[robotics-worldwide] Online datasets for long-term mapping by mobile robots
tduckett at lincoln.ac.uk
Fri Mar 30 03:20:38 PDT 2012
ONLINE DATASETS FOR LONG-TERM MAPPING BY MOBILE ROBOTS
Persistent mapping in dynamic environments is one of the current outstanding challenges for mobile robotics research to enable long-term automomy. Experimental validation of algorithms for long-term mapping requires data collected over longer periods of time.
Several datasets for long-term mobile robot mapping and localisation in indoor environments are provided under an Open Data Commons Attribution License at the following URL:
(short URL: http://lncn.eu/ijvz )
The datasets consist of time-stamped multi-session robot sensor data, including
(1) greyscale omni-directional images, 2D laser scans and odometry data recorded at the University of Lincoln, UK over periods of up to 7 weeks, and (2) 2D laser scans and odometry data recorded at the University of Örebro, Sweden over a 5 week period, as reported in the following papers:
Feras Dayoub, Tom Duckett and Grzegorz Cielniak, Long-Term Experiments with an Adaptive Spherical View Representation for Navigation in Changing Environments, Robotics and Autonomous Systems, Vol. 59, No. 5, pp. 285-295, May 2011.
Peter Biber and Tom Duckett, Experimental Analysis of Sample-Based Maps for Long-Term SLAM, International Journal of Robotics Research, Vol. 28, No. 1, pp. 20-33, 2009.
Dr. Tom Duckett
Reader in Computer Science
University of Lincoln
Phone: +44 1522 837113
Fax: +44 1522 886974
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