A Simple Framework for Indoor Monocular SLAM

Vision-based simultaneous localization and map building using a single camera, while compelling in theory, have not until recently been considered extensive in the practical realm of the real world. In this paper, we propose a simple framework for the monocular SLAM of an indoor mobile robot using natural line features. Our focus in this paper is on presenting a novel approach for modeling the landmark before integration in monocular SLAM. We also discuss data association improvement in a particle filter approach by using the feature management scheme. In addition, we take constraints between features in the environment into account for reducing estimated errors and thereby improve performance. Our experimental results demonstrate the feasibility of the proposed SLAM algorithm in real-time.

[1]  Vincent Lepetit,et al.  Monocular Model-Based 3D Tracking of Rigid Objects: A Survey , 2005, Found. Trends Comput. Graph. Vis..

[2]  Mohammad Mehdi Fateh,et al.  On the Transforming of Control Space by Manipulator Jacobian , 2008 .

[3]  Andrew J. Davison,et al.  Real-time simultaneous localisation and mapping with a single camera , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[4]  W. W. Armstrong,et al.  Single Camera Stereo for Mobile Robot World Exploration , 1999 .

[5]  Andrew Calway,et al.  Real-Time Camera Tracking Using a Particle Filter , 2005, BMVC.

[6]  Michel Devy,et al.  Undelayed initialization in bearing only SLAM , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[7]  Simon J. Julier,et al.  The scaled unscented transformation , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

[8]  Javier Civera,et al.  Unified Inverse Depth Parametrization for Monocular SLAM , 2006, Robotics: Science and Systems.

[9]  James J. Little,et al.  /spl sigma/SLAM: stereo vision SLAM using the Rao-Blackwellised particle filter and a novel mixture proposal distribution , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[10]  Ian D. Reid,et al.  Real-Time Monocular SLAM with Straight Lines , 2006, BMVC.

[11]  Tom Drummond,et al.  Edge landmarks in monocular SLAM , 2009, Image Vis. Comput..

[12]  Hugh F. Durrant-Whyte,et al.  Model-based multi-sensor data fusion , 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.

[13]  Wesley H. Huang,et al.  Inferring and Enforcing Relative Constraints in SLAM , 2006, WAFR.

[14]  Gamini Dissanayake,et al.  Bearing-only SLAM in Indoor Environments Using a Modified Particle Filter , 2003 .

[15]  Tom Drummond,et al.  Scalable Monocular SLAM , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[16]  Simon Lacroix,et al.  Monocular-vision based SLAM using Line Segments , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[17]  Kyoung Mu Lee,et al.  Visual SLAM with Line and Corner Features , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[18]  Ramón Galán,et al.  Consistency improvement for SLAM - EKF for indoor environments , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[19]  Wolfram Burgard,et al.  Map learning and high-speed navigation in RHINO , 1998 .

[20]  Sebastian Thrun,et al.  FastSLAM: a factored solution to the simultaneous localization and mapping problem , 2002, AAAI/IAAI.

[21]  Don Ray Murray,et al.  Using Real-Time Stereo Vision for Mobile Robot Navigation , 2000, Auton. Robots.

[22]  Bingrong Hong,et al.  Novel Rao-Blackwellized Particle Filter for Mobile Robot SLAM Using Monocular Vision , 2007 .

[23]  James J. Little,et al.  Design and analysis of a framework for real-time vision-based SLAM using Rao-Blackwellised particle filters , 2006, The 3rd Canadian Conference on Computer and Robot Vision (CRV'06).

[24]  Simon Baker,et al.  Lucas-Kanade 20 Years On: A Unifying Framework , 2004, International Journal of Computer Vision.

[25]  Byung-Ju Yi,et al.  Singularity-Free Dynamic Modeling Including Wheel Dynamics for an Omni-Directional Mobile Robot with Three Caster Wheels , 2008 .

[26]  Henrik I. Christensen,et al.  Vision SLAM in the Measurement Subspace , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.