We present two sets of outdoor LiDAR dataset for semantic place labeling using two different LiDAR sensors. Recognizing outdoor places according to semantic categories is useful for a mobile service robot, which works adaptively according to the surrounding conditions. However, place recognition is not straight forward due to the wide variety of environments and sensor performance limitations. In this paper, we present two sets of outdoor LiDAR dataset captured by two different LiDAR sensors, SICK and FARO LiDAR sensors. The LiDAR datasets consist of four different semantic places including forest, residential area, parking lot and urban area categories. The datasets are useful for benchmarking vision-based semantic place labeling in outdoor environments.
|Number of pages||2|
|Journal||The Abstracts of the international conference on advanced mechatronics : toward evolutionary fusion of IT and mechatronics : ICAM|
|Publication status||Published - 2015|