Visually mapping the RMS titanic: Conservative covariance estimates for SLAM information filters

International Journal of Robotics Research

Volumn 25, Issue 12, 2006, Pages 1223-1242

  Eustice, Ryan M ^a   Singh, Hanumant ^b   Leonard, John J ^c   Walter, Matthew R ^c  

^a UNIVERSITY OF MICHIGAN   (United States)

^b WOODS HOLE OCEANOGRAPHIC INSTITUTION   (United States)

^c Massachusetts Institute of Technology Cambridge   (United States)

Author keywords

Computer vision; Data association; Information filters; Mobile robotics; SLAM; Underwater vehicles

Indexed keywords

COMPUTER VISION; DIGITAL FILTERS; MOBILE ROBOTS; REMOTELY OPERATED VEHICLES; SENSORS; UNDERWATER IMAGING;

DATA ASSOCIATION; IMAGERY CONSTRAINTS; INFORMATION FILTERS; UNDERWATER VEHICLES;

CONFORMAL MAPPING;

EID: 33750976689     PISSN: 02783649     EISSN: 17413176     Source Type: Journal    
DOI: 10.1177/0278364906072512     Document Type: Conference Paper

References (55)

1. Ballard, R., Stager, L., Master, D., Yoerger, D., Mindell, D., Whitcomb, L., Singh, H., and Piechota, D. 2002. Iron age shipwrecks in deep water off Ashkelon, Israel. American Journal Archaeology 106 (2). 151-168.
2. Bar-Shalom, Y., Rong Li, X., and Kirubarajan, T. 2001. Estimation with Applications to Tracking and Navigation. John Wiley & Sons, Inc., New York.
3. Coleman, D., Ballard, R., and Gregory, T. 2003. Marine archaeological exploration of the Black Sea. Proceedings of IEEE/MTS OCEANS Conference and Exhibition, Vol. 3, September, pp. 1287-1291.
4. Davison, A. 2003. Real-time simultaneous localisation and mapping with a single camera. Proceedings of IEEE International Conference Computer Vision, pp. 1403-1410.
5. Davison, A. and Murray, D. 2001. Simultaneous localisation and map-building using active vision. IEEE Transactions Pattern Analysis and Machine Intelligence 24 (7). 865-880.
6. Dellaert, F. 2005. Square root SAM. Proceedings of Robotics: Science & Systems. MIT Press, Cambridge, MA, pp. 177-184.
7. Dissanayake, M., Newman, P., Clark, S., Durrant-Whyte, H., and Csorba, M. 2001. A solution to the simultaneous localization and map building (SLAM) problem. IEEE Transactions Robotics Automation 17 (3). 229-241.
8. Duckett, T., Marsland, S., and Shapiro, J. 2000. Learning globally consistent maps by relaxation. Proceedings of IEEE International Conference Robotics Automation, San Francisco, CA, April, pp. 3841-3846.
9. Eustice, R., Pizarro, O., and Singh, H. 2004. Visually augmented navigation in an unstructured environment using a delayed state history. Proceedings of IEEE International Conference Robotics Automation, Vol. 1, New Orleans, USA, April, pp. 25-32.
10. Eustice, R. 2005. Large-area visually augmented navigation for autonomous underwater vehicles. PhD dissertation, Massachusetts Institute of Technology/Woods Hole Oceaonographic Institution Joint Program, June.
11. Eustice, R., Pizarro, O., and Singh, H. 2006a. Visually augmented navigation for autonomous underwater vehicles. IEEE Journal Oceanic Engineering, 2006, Accepted, To Appear.
12. Eustice, R., Singh, H., and Leonard, J. 2005a. Exactly sparse delayed-state filters. Proceedings of IEEE International Conference Robotics Automation, Barcelona, Spain, pp. 2428-2435.
13. Eustice, R., Singh, H., and Leonard, J. 2006b. Exactly sparse delayed-state filters for view-based SLAM. IEEE Transactions Robotics, Accepted, To Appear.
14. Eustice, R., Walter, M., and Leonard, J. 2005b. Sparse extended information filters: insights into sparsification. Proceedings of IEEE/RSJ International Conference Intelligent Robot Systems, pp. 641-648.
15. Frese, U. and Hirzinger, G. 2001. Simultaneous localization and mapping - a discussion. Proceedings of IJCAI Workshop: Reasoning with Uncertainty in Robotics, Seattle, WA, pp. 17-26.
16. Frese, U. 2004. Treemap: an O(Log N) algorithm for simultaneous localization and mapping. Spatial Cognition IV, C. Freksa, Ed., Springer Verlag.
