3-D Mapping with an RGB-D camera

IEEE Transactions on Robotics

Volumn 30, Issue 1, 2014, Pages 177-187

  Endres, Felix ^a   Hess, Jürgen ^a   Sturm, Jürgen ^b   Cremers, Daniel ^b   Burgard, Wolfram ^a  

^a UNIVERSITY OF FREIBURG   (Germany)

^b TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

Localization; Mapping; Open source; RGB D; Simultaneous localization and mapping (SLAM)

Indexed keywords

CAMERAS; MAPPING; MATHEMATICAL TECHNIQUES; ROBOTICS; SENSORS;

BENCHMARK DATASETS; EXPERIMENTAL EVALUATION; FEATURE DESCRIPTORS; LOCALIZATION; OPEN SOURCES; RGB-D; SIMULTANEOUS LOCALIZATION AND MAPPING; SMALL DOMESTIC ROBOT;

OPEN SYSTEMS;

EID: 84894554423     PISSN: 15523098     EISSN: None     Source Type: Journal    
DOI: 10.1109/TRO.2013.2279412     Document Type: Article

References (44)

1. F. Endres, J. Hess, N. Engelhard, J. Sturm, D. Cremers, and W. Burgard. (2013, Jul.). [Online]. Available:http://ros.org/wiki/rgbdslam
2. P. J. Besl and H. D. McKay, "A method for registration of 3-D shapes," IEEE Trans. Pattern Anal. Mach. Intell., vol. 14, no. 2, pp. 239-256, Feb. 1992.
3. S. Rusinkiewicz and M. Levoy, "Efficient variants of the ICP algorithm," presented at the Int. Conf. 3-D Digital Imaging and Modeling, Quebec, Canada, 2001.
4. A. W. Fitzgibbon, "Robust registration of 2D and 3D point sets," Image Vision Comput., vol. 21, no. 13-14, pp. 1145-1153, 2003.
5. A. Censi, "An ICP variant using a point-to-line metric," in Proc. IEEE Int. Conf. Robot. Autom., Pasadena, CA, USA, May 2008, pp. 19-25.
6. J. Roewekaemper, C. Sprunk, G. Tipaldi, C. Stachniss, P. Pfaff, and W. Burgard, "On the position accuracy of mobile robot localization based on particle filters combined with scan matching," in Proc. IEEE/RSJ Int. Conf. Intell. Robots Syst., 2012, pp. 3158-3164.
7. S. Grzonka, G. Grisetti, and W. Burgard, "A fully autonomous indoor quadrotor," IEEE Trans. Robot., vol. 28, no. 1, pp. 90-100, Feb. 2012.
8. A. Davison, "Real-time simultaneous localisation and mapping with a single camera," in Proc. IEEE Intl. Conf. Comput. Vis., 2003, pp. 1403- 1410.
9. G. Klein and D. Murray, "Parallel tracking and mapping for small AR workspaces," in Proc. IEEE ACM Int. Symp. Mixed Augment. Reality, Nara, Japan, 2007, pp. 225-235.
10. H. Strasdat, J. M. M. Montiel, and A. Davison, "Scale drift-aware large scale monocular slam," presented at the Robotics: Sci. Syst. Conf., Zaragoza, Spain, 2010.
11. H. Jin, P. Favaro, and S. Soatto, "Real-time 3-D motion and structure of point-features: A front-end for vision-based control and interaction," in Proc. IEEE Int. Conf. Comput. Vis. Pattern Recog., 2000, pp. 778-779.
12. D. Nister, "Preemptive RANSAC for live structure and motion estimation," in Proc. IEEE Int. Conf. Comput. Vis., 2003, pp. 199-206.
13. D. Lowe, "Distinctive image features from scale-invariant keypoints," Int. J. Comput. Vis., vol. 60, no. 2, pp. 91-110, 2004.
14. H. Bay, A. Ess, T. Tuytelaars, and L. Van Gool, "Speeded-up robust features (SURF)," Comput. Vis. Image Understanding, vol. 110, pp. 346- 359, 2008.
15. E. Rublee, V. Rabaud, K. Konolige, and G. Bradski, "ORB: An efficient alternative to SIFT or SURF," in Proc. IEEE Int. Conf. Comput. Vis., 2011, vol. 13, pp. 2564-2571.
16. J. Shi and C. Tomasi, "Good features to track," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 1994, pp. 593-600.
17. P. Henry, M. Krainin, E. Herbst, X. Ren, and D. Fox, "RGB-D mapping: Using kinect-style depth cameras for dense 3D modeling of indoor environments," Int. J. Robot. Res., vol. 31, no. 5, pp. 647-663, Apr. 2012.
18. A. Segal, D. Haehnel, and S. Thrun, "Generalized-ICP," presented at the Robotics.: Sci. Syst. Conf., Seattle, WA, USA, 2009.
19. R. A. Newcombe, S. Izadi, O. Hilliges, D. Molyneaux, D. Kim, A. J. Davison, P. Kohli, J. Shotton, S. Hodges, and A. W. Fitzgibbon, "Kinectfusion: Real-time dense surface mapping and tracking," in Proc. IEEE Int. Symp. Mixed Augmented Reality, 2011, pp. 127-136.
20. B. Curless and M. Levoy, "A volumetric method for building complex models from range images," in Proc. Special Interest Group Graph. Interactive Techn., 1996, pp. 303-312.
