Real World Datasets for Autonomous Navigation
- Short Name: tc19_furo
- File: tc19_js_2019-09-14-14-12-15.bag (56 GB), tc19_js_2019-09-14-14-12-15.bag.7z (22 GB)
- Size: 55.8 GB
- Format: rosbag
- Date: 2019-09-14 14:12:15
- Duration: 1hr 47:31s
- Setup: Differential Wheeled Robot (Joystick Operation)
- Sensors:
- Lidar: SureStar R-Fans-16M
- Camera: No
- Radar: No
- GNSS: No
- IMU: Xsens MTi-3
- Motor Encoders (Wheel Odometry): Yes
- Description: Low cost 3D-Lidar. Low accuracy wheel odometry.
- License: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
If you use our dataset in your academic work, please cite the following paper [DOI]:
Yoshitaka Hara and Masahiro Tomono: "Moving Object Removal and Surface Mesh Mapping for Path Planning on 3D Terrain", Advanced Robotics, vol. 34, no. 6, pp. 375--387, 2020.
- Short Name: map_tc19_furo
- File: map_tc19_o085_f-04_t05.pcd
- Size: 683 MB
- Format: pcd
- Number of Points: 22,356,688
- Point Type:
- XYZ: Yes
- Intensity: Yes
- Color: No
- Normal: Yes
- SLAM Method: Occupancy Voxel Mapping using 3D Cartographer
- Description: Moving objects have been removed.
- License: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
If you use our dataset in your academic work, please cite the following paper [DOI]:
Yoshitaka Hara and Masahiro Tomono: "Moving Object Removal and Surface Mesh Mapping for Path Planning on 3D Terrain", Advanced Robotics, vol. 34, no. 6, pp. 375--387, 2020.
- Short Name: tc19_tsuchiuraPJ
- File: 2019-11-10-13-37-16.bag
- Size: 12.8 GB
- Format: rosbag
- Date: 2019-11-10 13:37:16
- Duration: 53:18s
- Setup: Mobile Robot (Autonomous Operation)
- Sensors:
- Lidar: Hokuyo YVT-X002, UTM-30LX-EW, URM-40LC-EW
- Camera: Ricoh Theta S, logicool C920
- Radar: No
- GNSS: u-blox NEO-M8T
- IMU: No
- Motor Encoders (Wheel Odometry): Yes
- Description: This bag file is compressed with 7z.
- License: TBD
- Short Name: tc18_furo
- File: tc18_js_2018-09-15-14-31-29.bag (41 GB), tc18_js_2018-09-15-14-31-29.bag.7z (12 GB)
- Size: 40.8 GB
- Format: rosbag
- Date: 2018-09-15 14:31:29 (Converted to rosbag on 2018-09-20)
- Duration: 1hr 31:43s
- Setup: Differential Wheeled Robot (Joystick Operation)
- Sensors:
- Lidar: Velodyne VLP-16
- Camera: No
- Radar: No
- GNSS: No
- IMU: Xsens MTi-3
- Motor Encoders (Wheel Odometry): Yes
- Description: High accuracy wheel odometry.
- License: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
If you use our dataset in your academic work, please cite the following paper [DOI]:
Yoshitaka Hara and Masahiro Tomono: "Moving Object Removal and Surface Mesh Mapping for Path Planning on 3D Terrain", Advanced Robotics, vol. 34, no. 6, pp. 375--387, 2020.
- Short Name: map_tc18_furo
- File: map_tc18_o085_f-04_t30.pcd
- Size: 519 MB
- Format: pcd
- Number of Points: 17,002,094
- Point Type:
- XYZ: Yes
- Intensity: Yes
- Color: No
- Normal: Yes
- SLAM Method: Occupancy Voxel Mapping using 3D Cartographer
- Description: Moving objects have been removed.
- License: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
If you use our dataset in your academic work, please cite the following paper [DOI]:
Yoshitaka Hara and Masahiro Tomono: "Moving Object Removal and Surface Mesh Mapping for Path Planning on 3D Terrain", Advanced Robotics, vol. 34, no. 6, pp. 375--387, 2020.
- Short Name: CIT_Tsudanuma
- File: CIT_2020_compressed.bag
- Size: 57 GB
- Format: rosbag
- Date: 2020-08-27 17:43:12
- Duration: 56:12s
- Setup: Mobile Robot (Joystick Operation)
- Sensors:
- Lidar: Velodyne VLP-16
- Camera: Intel Realsense d435i (without depth)
- Radar: No
- GNSS: Drogger DG-PRO1RW (Independent Positioning)
- IMU: Analog Devices ADIS16465
- Motor Encoders (Wheel Odometry): Yes
- Description: This bag file is compressed with a command
rosbag compress
. - License: TBD
- Short Name: map_tsudanuma
- File: map_tsudanuma.pcd
- Size: 490.8 MB
- Format: pcd
- Number of Points: 13,583,284
- Point Type:
- XYZ: Yes
- Intensity: Yes
- Color: No
- Normal: Yes
- SLAM Method: Occupancy Voxel Mapping using LIO-SAM.
- Description: Tsudanuma Campus of Chiba Institute of Technology.
- License: TBD