Dealing with laser scanner failure: Mirrors and windows

This paper addresses the problem of laser scanner failure on mirrors and windows. Mirrors and glasses are quite common objects that appear in our daily lives. However, while laser scanners play an important role nowadays in the field of robotics, there are very few literatures that address the related issues such as mirror reflection and glass transparency. We introduce a sensor fusion technique to detect the potential obstacles not seen by laser scanners. A laser-based mirror tracker is also proposed to figure out the mirror locations in the environment. The mirror tracking method is seamlessly integrated with the occupancy grid map representation and the mobile robot localization framework. The proposed approaches have been demonstrated using data from sonar sensors and a laser scanner equipped on the NTU-PAL5 robot. Mirrors and windows, as potential obstacles, are successfully detected and tracked.

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

[2]  Gregory Dudek,et al.  Vision-based robot localization without explicit object models , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[3]  Alberto Elfes,et al.  Using occupancy grids for mobile robot perception and navigation , 1989, Computer.

[4]  Alberto Elfes,et al.  Occupancy grids: a probabilistic framework for robot perception and navigation , 1989 .

[5]  Charles E. Thorpe,et al.  A hierarchical object based representation for simultaneous localization and mapping , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

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

[7]  William Whittaker,et al.  A robust approach to high‐speed navigation for unrehearsed desert terrain , 2007 .

[8]  Klaus-Werner Jörg World modeling for an autonomous mobile robot using heterogenous sensor information , 1995, Robotics Auton. Syst..

[9]  Sebastian Thrun,et al.  A Probabilistic On-Line Mapping Algorithm for Teams of Mobile Robots , 2001, Int. J. Robotics Res..

[10]  Lindsay Kleeman,et al.  Advanced sonar and laser range finder fusion for simultaneous localization and mapping , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).