17. Frese, U. 2005. A proof for the approximate sparsity of SLAM information matrices. Proceedings of IEEE International Conference Robotics Automation, Barcelona, Spain, pp. 331-337.
18. Frese, U., Larsson, P., and Duckett, T. 2005. A multilevel relaxation algorithm for simultaneous localisation and mapping. IEEE Transactions Robotics 21 (2). 1-12.
19. German, C., Connelly, D., Prien, R., Yoerger, D., Jakuba, M., Bradley, A., Shank, T., Edmonds, H., and Langmuir, C. 2004. New techniques for hydrothermal exploration: in situ chemical sensors on AUVs - preliminary results from the Lau Basin. EOS: Transactions American Geophysical Union Fall Meeting Supplement, December.
20. Harris, C. and Stephens, M. 1998. A combined corner and edge detector. Proceedings of 4th Alvey Vision Conference, Manchester, UK, pp. 147-151.
21. Hartley, R. and Zisserman, A. 2000. Multiple View Geometry in Computer Vision. Cambridge University Press.
22. Hill, J., Driscoll, N., Weissel, J., Kastner, M., Singh, H., Cormier, M., Camilli, R., Eustice, R., Lipscomb, R., McPhee, N., Newman, K., Robertson, G., Solomon, E., and Tomanka, K. 2004. A detailed near-bottom survey of large gas blowout structures along the US Atlantic shelf break using the autonomous underwater vehicle (AUV) SeaBED. EOS: Transactions American Geophysical Union Fall Meeting Supplement.
23. Horn, B. 1990. Relative orientation. International Journal Computer Vision 4 (1). 59-78.
24. Hunt, M., Marquet, W., Moller, D., Peal, K., Smith, W., and Spindel, R. 1974. An acoustic navigation system. Woods Hole Oceanographic Institution, Technical Report WHOI-74-6, December.
25. Knight, J. 2001. Computationally tractable SLAM. University of Oxford, Technical Report OUEL 2232/2001.
26. Konolige, K. 2004. Large-scale map-making. Proceedings of AAAI National Conference Artificial Intelligence, San Jose, CA, pp. 457-463.
27. Liu, Y. and Thrun, S. 2003. Results for outdoor-SLAM using sparse extended information filters. Proceedings of IEEE International Conference Robotics Automation, Vol. 1, September, pp. 1227-1233.
28. Lowe, D. 2004. Distinctive image features from scale-invariant keypoints. International Journal Computer Vision 60 (2). 91-110.
29. The Mathworks. 2005. MATLAB function reference: mldivide, www.mathworks.com/access/helpdesk/help/techdoc/ref/mldivide.html, Aug. 2005.
30. McLauchlan, P. and Murray, D. 1995. A unifying framework for structure and motion recovery from image sequences. Proceedings of IEEE International Conference Computer Vision, Boston, MA, pp. 314-320.
31. McLauchlan, P. 2000. A batch/recursive algorithm for 3D scene reconstruction. Proceedings of IEEE Conference Computer Vision Pattern Recognition, Vol. 2, Hilton Head, SC, pp. 738-743.
32. Milne, P. 1983. Underwater Acoustic Positioning Systems. Gulf Publishing Company, Houston, TX.
33. Neira, J. and Tardos, J. 2001. Data association in stochastic mapping using the joint compatibility test. IEEE Transactions Robotics Automation 17 (6). 890-897.
34. Newman, P. 1999. On the structure and solution of the simultaneous localisation and map building problem. PhD dissertation, Australian Centre for Field Robotics, The University of Sydney, March.
35. Nistér, D., Naroditsky, O., and Bergen, J. 2004. Visual odometry. Proceedings of IEEE Conference Computer Vision Pattern Recognition, Vol. 1, pp. 652-659.
36. Paskin, M. 2002 Thin junction tree filters for simultaneous localizationandmapping. University of California, Berkeley, Technical Report CSD-02-1198, September.
37. Paskin, M. 2003. Thin junction tree filters for simultaneous localization and mapping. Proceedings of International Joint Conference Artificial Intelligence, San Francisco, CA, pp. 1157-1164.
