An Analysis of 3D surface curvature features for 3D SLAM using Kinect data /

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2014

Author

Adil, Ömer Faruk

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The introduction of affordable and sufficiently accurate range sensors such as TOF cameras, laser scanners and RGBD cameras has significantly contributed to the robotic applications like SLAM. Although range sensors are used extensively and successfully in SLAM applications, there is still room for improvement in the sensor data utilization process. In this thesis a novel approach for the feature extraction part of 3D SLAM is introduced. The use of compact surface curvature features in the SLAM algorithm is proposed which will appear for the first time in the literature. The proposed method uses mean and Gaussian curvature calculations to extract curvedness features from RGBD output of Microsoft Kinect sensor. The extracted features are then fed to the SLAM algorithm to be used in the global data association process. The results are compared to the state-of-the art feature extraction techniques for SLAM, namely plane features, SURF features and corner features on real Kinect dataset sequences which are conventionally used as benchmark for SLAM algorithms.

Subject Keywords

Curvature., Surfaces., Detectors., Mobile robots., Autonomous robots., Kinect (Programmable controller).

URI

http://etd.lib.metu.edu.tr/upload/12618305/index.pdf
https://hdl.handle.net/11511/24299

Collections

Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

Ö. F. Adil, “An Analysis of 3D surface curvature features for 3D SLAM using Kinect data /,” M.S. - Master of Science, Middle East Technical University, 2014.