Efficient distributed sensing using adaptive censoring-based inference

Automatica

Volumn 50, Issue 6, 2014, Pages 1590-1602

  Mu, Beipeng ^a   Chowdhary, Girish ^b   How, Jonathan P ^c  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b OKLAHOMA STATE UNIVERSITY   (United States)

^c USA   (United States)

Author keywords

Bayesian parameter estimation; Conjugacy; Consensus

Indexed keywords

COMMUNICATION; COSTS; PARAMETER ESTIMATION;

ALMOST SURE CONVERGENCE; BAYESIAN PARAMETER ESTIMATION; CONJUGACY; CONSENSUS; CONSENSUS ALGORITHMS; DISTRIBUTED ESTIMATION; DISTRIBUTED SENSING; VALUE OF INFORMATION;

ALGORITHMS;

EID: 84902145619     PISSN: 00051098     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.automatica.2014.04.013     Document Type: Article

References (54)

1. Ahmed, N.; Schoenberg, J.; Campbell, M. (2012). Fast weighted exponential product rules for robust general multi-robot data fusion. In Robotics: science and systems, RSS, Sydney, Australia, July.
2. S.M. Ali, and S.D. Silvey A general class of coefficients of divergence of one distribution from another Journal of the Royal Statistical Society. Series B (Methodological) 28 1 1966 131 142
3. T. Apostol Calculus 2nd ed. 1967
4. Bailey, T.; Julier, S.; Agamennoni, G. (2012). On conservative fusion of information with unknown non-Gaussian dependence. In International conference on information fusion, July (pp. 1876-1883).
5. Berg, T.; Durrant-Whyte, H. (1992). Distributed and decentralized estimation. In Singapore international conference on intelligent control and instrumentation, SICICI, Vol. 2, February (pp. 1118-1123).
6. P. Bodik, W. Hong, C. Guestrin, S. Madden, M. Paskin, and R. Thibaux Intel lab data, Tech. rep. 2004
7. Bourgault, F.; Furukawa, T.; Durrant-Whyte, H.F. (2004). Decentralized Bayesian negotiation for cooperative search. In IEEE/RSJ international conference on intelligent robots and systems, IROS.
8. S. Boyd, A. Ghosh, B. Prabhakar, and D. Shah Randomized gossip algorithms IEEE Transactions on Information Theory 52 2006 2508 2530
9. L.D. Brown Fundamentals of statistical exponential families: with applications in statistical decision theory 1986 Institute of Mathematical Statistics Hayworth, CA, USA
10. Cao, Y.; Ren, W.; Sorensen, N.; Ballard, L.; Reiter, A.; Kennedy, J. (2007). Experiments in consensus-based distributed cooperative control of multiple mobile robots. In International conference on mechatronics and automation, August (pp. 2819-2824).
11. R. Carli, A. Chiuso, L. Schenato, and S. Zampieri Distributed Kalman filtering based on consensus strategies IEEE Journal on Selected Areas in Communications 26 4 2008 622 633
12. M. Cetin, L. Chen, J. Fisher III, A. Ihler, R. Moses, and M. Wainwright et al. Distributed fusion in sensor networks IEEE Signal Processing Magazine 23 4 2006 42 55
13. K. Chang, C.-Y. Chong, and S. Mori Analytical and computational evaluation of scalable distributed fusion algorithms IEEE Transactions on Aerospace and Electronic Systems 46 4 2010 2022 2034
14. H. Chernoff A measure of asymptotic efficiency for tests of a hypothesisbased on the sum of observations Annals of Mathematical Statistics 23 4 1952 493 507
15. Chowdhary, G.; Egerstedt, M.; Johnson, E.N. (2011). Network discovery: an estimation based approach. In American control conference, ACC, San Francisco, CA, June.
16. M. Egerstedt, and M. Mesbahi Graph theoretic methods in multiagent networks 2010 Princeton University Press
17. Farrell, W.; Ganesh, C. (2009). Generalized chernoff fusion approximation for practical distributed data fusion. In International conference on information fusion, July (pp. 555-562).
18. C.S. Fraser, L.F. Bertuccelli, H.-L. Choi, and J.P. How A hyperparameter consensus method for agreement under uncertainty Automatica 48 2 2012 374 380 [Online]. Available: http://dx.doi.org/10.1016/j.automatica.2011.11.003
19. A. Gelman, J. Carlin, H. Stern, and D. Rubin Bayesian data analysis 1995 Chapman and Hall
20. S. Grime, and H. Durrant-Whyte Data fusion in decentralized sensor networks Control Engineering Practice 2 5 1994 849 863
21. Guestrin, C.; Bodik, P.; Thibaux, R.; Paskin, M.; Madden, S. (2004). Distributed regression: an efficient framework for modeling sensor network data. In Third international symposium on information processing in sensor networks, April(pp. 1-10).
22. Guestrin, C.; Krause, A.; Singh, A. (2005). Near-optimal sensor placements in Gaussian processes. In International conference on machine learning, ICML.
23. Gupta, V. (2006). Distributed estimation and control in networked systems, Ph.D. dissertation, California institute of technology.
24. D. Hall, and J. Llinas An introduction to multisensor data fusion Proceedings of the IEEE 85 1 1997 6 23
25. Julier, S. (2006). An empirical study into the use of chernoff information for robust, distributed fusion of Gaussian mixture models. In International conference on information fusion, July (pp. 1-8).
