Papers › Towards Generation and Evaluation of Comprehensive Mapping Robot Datasets
Towards Generation and Evaluation of Comprehensive Mapping Robot Datasets
Hongyu Chen, Xiting Zhao, Jianwen Luo, Zhijie Yang, Zehao Zhao, Haochuan Wan, Xiaoya Ye, Guangyuan Weng, Zhenpeng He, Tian Dong, Sören Schwertfeger
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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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