4 papers
Collecting Larg-Scale Robotic Datasets on a High-Speed Mobile Platform
Yuxin Lin, Jiaxuan Ma, Sizhe Gu +6
Mobile robotics datasets are essential for research on robotics, for example for research on Simultaneous Localization and Mapping (SLAM). Therefore the ShanghaiTech Mapping Robot…
High-Quality, ROS Compatible Video Encoding and Decoding for High-Definition Datasets
Jian Li, Bowen Xu, Sören Schwertfeger
Robotic datasets are important for scientific benchmarking and developing algorithms, for example for Simultaneous Localization and Mapping (SLAM). Modern robotic datasets feature…
Benchmarking SLAM Algorithms in the Cloud: The SLAM Hive Benchmarking Suite
Xinzhe Liu, Yuanyuan Yang, Bowen Xu +2
Evaluating the performance of Simultaneous Localization and Mapping (SLAM) algorithms is essential for scientists and users of robotic systems alike. But there are a multitude of d…
ShanghaiTech Mapping Robot is All You Need: Robot System for Collecting Universal Ground Vehicle Datasets
Bowen Xu, Xiting Zhao, Delin Feng +2
This paper presents the ShanghaiTech Mapping Robot, a state-of-the-art unmanned ground vehicle (UGV) designed for collecting comprehensive multi-sensor datasets to support research…