Entropy Minimization SLAM Using Stereo Vision

In this paper we present an information-based approach to solve the SLAM problem using stereo vision. This approach results for an improvement, in terms of both efficiency and robustness, of our early multi-view ICP randomized algorithm. Instead of minimizing an ICP-based cost, we propose the minimization of the entropy of the 2D distribution induced by the projection of the 3D point cloud. In addition we embed both the egomotion/action estimation algorithm which precedes global rectification and the new global rectification algorithm in an autonomous exploration schema. We assume plane-parallel environments and, for the sake of efficiency, we also assume a flat floor and a fixed stereo camera mounted on the robot. We show successful experiments both under tele-operating the robot and under autonomous navigation.

[1]  Wolfram Burgard,et al.  Learning compact 3D models of indoor and outdoor environments with a mobile robot , 2003, Robotics Auton. Syst..

[2]  Jorge Dias,et al.  World feature detection and mapping using stereovision and inertial sensors , 2003, Robotics Auton. Syst..

[3]  Hong Bing-rong,et al.  Real-time acquisition of compact volumetric maps , 2006 .

[4]  P. Boulanger,et al.  Sensor based creation of indoor virtual environment models , 1997, Proceedings. International Conference on Virtual Systems and MultiMedia VSMM '97 (Cat. No.97TB100182).

[5]  Ioannis Stamos,et al.  AVENUE: Automated site modeling in urban environments , 2001, Proceedings Third International Conference on 3-D Digital Imaging and Modeling.

[6]  Wolfram Burgard,et al.  A real-time algorithm for mobile robot mapping with applications to multi-robot and 3D mapping , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[7]  Joachim Hertzberg,et al.  An autonomous mobile robot with a 3D laser range finder for 3D exploration and digitalization of indoor environments , 2003, Robotics Auton. Syst..

[8]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[9]  James J. Little,et al.  Vision-based mapping with backward correction , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[10]  Zhengyou Zhang,et al.  Iterative point matching for registration of free-form curves and surfaces , 1994, International Journal of Computer Vision.

[11]  Don Ray Murray,et al.  Stereo vision based mapping and navigation for mobile robots , 1997, Proceedings of International Conference on Robotics and Automation.

[12]  Jean-Claude Latombe,et al.  Numerical potential field techniques for robot path planning , 1991, Fifth International Conference on Advanced Robotics 'Robots in Unstructured Environments.

[13]  Evangelos E. Milios,et al.  Globally Consistent Range Scan Alignment for Environment Mapping , 1997, Auton. Robots.

[14]  Hans P. Moravec.  Robot spatial perception by stereoscopic vision and 3D evidence grids , 1996 .

[15]  Peter K. Allen,et al.  Design, architecture and control of a mobile site-modeling robot , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

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

[17]  Kurt Konolige,et al.  Visually Realistic Mapping of a Planar Environment with Stereo , 2000, ISER.

[18]  James J. Little,et al.  Mobile Robot Localization and Mapping with Uncertainty using Scale-Invariant Visual Landmarks , 2002, Int. J. Robotics Res..

[19]  James J. Little,et al.  Vision-based mobile robot localization and mapping using scale-invariant features , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

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

[21]  Juan Manuel Sáez,et al.  A global 3D map-building approach using stereo vision , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[22]  Roland Siegwart,et al.  Open challenges in SLAM: an optimal solution based on shift and rotation invariants , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[23]  C. Q. Little,et al.  Registration of range data using a hybrid simulated annealing and iterative closest point algorithm , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[24]  Bruce Randall Donald,et al.  Real-time robot motion planning using rasterizing computer graphics hardware , 1990, SIGGRAPH.