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CBNU Omni-directional Vision and LiDAR Dataset

We provide a 360-Vision dataset by an autonmous ground vehicle. The proposed framework is implemented and tested on Hyundai i30 (Hyundai Motor Company, Seoul, South Korea). Platform is equipped with Ladybug 3 omni-directional camera, mounted on the center top of the platform while LiDAR is placed at top of Ladybug 3 camera as shown.  The Novatel GPS is on the left side of the platform with dual antennas setup. The datasets contains the timely registered and synchronized measurement from Ladybug 3, 3D LiDAR, GPS and IMU.  More specifically, data can be used for multi-camera visual odometry and SLAM, panoramic SLAM, Multi-camera and LiDAR based odometry and panoramic image based loop closure detection.

Please site our dataset paper if you wish to use our dataset: PanoVILD: a challenging panoramic vision, inertial and LiDAR dataset for simultaneous localization and mapping

@article{javed2022panovild, title={PanoVILD: a challenging panoramic vision, inertial and LiDAR dataset for simultaneous localization and mapping}, author={Javed, Zeeshan and Kim, Gon-Woo}, journal={The Journal of Supercomputing}, volume={78}, number={6}, pages={8247--8267}, year={2022}, publisher={Springer} }

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DOWNLOADS

Sequence 1
Sequence 2

Sequence 3

Sequence 1

Sequence 4

Sequence 5

Sample Datasets/Codes/Calibration
Sequence 6
Sequence 7
Sequence 8
Sample Datasets/Codes/Calibration
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20200923_105655.jpg

SEQUENCES INFO

Sequence 1

​About Sequence 1

  • Robot Platform:  Car

  • Environment:  Outdoor Parking

  • Available Data: RTK GPS, Images, 3D LiDAR and IMU

  • Size:  7.3 GB

  • Number of Images: 583 (5 Cam)

  • Panorama:  583

  • Number of Point cloud: 972

  • GT: RTK GPS

Sequence 2

​About Sequence 2

  • Robot Platform:  Car

  • Environment: Outdoor  

  • Available Data: GPS, Images, 3D LiDAR and IMU

  • Size:  ~32 GB

  • Number of Images: 2023 (5 Cam)

  • Panorama:  2023

  • Number of Point cloud: 3375

  • GT: RTK GPS

Sequence 4

​About Sequence 3 

  • Robot Platform:  Car

  • Environment: Outdoor  

  • Available Data: GPS, Images, 3D LiDAR and IMU

  • Size:  ~10 GB

  • Number of Images: 912

  • Panorama: 912

  • Number of Point cloud: 1524

  • GT: RTK GPS

​About Sequence 4 

  • Robot Platform:  Car

  • Environment: Outdoor  

  • Available Data: GPS, Images, 3D LiDAR and IMU

  • Size:  

  • Number of Images: 900 (5 cam)

  • Panorama: 900

  • Number of Point cloud: 1500

  • GT: RTK GPS

Sequence 3

Sequence 6

​About Sequence 5 

  • Robot Platform:  Car

  • Environment: Outdoor  

  • Available Data: GPS, Images, 3D LiDAR and IMU

  • Size:  

  • Number of Images: 2897 (5 cam)

  • panorama:  2897

  • Number of Point cloud: 4827

  • GT: RTK GPS

​About Sequence 6

  • Robot Platform:  Car

  • Environment: Outdoor  

  • Available Data: GPS, Images, 3D LiDAR and IMU

  • Size:  

  • Number of Images: 2140 (5 cam)

  • Panorama: 2140

  • Number of Point cloud: 4102

  • GT: RTK GPS

Sequence 5

Sequence 7

Sequence 8

​About Sequence 7 

  • Robot Platform:  Car

  • Environment: Outdoor ground 

  • Available Data: GPS, Images, 3D LiDAR and IMU

  • Size:  

  • Number of Images: 3303 (5 cam)

  • panorama: 3303

  • Number of Point cloud: 6425

  • GT: RTK GPS

​About Sequence 8

  • Robot Platform:  Car

  • Environment: Outdoor  

  • Available Data: GPS, Images, 3D LiDAR and IMU

  • Size:  

  • Number of Images: 2685 (5 cam)

  • Panorama: 2685

  • Number of Point cloud: 5208

  • GT: RTK GPS

HD Mapping based on LiDAR and Inertial Odometry

Camera-LiDAR Calibration

Cam0 and LiDAR

Full stacked view

SLAM Experiments

Pano-SLAM Sequence 1

Pano-SLAM Sequence 5

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