Robust Self-Localization in Industrial Environments based on 3D Ceiling Structures

This video introduces a new perceptual model for Monte Carlo Localization (MCL). In our approach a 3D laser scanner is used to observe the ceiling. The MCL matches ceiling structures like beams, columns, air condition and lightning installation against a world model containing line and point features. Thus the localization is not effected by clutter or any kind of dynamic obstacles on the ground level. Different experiments show that our system can be used to localize robustly in factory buildings and halls. Experimental results include a 5 day run of an autonomous fork lift truck at a logistics fair in Hannover.

[1]  Horst-Michael Groß,et al.  Vision-based Monte Carlo self-localization for a mobile service robot acting as shopping assistant in a home store , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[2]  Sebastian Thrun,et al.  6D SLAM with an application in autonomous mine mapping , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[3]  Wolfram Burgard,et al.  Monte Carlo localization for mobile robots , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[4]  Wolfram Burgard,et al.  Probabilistic Algorithms and the Interactive Museum Tour-Guide Robot Minerva , 2000, Int. J. Robotics Res..

[5]  Nando de Freitas,et al.  Sequential Monte Carlo in Practice , 2001 .

[6]  Tom Duckett,et al.  A multilevel relaxation algorithm for simultaneous localization and mapping , 2005, IEEE Transactions on Robotics.

[7]  Carl F. R. Weiman,et al.  Helpmate autonomous mobile robot nav-igation system , 1991 .

[8]  S. Ito,et al.  Navigation system based on ceiling landmark recognition for autonomous mobile robot , 1993, Proceedings of IECON '93 - 19th Annual Conference of IEEE Industrial Electronics.

[9]  Henrik I. Christensen,et al.  2D mapping of cluttered indoor environments by means of 3D perception , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.