Skip to main content
Log in

Laser-based geometrical modeling of large-scale architectural structures using co-operative multiple robots

  • Published:
Autonomous Robots Aims and scope Submit manuscript

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Besl, P. J., & McKay, N. D. (1992). A method for registration of 3-d shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2(14), 239–256.

    Article  Google Scholar 

  • 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. (2006). Multi-robot simultaneous localization and mapping using particle filters. The International Journal of Robotics Research, 25(125), 1243–1256.

    Article  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.

    Article  Google Scholar 

  • Kurazume, R., & Hirose, S. (2000). An experimental study of a cooperative positioning system. Autonomous Robots, 8(1), 43–52.

    Article  Google 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 

  • Montesano, L., Gaspar, J., Santos-Victor, J., & Montano, L. (2005). Cooperative localization by fusing vision-based bearing measurements and motion. In Proc. of IEEE/RSJ international conference on intelligent robots and systems (pp. 2333–2338), August 2005

    Chapter  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 

  • Panzieri, S., Pascucci, F., & Setola, R. (2006). Multirobot localization using interlaced extended Kalman filter. In Proc. of the IEEE/RSJ international conference on intelligent robots and systems (pp. 2816–2821), October 2006

    Chapter  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 

  • Thrun, S. (2001). A probabilistic online mapping algorithm for teams of mobile robots. The International Journal of Robotics Research, 20(5), 335–363.

    Article  Google Scholar 

  • Thrun, S., & Montemerlo, M. (2006). The graph slam algorithm with applications to large-scale mapping of urban structures. The International Journal of Robotics Research, 25(5–6), 403–429.

    Article  Google Scholar 

  • Toppan vr system. http://biz.toppan.co.jp/vr/ (2011).

  • Triebel, R., Pfaff, P., & Burgard, W. (2006). Multi-level surface maps for outdoor terrain mapping and loop closing. In International conference on intelligent robots and systems (IROS) (pp. 2276–2282), 2006

    Chapter  Google Scholar 

  • 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 

  • Zhao, H., & Shibasaki, R. (2003). Reconstructing a textured cad model of an urban environment using vehicle-borne lase range scanners and line cameras. Machine Vision and Applications, 14, 35–41.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yukihiro Tobata.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Tobata, Y., Kurazume, R., Noda, Y. et al. Laser-based geometrical modeling of large-scale architectural structures using co-operative multiple robots. Auton Robot 32, 49–62 (2012). https://doi.org/10.1007/s10514-011-9256-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10514-011-9256-x

Keywords

Navigation