Advanced Mapping Robot and High-Resolution Dataset
This work provides a new dataset for robotics researchers to benchmark mapping algorithms, but it is incremental as it focuses on data collection rather than algorithmic innovation.
The authors introduced a hardware-synchronized mapping robot with multiple high-resolution sensors to collect precise datasets for evaluating mapping algorithms, generating maps and trajectory data for reproducibility and comparison.
This paper presents a fully hardware synchronized mapping robot with support for a hardware synchronized external tracking system, for super-precise timing and localization. Nine high-resolution cameras and two 32-beam 3D Lidars were used along with a professional, static 3D scanner for ground truth map collection. With all the sensors calibrated on the mapping robot, three datasets are collected 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. We provide the datasets for download and the mapping and evaluation procedures are made in a very easily reproducible manner for maximum comparability. We have also conducted a survey on available robotics-related datasets and compiled a big table with those datasets and a number of properties of them.