Continuous trajectory planning of mobile sensors for informative forecasting

Automatica

Volumn 46, Issue 8, 2010, Pages 1266-1275

  Choi, Han Lim ^a   How, Jonathan P ^b  

^a Korea Advanced Institute of Science and Technology (KAIST)   (South Korea)

^b Massachusetts Institute of Technology Cambridge   (United States)

Author keywords

Mobile robots; Mutual information; Sensor networks; Trajectory planning

Indexed keywords

COMPUTATIONALLY EFFICIENT; CONDITIONAL INDEPENDENCES; INFORMATION ACCUMULATION; INFORMATION POTENTIAL; INFORMATION REWARD; MEASUREMENT MATRIX; MOBILE SENSORS; MUTUAL INFORMATION; MUTUAL INFORMATIONS; OPTIMAL PATH PLANNING; PATH SYNTHESIS; PERFORMANCE BENEFITS; PLANNING METHODOLOGY; SPATIAL INTERPOLATION; STATE OF THE ART; STEERING LAW; TRAJECTORY PLANNING;

ARTS COMPUTING; COMPUTATIONAL EFFICIENCY; MOBILE ROBOTS; MOTION PLANNING; SENSOR NETWORKS; TRAJECTORIES; UNMANNED AERIAL VEHICLES (UAV); WEATHER FORECASTING; WIRELESS NETWORKS;

ROBOT PROGRAMMING;

EID: 77955423099     PISSN: 00051098     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.automatica.2010.05.004     Document Type: Article

References (38)

