Description
We take advantage of our Avenger 8x8 driving platform to develop a challenging off-road dataset in mountainous and forested scenarios. We equiped our platform with two industrial camera, two Velodyne laser scanner and a GPS localization system. The dataset is comprised of 5 sequences captured while driving in the mountains around Changchun. Each sequence contains a set of point cloud data, odometry data, and imu data which can be used in LiDAR-based SLAM task. In the future, we will gradually release other data, such as images and annotations for tasks such as environmental perception, semantic segmentation. We will also release the data in different seasons. Coming soon.
Acknowledgement
When using this dataset in your research, we will be happy if you cite our website. We would appreciate if you can send an email to let us know when you use this dataset or when the dataset appears in a publicaton. Please also feel free to contact us If you encounter difficulties in using the dataset or have any suggestions regarding our dataset.
Copyright
All datasets on this page are copyright by us and published under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License. This means that you must attribute the work in the manner specified by the authors, you may not use this work for commercial purposes and if you alter, transform, or build upon this work, you may distribute the resulting work only under the same license.
This page provides additional information about the recording platform and sensor setup we have used to record this dataset.
Computer
We used industrial computer when collecting data, and its main configuration is as follows
# | Version |
OS | Ubuntu 20.04 LTS |
CPU | Intel i7-6770HQ |
Memory | 8G |
Disk | Samsung nvme 2T SSD |
Sensors
Our recording platform is equipped with the following sensors
SensorName | count | config |
Velodyne VLP-16 | 2 | Strongest Return Mode |
USB Camera | 2 | 1280x720, 30fps, JPEG |
NovAtel npos220s | 1 | 10Hz #INSPVAXA sentence, 125Hz #RAWIMUA sentence |
Sequence
|
Details
|
|||
---|---|---|---|---|
Lidar Frames
|
Trace Length
|
Package Size
|
Duration
|
|
JORD-01 | 3508 frames | 374.4 meters | 4 GB | 377.9 seconds |
JORD-02 | 8216 frames | 872.3 meters | 9 GB | 869.2 seconds |
JORD-03 | 5444 frames | 654.2 meters | 6 GB | 576.4 seconds |
JORD-04 | 5144 frames | 618.3 meters | 5 GB | 541.7 seconds |
JORD-05 | 5157 frames | 719.3 meters | 5 GB | 550.1 seconds |
第四届国际创新创业博览会
2019年12月20日在北京国家会议中心,团队携项目“人工智能无人地面车平台”,代表吉林省总工会赴京参展,该设备特色鲜明、独具魅力,得到参观领导与嘉宾的高度关注。