The sensor selection problem for bounded uncertainty sensing models

IEEE Transactions on Automation Science and Engineering

Volumn 3, Issue 4, 2006, Pages 372-381

  Isler, Volkan ^a,b   Bajcsy, Ruzena ^a,c  

^a IEEE   (United States)

^b Rensselaer Polytechnic Institute   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Estimation; Localization; Sensor fusion; Sensor selection; Target tracking

Indexed keywords

LOCALIZATION; SENSOR FUSION; SENSOR SELECTION; TARGET TRACKING;

ALGORITHMS; APPROXIMATION THEORY; ERROR COMPENSATION; INTERSECTIONS; MATHEMATICAL MODELS; UNCERTAIN SYSTEMS;

SENSORS;

EID: 33750058895     PISSN: 15455955     EISSN: None     Source Type: Journal    
DOI: 10.1109/TASE.2006.876615     Document Type: Article

References (23)

1. V. Isler and R. Bajcsy, "The sensor selection problem for bounded uncertainty sensing models," in Proc. 4th Int. Symp. Information Processing in Sensor Networks. Los Angeles, CA, Apr. 2005, pp. 151-158.
2. S. Thrun, "Robotic mapping: a survey," in Exploring Artificial Intelligence in the New Millenium, G. Lakemeyer and B. Nebel, Eds. San Mateo, CA: Morgan Kaufmann, 2002.
3. _, "A probabilistic online mapping algorithm for teams of mobile robots," Int. J. Robot. Res., vol. 20, no. 5, pp. 335-363, 2001.
4. J. Spletzer and C. Taylor, "Dynamic sensor planning and control for optimally tracking targets," Int. J. Robot. Res., vol. 22, no. 1, pp. 7-20, 2003.
5. J. Manyika and H. Durrant-Whyte, Data Fusion and Sensor Management: A Decentralized Information-Theoretic Approach, ser. Ellis Horwood Series Elect. Electron. Eng., 1994.
6. F. Zhao, J. Liu, J. Liu, L. Guibas, and J. Reich, "Collaborative signal and information processing: an information directed approach," Proc. IEEE, vol. 91, no. 8, pp. 1199-1209, Aug. 2003.
7. J. Liu, J. Reich, and F. Zhao, "Collaborative in-network processing for target tracking," Proc. EURASIP JASP, vol. 4, no. 378-391, 2003.
8. H. Wang, K. Yao, G. Pottie, and D. Estrin, "Entropy-based sensor selection heuristic for target localization," in Proc. 3rd Int. Symp. Information Processing in Sensor Networks, 2004, pp. 36-45.
9. E. Ertin, J. W. Fisher III, and L. C. Potter, "Maximum mutual information principle for dynamic sensor query problems," in Proc. 2nd Int. Workshop on Information Processing in Sensor Networks, 2003.
10. J. Liu, M. Chu, J. Liu, J. Reich, and F. Zhao, "Distributed state representation for tracking problems in sensor networks," in Proc. 3rd Int. Symp. Information Processing in Sensor Networks, 2004, pp. 234-242.
11. J. Aslam, Z. Butler, F. Constantin, V. Crespi, G. Cybenko, and D. Rus, "Tracking a moving object with a binary sensor network," in Proc. 1st Int. Conf. Embedded Networked Sensor Systems, CA, 2003, pp. 150-161.
12. V. Isler, J. Spletzer, S. Khanna, and C. Taylor, "Target tracking in sensor networks: The focus of attention problem," Comput. Vision Image Understanding J., vol. 100, pp. 225-246, Oct. 2005.
13. L. Doherty, K. S. J. Pister, and L. E. Ghaoui, "Convex position estimation in wireless sensor networks," in Proc. IEEE Infocom, Anchorage, AK, 2001, pp. 1655-1663.
14. A. Howard, M. J. Matarić, and G. S. Sukhatme, "Cooperative relative localization for mobile robot teams: An ego-centric approach," in Proc. Naval Research Laboratory Workshop on Multi-Robot Systems, Washington, D.C., Mar. 2003.
15. J. Spletzer, A. Das, R. Fierro, C. Taylor, V. Kumar, and J. Ostrowski, "Cooperative localization and control for multi-robot manipulation," in Proc. Conf. Intelligent Robots and Systems, 2001.
16. J. Spletzer and C. Taylor, "A bounded uncertainty approach to multi-robot localization," in Proc. Conf. Intelligent Robots and Systems, 2003, pp. 1258-1265.
17. D. Moore, J. Leonard, D. Rus, and S. Teller, "Robust distributed network localization with noisy range measurements," in Proc. 2nd ACM Conf. Embedded Networked Sensor Systems, Baltimore, MD, Nov. 2004.
18. M. R. Garey and D. S. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness. San Francisco, CA: Freeman, 1979.
19. "On finding a minimal enclosing parallelgram," Int. Comput Sci. Inst., Berkeley, CA, Tech. Rep. tr-94-036, 1994.
20. C. Schwarz, J. Teich, A. Vainshtein, E. Welzl, and B. L. Evans, "Minimal enclosing parallelogram with application," in Proc. 11th Annu. Symp. Computational Geometry. Vancouver, BC, Canada, 1995, pp. 434-435.
21. M. de Berg, M. van Kreveld, M. Overmars, and O. Schwarzkopf, Computational Geometry: Algorithms and Applications. New York: Springer-Verlag, 1997.
22. J.-Y. Bouguet. Camera Calibration Toolbox for Matlab, Natick, MA.
23. P. Kovesi. Matlab Functions for Computer Vision and Image Analysis, Natick, MA.