1. Choi, H.-L. (2009). Adaptive sampling and forecasting with mobile sensor networks. Ph.D. thesis. Massachusetts Institute of Technology.
2. Choi, H.-L., & How, J. P. (2007). A multi-UAV targeting algorithm for ensemble forecast improvement. In AIAA guidance, navigation, and control conference, Hilton Head, SC, (pp. AIAA20076753).
3. Choi, H.-L., & How, J. P. (2009). On the roles of smoothing in planning of informative paths. In American control conference (pp. 21542159).
4. Choi, H.-L., How, J. P., & Hansen, J. (2007). Ensemble-based adaptive targeting of mobile sensor networks. In American control conference, New York City, NY, (pp. 23932398).
5. R. Cortez, X. Papageorgiou, H. Tanner, A. Klimenko, K. Borozdin, and R. Lumia Smart radiation sensor management: nuclear search and mapping using mobile IEEE Robotics & Automation Magazine 15 3 2008
6. T. Cover, and J. Thomas Elements of information theory Wiley series in telecommunications 1991
7. N. Cressie The origins of kriging Mathematical Geology 22 3 1990 239 252
8. T.E. Duncan On the calculation of mutual information SIAM Journal on Applied Mathematics 19 1 1970 215 220
9. Duncan, T. E., & Pasik-Duncan, B. (2007). Estimation and mutual information. In IEEE conference on decision and control, New Orleans, LA, (pp. 324327).
10. E. Fiorelli, N. Leonard, P. Bhatta, D. Paley, R. Bachmayer, and D. Fratantoni Multi-AUV control and adaptive sampling in Monterey Bay IEEE Journal of Oceanic Engineering 31 4 2006 935 948
11. Grocholsky, B. (2002). Information-theoretic control of multiple sensor platforms. Ph.D. thesis. University of Sydney.
12. B. Grocholsky, J. Keller, V. Kumar, and J. Pappas Cooperative air and ground surveillance IEEE Robotics and Automation Magazine 13 3 2006 16 25
13. Grocholsky, B., Makarenko, A., & Durrant-Whyte, H. (2003). Information-theoretic coordinated control of multiple sensor platforms. In IEEE international conference on robotics and automation, Taipei, Taiwan, (pp. 15211526).
14. D. Guo, S. Shamai (Shitz), and S. Verdu Mutual information and minimum mean-square error in Gaussian channels IEEE Transactions on Information Theory 51 4 2005 1261 1282
15. V. Gupta, T.H. Chung, B. Hassibi, and R.M. Murray On a stochastic sensor selection algorithm with applications in sensor scheduling and sensor coverage Automatica 42 2 2006 251 260
16. G. Hoffmann, and C.J. Tomlin Mobile sensor network control using mutual information methods and particle filters IEEE Transactions on Automatic Control 55 1 2010 32 47
17. R.A. Horn, and C. Johnson Matrix analysis 1985 Cambridge University Press
18. Hover, F. Continuous-time adaptive sampling and forecast assimilation for autonomous vehicles. Presentation given to WHOI Department of Applied Ocean Physics and Engineering. October 2008. http://web.mit.edu/hovergroup/pub/PPIDA. pdf.
19. T. Kadota, M. Zakai, and J. Ziv Mutual information of the white Gaussian channel with and without feedback IEEE Transactions on Information Theory 17 4 1971 368 371
20. A. Kolmogorov On the Shannon theory of information transmission in the case of continuous signals IRE Transactions on Information Theory 2 4 1956 102 108
21. J.B. Lasserre A trace inequality for matrix product IEEE Transactions on Automatic Control 40 8 1995 1500 1501
22. H.W.J. Lee, K.L. Teo, and A.E.B. Lim Sensor scheduling in continuous time Automatica 37 12 2001 2017 2023
23. S.J. Majumdar, C.H. Bishop, B.J. Etherton, and Z. Toth Adaptive sampling with the ensemble transform Kalman filter. Part II: field programming implementation Monthly Weather Review 130 3 2002 1356 1369
24. S. Martinez, and F. Bullo Optimal sensor placement and motion coordination for target tracking Automatica 42 2006 661 668
25. E. Mayer-Wolf, and M. Zakai On a formula relating the Shannon information to the Fisher information for the filtering problem Lecture notes in control and information sciences Vol. 61 1984 164 171
26. S. Mitter, and N. Newton Information and entropy flow in the KalmanBucy filter Journal of Statistical Physics 118 112 2005 145 176
27. N. Newton Dual nonlinear filters and entropy production SIAM Journal on Control and Optimization 45 3 2006 998 1016
28. N. Newton Dual KalmanBucy filters and interactive entropy production SIAM Journal on Control and Optimization 46 5 2007 1637 1663
29. T.N. Palmer, R. Gelaro, J. Barkmeijer, and R. Buizza Singular vectors, metrics, and adaptive observations Journal of the Atmospheric Sciences 55 4 1998 633 653
30. B. Ristic, and M.S. Arulampalam Tracking a manoevring target using angle-only measurements: algorithms and performance Signal Processing 83 6 2003 1223 1238
31. R. Subramanian, and K. Bhagwat On a theorem of Wigner on products of positive matrices Proceedings Mathematical Sciences 88A-3 1 1979 31 34
32. Y. Tomita, S. Omatu, and T. Soeda An application of the information theory to filtering problems Information Sciences 11 1976 13 27
33. TOMLAB/SNOPT (2008) http://tomopt.com/tomlab/products/snopt/.
34. J.E. Wall Jr., A.S. Willsky, and N.R. Sandell Jr. On the fixed-interval smoothing problem Stochastics 5 12 1981 1 41
35. J.S. Whitaker, and H.M. Hamill Ensemble data assimilation without perturbed observations Monthly Weather Review 130 7 2002 1913 1924
36. J.L. Williams, J.W. Fisher III, and A.S. Willsky Approximate dynamic programming for communication-constrained sensor network management IEEE Transactions on Signal Processing 55 8 2007 3995 4003
37. C. Willams, and C. Rasmussen Gaussian processes for regression Advances in neural information processing systems Vol. 8 1996 MIT Press
38. G. Zames On the metric complexity of casual linear systems:-entropy and-dimension for continuous time IEEE Transactions on Automatic Control 24 1979