-Based User Location and Tracking System,” In: Proceedings of IEEE INFOCOM 2000, Tel-Aviv, Israel (2000) pp. 775–784.Google Scholar
43. Rappaport, T. S., Wireless Communications: Principles and Practice (Prentice Hall PTR, New York, 2001).Google Scholar
44. Zadeh, L. A., “Fuzzy sets,” Inf. Control 8 (3), 338–353 (1965).CrossRefGoogle Scholar
45. Zadeh, L. A., “Fuzzy sets as a basis for a theory of possibility,” Fuzzy Sets Syst. 1 (1), 3–28 (1978).CrossRefGoogle Scholar
46. Gelb, A., Applied Optimal Estimation (The MIT Press, Cambridge, MA, 1974).Google Scholar
47. Bloch, I. and Maître, H., “Fuzzy mathematical morphologies: A comparative study,” Pattern Recognit. 28 (9), 1341–1387 (1995).CrossRefGoogle Scholar
48. Bloch, I., “Duality vs. adjunction for fuzzy mathematical morphology and general form of fuzzy erosions and dilations,” Fuzzy Sets Syst. 160 (13), 1858–1867 (2009).CrossRefGoogle Scholar
49. Bloch, I., “Information combination operator for data fusion: A comparative review with classification,” IEEE Trans. Syst. Man Cybern. 26 (1), 52–67 (1996).CrossRefGoogle Scholar
50. Thrun, S., Fox, D., Burgard, W. and Dellaert, F., “Robust Monte Carlo localization for mobile robots,” Artif. Intell. 128 (1–2), 99–141 (2001).CrossRefGoogle Scholar
51. Doucet, A., Godsill, S. J. and Andrieu, C., “On sequential Monte Carlo sampling methods for Bayesian filtering,” Stat. Comput. 10 (3), 197–208 (2000).CrossRefGoogle Scholar
52. Doucet, A. and de Freitas, N., Sequential Monte Carlo in Practice (Springer-Verlag, New York, 2001).CrossRefGoogle Scholar
53. Stoleru, R., He, T. and Stankovic, J. A., “Walking GPS: A Practical Solution for Localization in Manually Deployed Wireless Sensor Networks,” In: IEEE International Conference on Local Computer Networks (LCN'04), Tampa, FL, USA, Tampa, FL, USA (2004) pp. 480–489.Google Scholar