Towards Generation and Evaluation of Comprehensive Mapping Robot Datasets
May 23, 2019 Β· Declared Dead Β· π IEEE International Conference on Robotics and Automation
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Authors
Hongyu Chen, Xiting Zhao, Jianwen Luo, Zhijie Yang, Zehao Zhao, Haochuan Wan, Xiaoya Ye, Guangyuan Weng, Zhenpeng He, Tian Dong, SΓΆren Schwertfeger
arXiv ID
1905.09483
Category
cs.RO: Robotics
Citations
9
Venue
IEEE International Conference on Robotics and Automation
Last Checked
4 months ago
Abstract
This paper presents a fully hardware synchronized mapping robot with support for a hardware synchronized external tracking system, for super-precise timing and localization. We also employ a professional, static 3D scanner for ground truth map collection. Three datasets are generated to evaluate the performance of mapping algorithms within a room and between rooms. Based on these datasets we generate maps and trajectory data, which is then fed into evaluation algorithms. The mapping and evaluation procedures are made in a very easily reproducible manner for maximum comparability. In the end we can draw a couple of conclusions about the tested SLAM algorithms.
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