Learning sensor network topology through Monte Carlo expectation maximization

Proceedings - IEEE International Conference on Robotics and Automation

Volumn 2005, Issue , 2005, Pages 4581-4587

  Marinakis, Dimitri ^a   Dudek, Gregory ^a   Fleet, David J ^b  

^a MCGILL UNIVERSITY   (Canada)

^b UNIVERSITY OF TORONTO   (Canada)

Author keywords

Expectation maximization; Learning; Markov chain Monte Carlo; Sensor networks

Indexed keywords

GRAPH THEORY; MARKOV PROCESSES; MONTE CARLO METHODS; OPTIMIZATION; TOPOLOGY; WIRELESS TELECOMMUNICATION SYSTEMS;

MARKOV CHAIN MONTE CARLO; SENSOR NETWORKS;

LEARNING SYSTEMS;

EID: 33846155236     PISSN: 10504729     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ROBOT.2005.1570826     Document Type: Conference Paper

References (31)

1. N. Bulusu, D. E. strin, L. Girod, and J. Heidemann, "Scalable coordination for wireless sensor networks: self-configuring localization systems," in Sixth International Symposium on Communication Theory and Applications (ISCTA-01), Ambleside, Lake District, UK, July 2001.
2. N. Correal and N. Patwari, "Wireless sensor networks: Challenges and opportunities," in MPRG/Virglna Tech Wireless Symposium, 2001.
3. S. Capkun, M. Hamdi, and J.-P. Hubaux, "GPS-free positioning in mobile ad-hoc networks," in HICSS, 2001.
4. N. Patwari, A. Hero, M. Perkins, N. Correal, and R. O'Dea, "Relative location estimation in wireless sensor networks," in IEEE Transactions on Signal Processing, ser. 8, vol. 51, Aug 2003, pp. 2137-2148.
5. D. Niculescu and B. Nath, "Ad hoc positioning system (aps) using aoa," 2003.
6. N. B. Priyantha, A. Chakraborty, and H. Balakrishnan, "The cricket location-support system," in Mobile Computing and Networking, 2000, pp. 32-43.
7. A. Savvides, C. Han, and M. Strivastava, "Dynamic fine-grained localization in ad-hoc networks of sensors," in 7th annual international conference on Mobile computing and networking, Rome, Italy, 2001, pp. 166-179.
8. D. Moore, J. Leonard, D. Rus, and S. Teller, "Robust, distributed network localization with noisy range measurements," in Proc. of the Second ACM Conference on Embedded Networked Sensor Systems (SenSys '04) (To Appear), Baltimore, November 2004.
9. I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. A. Cayirci, "A survey on sensor networks," IEEE Communications Magazine, vol. 40, no. 8, pp. 102-114, August 2002.
10. Y. Xu, J. Heidemann, and D. Estrin, "Geography-informed energy conservation for ad hoc routing," in ACM/IEEE International Conference on Mobile Computing and Networking. Rome, Italy: USC/Information Sciences Institute, July 2001, pp. 70-84.
11. F. Kuhn, T. Moscibroda, and R. Wattenhofer, "Initializing newly deployed ad hoc and sensor networks," 2004.
12. M. Batalin, G. Sukhatme, and M. Hattig, "Mobile robot navigation using a sensor network," in IEEE International Conference on Robotics and Automation, vol. 1, New Orleans, Louisiana, April 26-May 1 2004, pp. 636-641.
13. S. Poduri and G. S. Sukhatme, "Constrained coverage for mobile sensor networks," in IEEE International Conference on Robotics and Automation, New Orleans, LA, May 2004, pp. 165-172.
14. M. Batalin and G. S. Sukhatme, "Coverage, exploration and deployment by a mobile robot and communication network," Telecommunication Systems Journal, Special Issue on Wireless Sensor Networks, vol. 26, no. 2, pp. 181-196, 2004.
15. O. Javed, Z. Rasheed, K. Shafique, and M. Shan, "Tracking across multiple cameras with disjoint views," in The Ninth IEEE International Conference on Computer Vision, Nice, France, 2003.
16. T. Ellis, D. Makris, and J. Black, "Learning a multicamera topology," in Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, Nice, France, October 2003, pp. 165-171.
17. D. Makris, T. Ellis, and J. Black, "Bridging the gaps between cameras," in IEEE Conference on Computer Vision and Pattern Recognition CVPR 2004, Washington DC, June 2004.
18. Y. Bar-Shalom, Ed., Multitarget multisensor trucking: advanced applications. Artech House, 1992, vol. II.
19. J. Liu, J. Liu, J. Reich, P. Cheung, and F. Zhao, "Distributed group management for track initiation and maintenance in target localization applications," in Proceedings of 2nd International Workshop on Information Processing in Sensor Networks (IPSN), April 2003.
20. M. Rosencrantz, G. Gordon, and S. Thrun, "Locating moving entities in indoor environments with teams of mobile robots," in Second international joint conference on Autonomous agents and multiagent systems, Melbourne, Australia, 2003, pp. 233-240.
21. J. Shin, L. J. Guibas, and F. Zhao, "A distributed algorithm for managing multi-target identities in wireless ad-hoc sensor networks," in Information Processing in Sensor Networks Second International Workshop, IPSN 2003, Palo Alto, CA, April 2003, pp. 223-238.
22. C. Rasmussen and G. Hager, "Probabilistic data association methods for tracking multiple and compound visual objects," in IEEE Trans. Pattern Analysis and Machine Intelligence, 2001.
23. T. Yu and Y. Wu, "Collaborative tracking of multiple targets," in IEEE Conf. on Computer Vision and Pattern Recognition (CVPR 2004), Washington, DC, June 2004.
24. H. Pasula, S. Russell, M. Ostland, and Y. Ritov, "Tracking many objects with many sensors," in IJCAI-99, Stockholm, 1999.
25. A. Dempster, N. Laird, and D. Rubin, "Maximum likelihood from incomplete data via the EM algorithm," Journal of the Royal Statistical Society, 1977.
26. S. Thrun, D. Fox, and W. Burgard, "A probabilistic approach to concurrent mapping and localization for mobile robots," Machine Learning and Autonomous Robots (joint issue), 1998.
27. G. Wei and M. Tanner, "A monte-carlo implementation of the EM algorithm and the poor man's data augmentation algorithms," Journal of the American Statistical Association, vol. 85(411), pp. 699-704, 1990.
28. F. Dellaert, S. Seitz, C. Thorpe, and S. Thum, "EM, MCMC, and chain flipping for structure from motion with unknown correspondence," Machine Learning, special issue on Markov chain Monte Carlo method, vol. 5, pp. 45-7, 2003.
29. D. Tregouet, S. Escolano, L. Tiret, A. Mallet, and J. L. Golmard, "A new algorithm for haplotype-based association analysis:the stochastic-EM algorithm," Annals of Human Genetics, vol. 68, no. 165, March 2004.
30. M. Tanner, Tools for Statistical Inference, 3rd ed. New York: Springer Verlag, 1996.
31. J. Jonasson and O. Schramn, "On the cover time of planar graphs," in Electronic Communications in Probability, 2000, pp. 85-90.