This is the dataset website for our paper PSEF: Point Cloud and Semantic ESKF Fusion System For Precise and Robust Localization in Underground Parking Environments
Location and mapping data set of underground parking lot.
Two bag files, corresponding to the senmatic map and the point cloud map data under normal conditions and full parking spaces.
Parameter setting
| Sensor Type | Parameter | Value |
|---|---|---|
| LiDAR | Number of Channels | 16 |
| Measurement Range | <100m | |
| Horizontal Field of View | 360° | |
| Vertical Field of View | 30° | |
| Scanning Frequency | 10Hz | |
| Camera | Resolution | 640 × 480 |
| Frame Rate | 30Hz | |
| IMU | Update Frequency | 200Hz |
#Installation angles of six cameras
rotateDeg0: 0
rotateDeg1: -1.0471975511965976
rotateDeg2: -2.0943951023931953
rotateDeg3: -3.141592653589793
rotateDeg4: 2.0943951023931953
rotateDeg5: 1.0471975511965976
K: [337.2084410968044, 0.0, 320.5,
0.0, 337.2084410968044, 240.5,
0.0, 0.0, 1.0]
#Relative to the ground coordinate system
R0: [0, 1.0, 0,
0.0, 0, 1,
1.0, 0.0, 0.0]
T0: [0,
1.23,
0.0]
#LiDAR VLP-16 16channels 10Hz
#IMU 200Hz noise [0.01,0.01]
#camera 30Hz size 640X480
#Camera external parameter lidar_to_imu:0,0,1,0.3,-1,0,0,1.5,-0,-1,-0,0,0,0,0,1;
camera-to-imu:
[0, 1.0, 0, 0,
0.0, 0, 1, 1.0,
1.0, 0.0, 0.0,0.0]
Download link
The file is transferred to the cloud disk here, and the download address of URL is provided.
link: https://pan.baidu.com/s/1GOsbk-sSezOEB634Uhx9rA
Extraction code: fjos
You can use tools provided by ROS, such as rosbag, to create, read and process bag files.