21. T. Whelan, H. Johannsson, M. Kaess, J. Leonard, and J. McDonald, "Robust real-time visual odometry for dense RGB-D mapping," presented at the IEEE Int. Conf. Robotics Automation, Karlsruhe, Germany, May 2013.
22. M. Zeng, F. Zhao, J. Zheng, and X. Liu, "Octree-based fusion for realtime 3D reconstruction," Graph. Models, vol. 75, 2012.
23. G. Hu, S. Huang, L. Zhao, A. Alempijevic, and G. Dissanayake, "A robust RGB-D SLAM algorithm," in Proc. IEEE/RSJ Int. Conf. Intell. Robots Syst.), 2012, pp. 1714-1719.
24. F. Endres, J. Hess, N. Engelhard, J. Sturm, D. Cremers, and W. Burgard, "An evaluation of the RGB-D SLAM system," in Proc. IEEE Int. Conf. Robot. Autom., St. Paul, MN, USA, 2012, pp. 1691-1696.
25. F. Endres, J. Hess, N. Engelhard, J. Sturm, and W. Burgard, "6D visual SLAM for RGB-D sensors," Automatisierungstechnik, vol. 60, pp. 270- 278, May 2012.
26. J. Sturm, N. Engelhard, F. Endres,W. Burgard, and D. Cremers, "A benchmark for the evaluation of RGB-D slam systems," in Proc. Int. Conf. Intell. Robot Syst., 2012, pp. 573-580.
27. H. Durrant-Whyte and T. Bailey, "Simultaneous localization and mapping: Part I," IEEE Robot. Autom. Mag., vol. 13, no. 2, pp. 99-110, Jun. 2006.
28. T. Bailey and H. Durrant-Whyte, "Simultaneous localization and mapping (SLAM): Part II," IEEE Robot. Autom. Mag., vol. 13, no. 3, pp. 108-117, Sep. 2006. (Pubitemid 46530408)
29. R. Arandjelovíc and A. Zisserman, "Three things everyone should know to improve object retrieval," in Proc. IEEE Conf. Comput. Vis. Pattern Recog., 2012, pp. 2911-2918.
30. M. Fischler and R. Bolles, "Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography," Commun. ACM, vol. 24, no. 6, pp. 381-395, 1981. (Pubitemid 12444102)
31. O. Chum, J. Matas, and J. Kittler, "Locally optimized ransac," in Pattern Recognition. NewYork, NY, USA: Springer-Verlag, 2003, pp. 236-243.
32. S. Umeyama, "Least-squares estimation of transformation parameters between two point patterns," IEEE Trans. Pattern Anal.Mach. Intell., vol. 13, no. 4, pp. 376-380, Apr. 1991. (Pubitemid 21645719)
33. S. Thrun, W. Burgard, and D. Fox, Probabilistic Robotics. NewYork, NY, USA: MIT Press, 2005.
34. S. Oßwald, A. Hornung, and M. Bennewitz, "Improved proposals for highly accurate localization using range and vision data," in Proc. IEEE/RSJ Int. Conf. Intell. Robots Syst., Vilamoura, Portugal, Oct. 2012, pp. 1809-1814.
35. K. Khoshelham and S. O. Elberink, "Accuracy and resolution of kinect depth data for indoor mapping applications," Sensors, vol. 12, no. 2, pp. 1437-1454, 2012.
36. K. B. Petersen and M. S. Pedersen, "The Matrix Cookbook," Oct. 2008. Available: http://www2.imm.dtu.dk/pubdb/p.php?3274
37. C. Bishop, Pattern Recognition and Machine Learning. New York, NY, USA: Springer-Verlag, 2006.
38. D. Nister and H. Stewenius, "Scalable recognition with a vocabulary tree," in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recog., vol. 2, Washington, DC, USA, 2006, pp. 2161-2168. (Pubitemid 44931581)
39. M. Cummins and P. Newman, "Appearance-only SLAM at large scale with FAB-MAP 2.0," Int. J. Robot. Res., vol. 30, pp. 1100-1123, 2010.
40. R. Kümmerle, G. Grisetti, H. Strasdat, K. Konolige, and W. Burgard, "G2o: A general framework for graph optimization," in Proc. IEEE Int. Conf. Robot. Autom., Shanghai, China, 2011, pp. 3607-3613.
41. A. Hornung, K. M. Wurm, M. Bennewitz, C. Stachniss, and W. Burgard, "OctoMap: An efficient probabilistic 3D mapping framework based on octrees," Auton. Robots, pp. 189-206, 2013.
42. C.Wu. (2007). SiftGPU: A GPU implementation of scale invariant feature transform (SIFT). [Online]. Available:http://cs.unc.edu/ccwu/siftgpu
43. P. Agarwal, G. D. Tipaldi, L. Spinello, C. Stachniss, and W. Burgard, "Robust map optimization using dynamic covariance scaling," in Proc. IEEE Int. Conf. Robot. Autom., May 2013.
44. E. Olson and P. Agarwal, "Inference on networks of mixtures for robust robot mapping," Int. J. Robot. Res., vol. 32, no. 7, pp. 826-840, Jun. 2013.