Interior mapping of a building: A real-life experiment with Microsoft Kinect for Windows v1 and RGBD-SLAM

Mapping the interior of a building is a nice step to obtain the description of that building. In that context, this article presents the use of a low cost 3D sensor, the Microsoft Kinect for Windows v1, associated to RGBDSLAM in order to perform that mapping. Even if the method is well-known and has showed its performance, its use is not as simple as it looks like. Limitations of both the sensor and the method have to be dealt with and great care has to be taken during the measurements. Some post-processing is also needed to obtain nice point cloud as results of the experiments. Emphasis is put on the point cloud' size and the storage needed. Finally, the data obtained after an internship measurement campaign are presented and show to fulfill nicely the goals and requirements of the study.

[1]  Radu Bogdan Rusu,et al.  3D is here: Point Cloud Library (PCL) , 2011, 2011 IEEE International Conference on Robotics and Automation.

[2]  Yves Bergeon,et al.  Low cost 3D mapping for indoor navigation , 2015, International Conference on Military Technologies (ICMT) 2015.

[3]  Yves Bergeon,et al.  UAV assisted landing on moving UGV , 2015, International Conference on Military Technologies (ICMT) 2015.

[4]  Mohamed S. Shehata,et al.  Image Matching Using SIFT, SURF, BRIEF and ORB: Performance Comparison for Distorted Images , 2017, ArXiv.

[5]  Wolfram Burgard,et al.  An evaluation of the RGB-D SLAM system , 2012, 2012 IEEE International Conference on Robotics and Automation.

[6]  Yves Bergeon,et al.  Proactive Teaching of Mechatronics in Master Courses – Project Case Study , 2016 .

[7]  Wolfram Burgard,et al.  Probabilistic Robotics (Intelligent Robotics and Autonomous Agents) , 2005 .

[8]  Wolfram Burgard,et al.  OctoMap: an efficient probabilistic 3D mapping framework based on octrees , 2013, Autonomous Robots.