Gaussian processes for signal strength-based location estimation

Robotics: Science and Systems

Volumn 2, Issue , 2006, Pages 303-310

  Ferris, Brian ^a   Hahnel, Dirk ^b   Fox, Dieter ^a  

^a UNIVERSITY OF WASHINGTON   (United States)

^b INTEL RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84864765652     PISSN: None     EISSN: 2330765X     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (16)

1. P. Bahl and V.N. Padmanabhan. RADAR: An in-building RF-based user location and tracking system. In Proc. of IEEE Infocom, 2000.
2. A. Doucet, N. de Freitas, and N. Gordon, editors. Sequential Monte Carlo in Practice. Springer-Verlag, New York, 2001.
3. C. Guestrin, A. Krause, and A. Singh. Near-optimal sensor placements using Gaussian processes. In Proc. of the International Conference on Machine Learning (ICML), 2005.
4. A. Haeberlen, E. Flannery, A.M. Ladd, A. Rudys, D.S. Wallach, and L.E. Kavraki. Practical robust localization over large-scale 802.11 wireless networks. In Proc. of the Tenth ACM International Conference on Mobile Computing and Networking (MOBICOM), 2004.
5. A. Howard, S. Siddiqi, and G. Sukhatme. An experimental study of localization using wireless ethernet. In Proc. of the International Conference on Field and Service Robotics, 2003.
6. X. Huang, A. Acero, and H.-W. Hon. Spoken Language Processing: A Guide to Theory, Algorithm and System Development. Prentice Hall, 2001.
7. A.M. Ladd, K.E. Bekris, A. Rudys, G. Marceau, L.E. Kavraki, and D. Wallach. Robotics-based location sensing using wireless ethernet. In Proc. of the Eight ACM International Conference on Mobile Computing and Netwrking (MOBICOM), 2002.
8. A. LaMarca, J. Hightower, I. Smith, and S. Consolvo. Self-mapping in 802.11 location systems. In International Conference on Ubiquitous Computing (UbiComp), 2005.
9. N. Lawrence. Gaussian process latent variable models for visualization of high dimensional data. In Advances in Neural Information Processing Systems (NIPS), 2003.
10. J. Letchner, D. Fox, and A. LaMarca. Large-scale localization from wireless signal strength. In Proc. of the National Conference on Artificial Intelligence (AAAI), 2005.
11. L. Liao, D. Fox, J. Hightower, H. Kautz, and D. Schulz. Voronoi tracking: Location estimation using sparse and noisy sensor data. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2003.
12. K. Liu, A. Hertzmann, and Z. Popovic. Learning physics-based motion style with nonlinear inverse optimization. In ACM Transactions on Graphics (Proc. of SIGGRAPH), 2005.
13. C.E. Rasmussen and C.K.I. Williams. Gaussian processes for machine learning. The MIT Press, 2005.
14. A. Schwaighofer, M. Grigoras, V. Tresp, and C. Hoffmann. GPPS: A Gaussian process positioning system for cellular networks. In Advances in Neural Information Processing Systems (NIPS), 2003.
15. S. Seidel and T. Rappaport. 914 MHz path loss prediction models for indoor wireless communictions in multifloored buildings. IEEE Transactions on Antennas and Propagation, 40(2), 1992.
16. S. Thrun, W. Burgard, and D. Fox. Probabilistic Robotics. MIT Press, Cambridge, MA, September 2005. ISBN 0-262-20162-3.