3 D Graph-based Vision-SLAM Registration and Optimization

environment is a complicated but essential task for navigation and further operations. This has made researchers eager to solve this problem and accordingly many techniques have been investigated using different types of sensors. In this paper we address the Simultaneous Localization and Mapping (SLAM) problem using colored and depth images. We present an overview of the most known techniques with focus on the graph-based mapping, along with a comparison of different algorithms used in registration and optimization. The system is tested on a standard 3D datasets of indoor environment.

[1]  Niko Sünderhauf.  Robust optimization for simultaneous localization and mapping , 2012 .

[2]  Mohamed Roushdy,et al.  Two-Level Topological Mapping and Localization Based on SIFT and The Wavelet Transform , 2013 .

[3]  Wolfram Burgard,et al.  Improved Techniques for Grid Mapping With Rao-Blackwellized Particle Filters , 2007, IEEE Transactions on Robotics.

[4]  Wolfram Burgard,et al.  A Tutorial on Graph-Based SLAM , 2010, IEEE Intelligent Transportation Systems Magazine.

[5]  Tomas Neuzil.  Simultaneous mapping and navigation for skid steered mobile robot , 2008 .

[6]  W. Burgard,et al.  Real-time 3 D visual SLAM with a hand-held RGB-D camera , 2011 .

[7]  Frank Dellaert,et al.  Square Root SAM: Simultaneous Localization and Mapping via Square Root Information Smoothing , 2006, Int. J. Robotics Res..

[8]  A. Guiducci,et al.  Integrating Monocular Vision and Odometry for SLAM , 2003 .

[9]  Piotr Skrzypczynski,et al.  Simultaneous localization and mapping: A feature-based probabilistic approach , 2009, Int. J. Appl. Math. Comput. Sci..

[10]  Gérard G. Medioni,et al.  Visual loop closing using multi-resolution SIFT grids in metric-topological SLAM , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[11]  Aldo Cumani,et al.  Mobile robot localisation with stereo vision , 2005 .

[12]  Mohamed I. Roushdy,et al.  Comparison of 3D feature registration techniques for indoor mapping , 2013, 2013 8th International Conference on Computer Engineering & Systems (ICCES).

[13]  International Journal of Circuits, Systems and Signal Processing , 2022 .

[14]  Vincent Lepetit,et al.  BRIEF: Binary Robust Independent Elementary Features , 2010, ECCV.

[15]  Jizhong Xiao,et al.  Multi-volume occupancy grids: An efficient probabilistic 3D mapping model for micro aerial vehicles , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

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

[17]  Aleksandr V. Segal,et al.  Generalized-ICP , 2009, Robotics: Science and Systems.

[18]  Ian D. Reid,et al.  RSLAM: A System for Large-Scale Mapping in Constant-Time Using Stereo , 2011, International Journal of Computer Vision.

[19]  Wolfram Burgard,et al.  A benchmark for the evaluation of RGB-D SLAM systems , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[20]  Mohamed I. Roushdy,et al.  Comparison of Optimization Techniques for 3 D Graph-based SLAM , 2013 .

[21]  Dieter Fox,et al.  RGB-D Mapping: Using Depth Cameras for Dense 3D Modeling of Indoor Environments , 2010, ISER.

[22]  Jizhong Xiao,et al.  3 D Indoor Mapping for Micro-UAVs Using Hybrid Range Finders and Multi-Volume Occupancy Grids , 2010 .

[23]  Nabil Aouf,et al.  Robust Airborne 3D Visual Simultaneous Localization and Mapping with Observability and Consistency Analysis , 2009, J. Intell. Robotic Syst..

[24]  Michel Dhome,et al.  Monocular SLAM Reconstructions and 3D City Models: Towards a Deep Consistency , 2009, VISIGRAPP.

[25]  M. A. Salem,et al.  Multi-stage localization given topological map for autonomous robots , 2012, 2012 Seventh International Conference on Computer Engineering & Systems (ICCES).

[26]  Wolfram Burgard,et al.  G2o: A general framework for graph optimization , 2011, 2011 IEEE International Conference on Robotics and Automation.

[27]  Ian D. Reid,et al.  Article in Press Robotics and Autonomous Systems ( ) – Robotics and Autonomous Systems a Comparison of Loop Closing Techniques in Monocular Slam , 2022 .

[28]  Christopher Hunt,et al.  Notes on the OpenSURF Library , 2009 .

[29]  Eduardo Mario Nebot,et al.  Recursive scan-matching SLAM , 2007, Robotics Auton. Syst..

[30]  Arturo Gil,et al.  Multi-robot visual SLAM using a Rao-Blackwellized particle filter , 2010, Robotics Auton. Syst..

[31]  Tom Drummond,et al.  Machine Learning for High-Speed Corner Detection , 2006, ECCV.

[32]  Gary R. Bradski,et al.  ORB: An efficient alternative to SIFT or SURF , 2011, 2011 International Conference on Computer Vision.

[33]  Aldo Cumani,et al.  Robot localisation and mapping with stereo vision , 2004 .

[34]  Roland Siegwart,et al.  BRISK: Binary Robust invariant scalable keypoints , 2011, 2011 International Conference on Computer Vision.

[35]  Cyrill Stachniss,et al.  Hierarchical optimization on manifolds for online 2D and 3D mapping , 2010, 2010 IEEE International Conference on Robotics and Automation.

[36]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..