c-qiyao/sjtu_gvi

A GNSS-Visual-IMU Dataset for SLAM

SJTU_GVI

A GNSS-Visual-IMU Dataset for SLAM

Authors: Jie Yin

Different from M2DGR, this dataset has following features:

1.More light-weight and easy for downloading.

2.Recoreded on a real car with high speed.

3.GNSS raw measurements are captured by a Ublox ZED-F9P receiver, which facilitate the GNSS-SLAM research.

Please give us a star if this project is helpful to your research. Thank you! If you use M2DGR in an academic work, please cite:

@ARTICLE{9664374,
  author={Yin, Jie and Li, Ang and Li, Tao and Yu, Wenxian and Zou, Danping},
  journal={IEEE Robotics and Automation Letters}, 
  title={M2DGR: A Multi-sensor and Multi-scenario SLAM Dataset for Ground Robots}, 
  year={2021},
  volume={},
  number={},
  pages={1-1},
  doi={10.1109/LRA.2021.3138527}}

Figure 1. A picture of our acquisition platform.

Figure 2. We were calibrating the extrinsics.

1.Sequence

The extraction code is "yj66"

Sequence	Collection Date	Total Size	Duration	Rosbag
Seq1	2021-12-23	2.37G	349s	Rosbag
Seq2	2021-12-23	921M	109s	Rosbag
Seq3	2021-12-23	1.19G	146s	Rosbag
Seq4	2021-12-23	850M	112s	Rosbag
Seq5	2021-12-23	1.26G	159s	Rosbag

2.Calibration

The camera intrinsic and cam-imu extrinsics calibration results is given in Link

3.Ground Truth

The ground truth of the datasets is given in Link

4.ACKNOWLEGEMENT

Authors express our appreciation for the support of Shanghai West Hongqiao Navigation Technology Co., LTD.