38. Pizarro, O. 2004. Large scale structure from motion for autonomous underwater vehicle surveys. PhD dissertation, Massachusetts Institute of Technology /Woods Hole Oceaonographic Institution Joint Program, September.
39. Pizarro, O., Eustice, R., and Singh, H. 2003. Relative pose estimation for instrumented, calibrated imaging platforms. Proceedings of Digital Image Computing Applications, Sydney, Australia, December, pp. 601-612.
40. Pizarro, O., Eustice, R., and Singh, H. 2004. Large area 3D reconstructions from underwater surveys. Proceedings of IEEE/MTS OCEANS Conference and Exhibition, Vol. 2, Kobe, Japan, November, pp. 678-687.
41. Pollefeys, M., Gool, L. V., Vergauwen, M., Verbiest, F., Cornelis, K., Journal Tops, and Koch, R. 2004. Visualmodeling with a hand-held camera. International Journal Computer Vision 59 (3). 207-232.
42. Repko, J. and Pollefeys, M. 2005. 3D models from extended uncalibrated video sequences: addressing key-frame selection and projective drift. Proceedings of International Conference 3-D Digital Imaging and Modeling, pp. 150-157.
43. Reynolds, J., Highsmith, R., Konar, B., Wheat, C., and Doudna, D. 2001. Fisheries and fisheries habitat investigations using undersea technology. Proceedings of IEEE/MTS OCEANS Conference and Exhibition, Vol. 2, Honolulu, HI, USA, November, pp. 812-820.
44. Roumeliotis, S., Johnson, A., and Montgomery, J. 2002. Aug-menting inertial navigation with image-based motion estimation. Proceedings of IEEE International Conference Robotics Automation, Vol. 4, Washington, DC, May, pp. 4326-4333.
45. Rousseeuw, P. and Leroy, A. 1987. Robust regression and outlier detection. John Wiley and Sons, New York.
46. Se, S., Lowe, D., and Little, J. 2005. Vision-based global localization and mapping for mobile robots. IEEE Transactions Robotics 21 (3). 364-375.
47. Shewchuk, J. 1994. An introduction to the conjugate gradient method without the agonizing pain. Carnegie Mellon University, Technical Report CMU-CS-94-125, August.
48. Singh, H., Armstrong, R., Gilbes, F., Eustice, R., Roman, C., Pizarro, O. and Torres, J. 2004. Imaging coral I: imaging coral habitats with the Sea BED AUV. Journal Subsurface Sensing Technology and Applications 5 (1). 25-42.
49. Smith, R., Self, M., and Cheeseman, P. 1990. Estimating uncertain spatial relationships in robotics. Autonomous Robot Vehicles, I. Cox and G. Wilfong, Eds. Springer-Verlag, pp. 167-193.
50. Thrun, S., Koller, D., Ghahramani, Z., Durrant-Whyte, H., and Ng, A. 2002. Simultaneous mapping and localization with sparse extended information filters: theory and initial results. Proceedings of International Workshop Algorithmic Foundations of Robotics, J. Boissonnat, J. Burdick, K. Goldberg, and S. Hutchinson, Eds, Nice, France.
51. Thrun, S., Liu, Y., Koller, D., Ng, A., Ghahramani, Z., and Durrant-Whyte, H. 2004. Simultaneous localization and mapping with sparse extended information filters. International Journal Robotics Research 23 (7-8). 693-716.
52. Uhlmann, J. 1997. A culminating advance in the theory and practice of data fusion, filtering, and decentralized estimation. Covariance Intersection Working Group (CIWG), Technical Report, 1997.
53. Van Gool, L., Defoort, F., Hug, J., Kalberer, G., Koch, R., Martens, D., Pollefeys, M., Proesmans, M., Vergauwen, M., and Zalesny, A. 2000. Image-based 3D modeling: modeling from reality. Proceedings of NATO Advanced Workshop on Confluence of Computer Vision and Computer Graphics, ser. NATO Science Series, S. Ljubljana, A. Leonardis, F. Solina, and R. Bajcsy, Eds, Vol. 84, Kluwer Academic Publishers, pp. 161-178.
54. Whitcomb, L., Yoerger, D., and Singh, H. 1999. Combined Doppler/LBL based navigation of underwater vehicles. Proceedings of International Symposium Unmanned Untethered Submersibles Technology, Durham, New Hampshire, May.
55. Zhang, Z. 1998. Determining the epipolar geometry and its uncertainty: a review. International Journal Computer Vision 27 (2). 161-198.