Bathymetric SLAM with no map overlap using Gaussian processes

IEEE International Conference on Intelligent Robots and Systems

Volumn , Issue , 2011, Pages 1242-1248

  Barkby, Stephen ^a   Williams, Stefan B ^a   Pizarro, Oscar ^a   Jakuba, Michael V ^a  

^a UNIVERSITY OF SYDNEY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

DEAD RECKONING; GAUSSIAN PROCESS; GAUSSIAN PROCESSES; LARGE DATASETS; LOOP CLOSURE; MEMORY REQUIREMENTS; RAO-BLACKWELLIZED PARTICLE FILTER; RESAMPLING; SEA FLOOR; SELF-CONSISTENCY; SIMULTANEOUS LOCALIZATION AND MAPPING; SPATIAL CORRELATIONS;

BATHYMETRY; FORECASTING; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); INTELLIGENT ROBOTS; MATHEMATICAL TECHNIQUES;

ROBOTICS;

EID: 84455206367     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IROS.2011.6048284     Document Type: Conference Paper

References (15)

1. http://www.whoi.edu/page.do?pid=38095, March 2011.
2. S.A. Barkby, S.B. Williams, O. Pizarro, and M. Jakuba. A Featureless Approach to Efficient Bathymetric SLAM using Distributed Particle Mapping. Journal of Field Robotics, 28(1):19-39, Jan. 2011.
3. S. Blasco. Application of Multibeam Surveying to Resource Mapping. FIG XXII International Congress, TS4.3 Hydrographic Surveying I, April 2002.
4. P. Chapman, D. Wills, G. Brookes, and P. Stevens. Visualizing Underwater Environments Using Multifrequency Sonar. IEEE Computer Graphics and Applications, 19(5):61-65, Sep. 1999.
5. A.I. Eliazar and R. Parr. DP-SLAM 2.0. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA '04), 2:1314-1320, April 2004.
6. A.I. Eliazar and R. Parr. Hierarchical Linear/Constant Time SLAM Using Particle Filters for Dense Maps. Neural Information Processing Systems Conference, Dec. 2005.
7. N. Fairfield, G.A. Kantor, and D. Wettergreen. Towards particle filter SLAM with three dimensional evidence grids in a flooded subterranean environment. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA '06), pages 3575-3580, Orlando, FL, May 2006.
8. N. Fairfield and D. Wettergreen. Active localization on the ocean floor with multibeam sonar. In Proceedings of the OCEANS '08 Conference, Quebec City, Quebec, Sep. 2008.
9. W.J. Kirkwood. Development of the dorado mapping vehicle for multibeam, subbottom, and sidescan science missions. Journal of Field Robotics, 24(6):487-495, June 2007. (Pubitemid 47108341)
10. J.S. Liu. Metropolized independent sampling with comparisons to rejection sampling and importance sampling. Statistics and Computing, 6(2):113-119, 1996. (Pubitemid 126724248)
11. A. Melkumyan and F. Ramos. A Sparse Covariance Function for Exact Gaussian Process Inference in Large Datasets. International Joint Conferences on Artificial Intelligence (IJCAI '09), June 2009.
12. C.A. Rasmussen and C.K.I. Williams. Gaussian Processes for Machine Learning. The MIT Press, MIT, MA, 2006.
13. C. Roman and H. Singh. Improved vehicle based multibeam bathymetry using sub-maps and SLAM. In Proceedings of the Intelligent Robots and Systems (IROS '05), pages 3662-3669, Edmonton, Canada, Aug. 2005.
14. C. Roman and H. Singh. Consistency based error evaluation for deep sea bathymetric mapping with robotic vehicles. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA '06), pages 3568-3574, Orlando, FL, May 2006.
15. H. Singh, L. Whitcomb, D. Yoerger, and O. Pizarro. Microbathymetric Mapping from Underwater Vehicles in the Deep Ocean. Computer Vision and Image Understanding, 79:143-161, 2000.