Assessment of Laser Range Finders in risky environments

This paper characterizes four commercial laser range finders (LRF) while operating under adverse conditions, namely: low visibility, and multiple types of target surfaces, including different optical properties, angles and radiant surfaces. The study considered two scanning LRF commonly used in mobile robotics: the Sick LMS200 and the Hokuyo URG-04LX, and two industrial punctual LRFs: the IFM Efector O1D100 and the Sick DT60. Based on the results obtained, a set of conclusions and recommendations are taken considering the utilization of LRF in mobile robots operating in risky and adverse environments, like firefighting applications.

[1]  Martial Hebert,et al.  3-D measurements from imaging laser radars: how good are they? , 1991, Proceedings IROS '91:IEEE/RSJ International Workshop on Intelligent Robots and Systems '91.

[2]  Martial Hebert,et al.  3D measurements from imaging laser radars: how good are they? , 1992, Image Vis. Comput..

[3]  Hobart R. Everett,et al.  Where am I?" sensors and methods for mobile robot positioning , 1996 .

[4]  Antonio Reina,et al.  Characterization of a radial laser scanner for mobile robot navigation , 1997, Proceedings of the 1997 IEEE/RSJ International Conference on Intelligent Robot and Systems. Innovative Robotics for Real-World Applications. IROS '97.

[5]  M. Amann,et al.  Laser ranging: a critical review of usual techniques for distance measurement , 2001 .

[6]  Cang Ye,et al.  Characterization of a 2D laser scanner for mobile robot obstacle negotiation , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[7]  Hong Zhang,et al.  Characterization of acuity laser range finder , 2004, ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004..

[8]  Shin'ichi Yuta,et al.  Development of ultra-small lightweight optical range sensor system , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[9]  Pradip Sheth,et al.  Characterization of Infrared Range-Finder PBS-03JN for 2-D Mapping , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[10]  Kazunori Ohno,et al.  Dense 3D map building based on LRF data and color image fusion , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.