Abstract
The current state of technology permits very accurate 3D reconstructions of real scenes acquiring information through quite different sensors altogether. A high precision modelling that allows simulating any element of the environment on virtual interfaces has also been achieved. This paper illustrates a methodology to correctly model a 3D reconstructed scene, with either a camera RGB-D or a laser, and how to integrate and display it in virtual reality environments based on Unity, as well as a comparison between both results. The main interest regarding this line of research consists in the automation of all the process from the map generation to its visualisation with the VR glasses, although this first approach only managed to get results using several programs manually. The long-term objective would be indeed a real-time immersion in Unity interacting with the scene seen by the camera.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Cong, V., Linh, H.: 3D medical image reconstruction. Biomedical Engineering Department Faculty of Applied Science, HCMC University of Technology, pp. 1–5 (2002)
Bruno, F., Bruno, S., De Sensi, G., Luchi, M., Mancuso, S., Muzzupappa, M.: From 3d reconstruction to virtual reality: a complete methodology for digital archaeological exhibition. J. Cult. Heritage 11, 42–49 (2010)
Cazamias, J., Raj, A.: Virtualized reality using depth camera point clouds. Stanford EE 267: Virtual Reality, Course Report (2016)
Codd-Downey, R., Forooshani, P., Speers, A., Wang, H., Jenkin, M.: From ROS to unity: leveraging robot and virtual environment middleware for immersive teleoperation. In: 2014 IEEE International Conference on Information and Automation, ICIA 2014, pp. 932–936 (2014)
Labb, M., Michaud, F.: Online global loop closure detection for large-scale multi-session graph-based slam. In: IEEE International Conference on Intelligent Robots and Systems, pp. 2661–2666 (2014)
Pomerleau, F., Colas, F., Siegwart, R., Magnenat, S.: Comparing ICP variants on real-world data sets. Autonom. Robot. 34(3), 133–148 (2013)
Ahrnes, J., Geveci, B., Law, C.: ParaView: an end-user tool for large-data visualization. In: Hansen, C.D., Johnson, C.R. (eds.) Visualization Handbook, pp. 717–731. Butterworth-Heinemann, Burlington (2005)
Rusu, R., Cousins, S.: 3D is here: point cloud library. In: IEEE International Conference on Robotics and Automation, pp. 1–4 (2011)
Cignoni, P., Callieri, M., Corsini, M., Dellepiane, M., Ganovelli, F., Ranzuglia, G.: MeshLab: an open-source mesh processing tool. In: Sixth Eurographics Italian Chapter Conference, pp. 129–136 (2008)
Acknowledgments
This work was partially supported by the Robotics and Cybernetics Group at Universidad Politécnica de Madrid (Spain), and it was funded under the projects: PRIC (Proteccin Robotizada de Infraestructuras Crticas; DPI2014-56985-R), sponsored by the Spanish Ministry of Economy and Competitiveness and RoboCity2030-III-CM (Robtica aplicada a la mejora de la calidad de vida de los ciudadanos. fase III; S2013/MIT-2748), funded by Programas de Actividades I+D en la Comunidad de Madrid and cofunded by Structural Founds of the EU.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Navarro, F., Fdez, J., Garzón, M., Roldán, J.J., Barrientos, A. (2018). Integrating 3D Reconstruction and Virtual Reality: A New Approach for Immersive Teleoperation. In: Ollero, A., Sanfeliu, A., Montano, L., Lau, N., Cardeira, C. (eds) ROBOT 2017: Third Iberian Robotics Conference. ROBOT 2017. Advances in Intelligent Systems and Computing, vol 694. Springer, Cham. https://doi.org/10.1007/978-3-319-70836-2_50
Download citation
DOI: https://doi.org/10.1007/978-3-319-70836-2_50
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-70835-5
Online ISBN: 978-3-319-70836-2
eBook Packages: EngineeringEngineering (R0)