Abstract
3D Mapping using RBG-D sensor is a hot topic in the robotic field. This paper proposes a sub-map stitching method to build map in the large scale indoor environment. We design a special landmark, and place it in the environment. Every sub-map contains those landmarks, and then can be stitched by BA optimization. The result shows that the map error is blow 1 % in a room with the dimensions of 13 m × 8 m.
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References
Engelhard, N., Endres, F., Hess, J., Sturm, J., Burgard, W.: Real-time 3D visual SLAM with a hand-held RGB-D camera. In: RSS 2010 Workshop on RGB-D Cameras (2010)
Henry, P., Krainin, M., Herbst, E., Ren, X., Fox, D.: RGB-D mapping: using depth cameras for dense 3D modeling of indoor environments. In: RSS 2010 Workshop on RGB-D Cameras (2010)
Slam6d. Slam6d toolkit. http://slam6d.sourceforge.net/index.html
Izadi, S., Newcombe, R.A., Kim, D., Hilliges, O., Molyneaux, D., Kohli, P., Shotton, J., Hodges, S., Freeman, D., Davison, A., Fitzgibbon, A.: Kinectfusion: real-time dynamic 3D surface reconstruction and interaction. In: ACM SIGGRAPH 2011 (2011)
Zeng, M., Zhao, F., Zheng, J., Liu, X.: Octree-based fusion for realtime 3D reconstruction. In: Graphical Models (2012)
Zeng, M., Zhao, F., Zheng, J., Liu, X.: A memory-efficient KinectFusion using octree. In: Hu, S.-M., Martin, R.R. (eds.) CVM 2012. LNCS, vol. 7633, pp. 234–241. Springer, Heidelberg (2012)
Curless, B., Levoy, M.: A volumetric method for building complex models from range images. In: Proceedings of SIGGRAPH 1996, pp. 303–312 (1996)
Whelan, T., Kaess, M., Fallon, M., Johannsson, H., Leonard, J., McDonald, J.: Kintinuous: spatially extended kinectfusion (2012)
Besl, P.J., McKay, N.D.: A Method for Registration of 3-D Shapes. IEEE Trans. Pattern Anal. Mach. Intell. 14(2), 239–256 (1992)
Zhu, X., Cao, Q., Yang, Y., et al.: An improved kinect fusion 3D reconstruction algorithm. Robot 36(2), 129–136 (2014)
Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24(6), 381–395 (1981)
Eggert, D.W., Lorusso, A., Fisher, R.B.: Estimating 3-D rigid body transformations: a comparison of four major algorithms. Mach. Vis. Appl. J. 9(5), 272–290 (1997)
Arun, K.S., Huang, T.S., Blostein, S.D.: Least-squares fitting of two 3-D point sets. IEEE Trans. Pattern Anal. Mach. Intell. J. 5, 698–700 (1987)
Triggs, B., McLauchlan, P.F., Hartley, R.I., Fitzgibbon, A.W.: Bundle adjustment – A modern synthesis. In: Triggs, B., Zisserman, A., Szeliski, R. (eds.) ICCV-WS 1999. LNCS, vol. 1883, pp. 298–372. Springer, Heidelberg (2000)
Acknowledgment
We thank the support of China Postdoctoral Science Foundation, No. 2015M571561 and the National Natural Science Foundation of China, No. 61273331.
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Zhu, X., Cao, Q., Yokoi, H., Jiang, Y. (2016). Large Scale Indoor 3D Mapping Using RGB-D Sensor. In: Kubota, N., Kiguchi, K., Liu, H., Obo, T. (eds) Intelligent Robotics and Applications. ICIRA 2016. Lecture Notes in Computer Science(), vol 9834. Springer, Cham. https://doi.org/10.1007/978-3-319-43506-0_27
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DOI: https://doi.org/10.1007/978-3-319-43506-0_27
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