Live structural modeling using RGB-D SLAM

Nicolas Olivier; Hideaki Uchiyama; Masashi Mishima; Diego Thomas; Rin Ichiro Taniguchi; Rafael Roberto; Joao Paulo Lima; Veronica Teichrieb

doi:10.1109/ICRA.2018.8460973

Live structural modeling using RGB-D SLAM

Nicolas Olivier, Hideaki Uchiyama, Masashi Mishima, Diego Thomas, Rin Ichiro Taniguchi, Rafael Roberto, Joao Paulo Lima, Veronica Teichrieb

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Citations (Scopus)

Abstract

This paper presents a method for localizing primitive shapes in a dense point cloud computed by the RGB-D SLAM system. To stably generate a shape map containing only primitive shapes, the primitive shape is incrementally modeled by fusing the shapes estimated at previous frames in the SLAM, so that an accurate shape can be finally generated. Specifically, the history of the fusing process is used to avoid the influence of error accumulation in the SLAM. The point cloud of the shape is then updated by fusing the points in all the previous frames into a single point cloud. In the experimental results, we show that metric primitive modeling in texture-less and unprepared environments can be achieved online.

Original language	English
Title of host publication	2018 IEEE International Conference on Robotics and Automation, ICRA 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	6352-6358
Number of pages	7
ISBN (Electronic)	9781538630815
DOIs	https://doi.org/10.1109/ICRA.2018.8460973
Publication status	Published - Sept 10 2018
Event	2018 IEEE International Conference on Robotics and Automation, ICRA 2018 - Brisbane, Australia Duration: May 21 2018 → May 25 2018

Publication series

Name	Proceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)	1050-4729

Conference

Conference	2018 IEEE International Conference on Robotics and Automation, ICRA 2018
Country/Territory	Australia
City	Brisbane
Period	5/21/18 → 5/25/18

All Science Journal Classification (ASJC) codes

Software
Control and Systems Engineering
Artificial Intelligence
Electrical and Electronic Engineering

Access to Document

10.1109/ICRA.2018.8460973

Cite this

Olivier, N., Uchiyama, H., Mishima, M., Thomas, D., Taniguchi, R. I., Roberto, R., Lima, J. P., & Teichrieb, V. (2018). Live structural modeling using RGB-D SLAM. In 2018 IEEE International Conference on Robotics and Automation, ICRA 2018 (pp. 6352-6358). Article 8460973 (Proceedings - IEEE International Conference on Robotics and Automation). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICRA.2018.8460973

Live structural modeling using RGB-D SLAM. / Olivier, Nicolas; Uchiyama, Hideaki; Mishima, Masashi et al.
2018 IEEE International Conference on Robotics and Automation, ICRA 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 6352-6358 8460973 (Proceedings - IEEE International Conference on Robotics and Automation).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Olivier, N, Uchiyama, H, Mishima, M, Thomas, D , Taniguchi, RI, Roberto, R, Lima, JP & Teichrieb, V 2018, Live structural modeling using RGB-D SLAM. in 2018 IEEE International Conference on Robotics and Automation, ICRA 2018., 8460973, Proceedings - IEEE International Conference on Robotics and Automation, Institute of Electrical and Electronics Engineers Inc., pp. 6352-6358, 2018 IEEE International Conference on Robotics and Automation, ICRA 2018, Brisbane, Australia, 5/21/18. https://doi.org/10.1109/ICRA.2018.8460973

Olivier N, Uchiyama H, Mishima M, Thomas D , Taniguchi RI, Roberto R et al. Live structural modeling using RGB-D SLAM. In 2018 IEEE International Conference on Robotics and Automation, ICRA 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 6352-6358. 8460973. (Proceedings - IEEE International Conference on Robotics and Automation). doi: 10.1109/ICRA.2018.8460973

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AB - This paper presents a method for localizing primitive shapes in a dense point cloud computed by the RGB-D SLAM system. To stably generate a shape map containing only primitive shapes, the primitive shape is incrementally modeled by fusing the shapes estimated at previous frames in the SLAM, so that an accurate shape can be finally generated. Specifically, the history of the fusing process is used to avoid the influence of error accumulation in the SLAM. The point cloud of the shape is then updated by fusing the points in all the previous frames into a single point cloud. In the experimental results, we show that metric primitive modeling in texture-less and unprepared environments can be achieved online.

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Live structural modeling using RGB-D SLAM

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