Rendering of 3D Maps with Additional Information for Operator of a Coal Mine Mobile Robot
The paper focuses on visualization of point clouds made by a 3D scanner mounted on a mobile robot Telerescuer designed for reconnaissance of coal mines affected by a disaster. Briefly are described some algorithms used for point cloud pre-processing – voxelization for data reduction, outliers removing for filtering of erroneous data and smoothing for additional filtering of noise data. These algorithms are implemented in C++ using the Point Cloud Library.
The next parts focus on the rendering engine created for this application, with more detailed information about drawing individual points with specific size and using the point colours to support better representation of shapes in the map by shading/lighting and additional colouring based on orientation of normal vectors. Mentioned are also some crucial optimizations of rendering and processing performance build on a simple custom system similar to Octree.
The final part presents some methods of adding additional information to the map, including sensor readings (temperature, gas concentration, wind speed etc.) and distance measurements (exact numeric measuring, rough dimension estimation by colour coding, corridor cross-section etc.). Integration of these data and the advanced rendering techniques not typically used for point cloud visualization are the innovative approaches described in this paper.
KeywordsVisualization 3D map 3D scanning Point cloud Mobile robot PCL
- 1.Ray, D.N., Majumder, S., Maity, A., Roy, B., Karmakar, S.: Design and development of a mobile robot for environment monitoring in underground coal mines. In: Proceedings of the 2015 Conference on Advances in Robotics (2015). ISBN: 978-1-4503-3356-6Google Scholar
- 2.Gomathi, V., Sowmeya, S., Avudaiammal, P.S.: Design of an adaptive coal mine rescue robot using wireless sensor networks. Int. J. Comput. Appl. 2015(2), 8–11 (2015)Google Scholar
- 5.Moczulski, W., Cyran, K., Novak, P., Rodriguez, A., Januszka, M.: TeleRescuer - a concept of a system for teleimmersion of a rescuer to areas of coal mines affected by catastrophes. VI. Międzynarodowa Konferencja Systemy Mechatroniczne Pojazdów i Maszyn Roboczych 2014 (2014)Google Scholar
- 6.Olivka, P., Mihola, M., Novák, P., Kot, T., Babjak, J.: The 3D laser range finder design for the navigation and mapping for the coal mine robot. In: Proceedings of the 2016 17th International Carpathian Control Conference ICCC (2016). ISBN 978-1-47-993528-4Google Scholar
- 7.Blanco, J.L.: Efficiently rendering point clouds of millions of points. http://www.mrpt.org/tutorials/programming/gui-windows-and-3d-opengl-graphics/efficiently_rendering_point_clouds_of_millions_of_points/
- 8.Rusu, R.B., Willow, G., Park, M.: 3D is here: Point Cloud Library (PCL). In: IEEE International Conference on Robotics and Automation (ICRA), pp. 1–4 (2011). ISBN 978-1-61284-386-5Google Scholar
- 9.Universität Karlsruhe. Point Cloud Representation. http://geom.ivd.kit.edu/downloads/pubs/pub-linsen_2001.pdf
- 10.PCL – Point Cloud Library. http://pointclouds.org/
- 11.Removing outliers using a Statistical Outlier Removal filter. http://pointclouds.org/documentation/tutorials/statistical_outlier.php
- 12.Downsampling a PointCloud using a VoxelGrid filter. http://pointclouds.org/documentation/tutorials/voxel_grid.php
- 13.Smoothing and normal estimation based on polynomial reconstruction. http://pointclouds.org/documentation/tutorials/resampling.php