Laser-based geometrical modeling of large-scale architectural structures using co-operative multiple robots
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For the construction of 3-D shape models of large-scale architectural structures using laser range finders, a number of range images are taken from different viewpoints around the targets. Next, the obtained images are normally aligned by post-processing procedures, such as the ICP algorithm. However, to obtain convergent results in the ICP algorithm and align these range images to their proper positions, the initial position of each range image needs to be manually aligned to roughly the correct position. This paper proposes a new measurement and modeling system using a group of multiple robots and an on-board laser range finder. Each measurement position is identified by a highly precise positioning technique called the Co-operative Positioning System (CPS), which utilizes the characteristics of the multiple-robot system. Therefore, the proposed system can construct 3-D shapes of large-scale architectural structures without any post-processing procedure or manual intervention. In addition, it is possible to register range images even if the number of measurements is few and there are only a few range images, for example, due to range images containing insufficient feature shapes or overlapping regions. Measurement experiments in unknown and large indoor/outdoor environments including a large hall, a building, an urban district, and a cultural heritage have been successfully carried out using the newly developed measurement system consisting of three mobile robots named CPS-V. Path generation experiments of the mobile robots based on the partially measured 3-D model are also presented.
KeywordsSLAM 3-D map Multiple robots Cooperative positioning Laser range finder
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- Chen, Y., & Medioni, G. (1992). Object modelling by registration of multiple range images. Image and Vision Computing, 3(10), 145–155. Google Scholar
- Cole, D. M., & Newman, P. M. (2006). Using laser range data for 3d slam in outdoor environment. In Proc. IEEE international conference on robotics and automation (pp. 1556–1563), 2006 Google Scholar
- Howard, A., Matarić, M. J., & Sukhatme, G. S. (2003). Putting the ‘i’ in ‘team’: an ego-centric approach to cooperative localization. In Proc. IEEE international conference on robotics and automation (ICRA) (pp. 868–892), September 2003 Google Scholar
- Ikeuchi, K., Hasegawa, K., Nakazawa, A., Takamatsu, J., Oishi, T., & Masuda, T. (2004). Bayon digital archival project. In Proceedings of the tenth international conference on virtual system and multimedia (pp. 334–343), November 2004 Google Scholar
- Ikeuchi, K., Oishi, T., Takamatsu, J., Sagawa, R., Nakazawa, A., Kurazume, R., Nishino, N., Kamakura, M., & Okamoto, Y. (2007). The great Buddha project: digitally archiving, restoring, and analyzing cultural heritage objects. International Journal of Computer Vision, 75(1), 189–208. CrossRefGoogle Scholar
- Kurazume, R., Nagata, S., & Hirose, S. (1994). Cooperative positioning with multiple robots. In Proc. IEEE int. conf. on robotics and automation (vol. 2, pp. 1250–1257), 1994 Google Scholar
- Levoy, M., Pulli, K., Curless, B., Rusinkiewicz, S., Koller, D., Pereira, L., Ginzton, M., Anderson, S., Davis, J., Ginsberg, J., Shade, J., & Fulk, D. (2000). The digital Michelangelo project: 3d scanning of large statues. In Proc. ACM SIGGRAPH 2000 (pp. 131–144), July 2000. Google Scholar
- Marco, M. D., Garulli, A., Giannitrapani, A., & Vicino, A. (2003). Simultaneous localization and map building for a team of cooperating robots: a set membership approach. IEEE Transactions on Robotics and Automation, 19(2), 1243–1256. Google Scholar
- Nerurkar, E., Roumeliotis, S., & Martinelli, A. (2009). Distributed maximum a posteriori estimation for multi-robot cooperative localization. In Proceedings of the 2009 IEEE international conference on robotics and automation (pp. 1402–1409), May 2009 Google Scholar
- Nüchter, A., Surmann, H., Lingemann, K., Hertzberg, J., & Thrun, S. (2004). 6d slam with an application in autonomous mine mapping. In Proc. IEEE international conference on robotics and automation (pp. 1998–2003), 2004 Google Scholar
- Ohno, K., Tsubouchi, T., & Yuta, S. (2004). Outdoor map building based on odometry and rtk-gps positioning fusion. In Proc. IEEE international conference on robotics and automation (pp. 684–690), April 2004 Google Scholar
- Rekleitis, I., Dudek, G., & Milios, E. (2002). Multi-robot cooperative localization: a study of trade-offs between efficiency and accuracy. In Proc. IEEE/RSJ IROS’02 (pp. 2690–2696), September 30–October 4 2002 Google Scholar
- Spletzer, J., Das, A., Fierro, R., Taylor, C., Kumar, V., & Ostrowski, J. (2001). Cooperative localization and control for multi-robot manipulation. In Proc. of IEEE/RSJ international conference on intelligent robots and systems (vol. 2, pp. 631–636), November 2001 Google Scholar
- Toppan vr system. http://biz.toppan.co.jp/vr/ (2011).
- Weingarten, J., & Siegwart, R. (2005). Ekf-based 3d slam for structured environment reconstruction. In Proc. IEEE/RSJ international conference on intelligent robots and system (pp. 2089–2094), 2005 Google Scholar