26. C.M. Kreucher, A.O. Hero, and K.D. Kastella An information-based approach to sensor management in large dynamic networks Proceedings of the IEEE 95 5 2007 978 999 Special Issue on Modeling, Identificiation & Control of Large-Scale Dynamical Systems
27. S. Kullback Information theory and statistics 1959 John Wiley and Sons New York
28. S. Kullback, and R.A. Leibler On information and sufficiency Annals of Mathematical Statistics 22 1 1951 79 86
29. Makarenko, A.; Brooks, A.; Kaupp, T.; Durrant-Whyte, H.; Dellaert, F. (2009). Decentralised data fusion: a graphical model approach. In International conference on information fusion, July (pp. 545-554).
30. Michael, N.; Stump, E.; Mohta, K. (2011). Persistent surveillance with a team of MAVs. In IEEE/RSJ international conference on intelligent robots and systems, IROS (pp. 2708-2714).
31. B. Mockenhaupt We've seen the future, and it's unmanned Esquire 2009
32. Msechu, E.; Giannakis, G. (2011). Distributed measurement censoring for estimation with wireless sensor networks. In IEEE International workshop on signal processing advances in wireless communications, SPAWC, June (pp. 176-180).
33. Mu, B.; Chowdhary, G.; How, J. P. (2013). Efficient distributed information fusion using adaptive decentralized censoring algorithms. In American control conference, ACC, Washington, DC, July.
34. Muhammad, A.; Jadbabaie, A. (2007). Decentralized computation of homology groups in networks by gossip. In American control conference, ACC.
35. R. Murray Recent research in cooperative control of multi-vehicle systems ASME Journal of Dynamic Systems, Measurement, and Control 2007
36. M. Nabi-Abdolyousefi, and M. Mesbahi Network identification via node knockout IEEE Transactions on Automatic Control 57 12 2012 3214 3219
37. Nielsen, F.; Nock, R. (2010). Entropies and cross-entropies of exponential families. In IEEE international conference on image processing, ICIP, September (pp. 3621-3624).
38. R. Olfati-Saber, A. Fax, and R.M. Murray Consensus and cooperation in networked multi-agent systems IEEE Transactions on Automatic Control 95 1 2007 215 233
39. Olfati-Saber, R.; Franco, E.; Frazzoli, E.; Shamma, J.S. (2005). Belief consensus and distributed hypothesis testing in sensor networks. In Workshop of network embedded sensing and control, October.
40. Oliva, G.; Panzieri, S.; Priolo, A.; Ulivi, G. (2012). Adding and removing nodes in consensus. In 20th Mediterranean conference on control automation, MED, July (pp. 1031-1036).
41. Paskin, M.A. (2004). Exploiting locality in probabilistic inference. Ph.D. dissertation, Berkeley, CA, USA, aAI3165519.
42. W. Ren, R.W. Beard, and E.M. Atkins Information consensus in multivehicle cooperative control IEEE Control Systems Magazine 27 2 2007 71 82
43. Renyi, A. (1960). On measures of information and entropy. In Proceedings of the 4th Berkeley symposium on mathematics, statistics and probability (pp. 547-561). [Online]. Available: http://digitalassets.lib.berkeley.edu/math/ucb/ text/math-s4-v1-article-27.pdf.
44. V. Saligrama, and M. Alanyali A token-based approach for distributed computation in sensor networks IEEE Journal of Selected Topics in Signal Processing 5 4 2011 817 832
45. C.E. Shannon, and W. Weaver The mathematical theory of communication 1948 The University of Illinois Press Urbana, IL
46. W.P. Tay, J. Tsitsiklis, and M. Win Asymptotic performance of a censoring sensor network IEEE Transactions on Information Theory 53 11 2007 4191 4209
47. Techy, L.; Woolsey, C.; Schmale, D. (2008). Path planning for efficient uav coordination in aerobiological sampling missions. In IEEE Conference on decision and control, CDC (pp. 2814-2819).
48. Trivedi, N.; Balakrishnan, N. (2009). Graphical models for distributed inference in wireless sensor networks. In International conference on sensor technologies and applications, June (pp. 596-603).
49. Uney, M. (2009). Decentralized eestimation under ccommunication constraints. Ph.D. dissertation, Middle East Technical University, Turkey.
50. Unmanned aircraft systems roadmap: 2007-2032. Tech. rep.; Office of the Secretary of defense 2007
51. P.K. Varshney Distributed detection and data fusion 1997 Springer-Verlag, New York Inc
52. M.J. Wainwright, and M.I. Jordan Graphical models, exponential families, and variational inference Foundations and Trends in Machine Learning 1 1-2 2008 1 305 [Online]. Available: http://dx.doi.org/10.1561/2200000001
53. X. Wang, V. Yadav, and S.N. Balakrishnan Cooperative UAV formation flying with obstacle/collision avoidance IEEE Transactions on Control Systems Technology 15 4 2007 672 679
54. Zhang, L.; Kim, Y.J.; Manocha, D. (2007). C-DIST: efficient distance computation for rigid and articulated model in configuration space. In Proceedings of the ACM solid and physical modeling conference, Beijing, China, June.