S3E: A Large-scale Multimodal Dataset for Collaborative SLAM

Authors: Dapeng Feng, Yuhua Qi*, Shipeng Zhong, Zhiqiang Chen, Yudu Jiao, Qiming Chen, Tao Jiang, Hongbo Chen

Update !

2024/04/02 We are currently in the process of integrating UWB data into S3E, and anticipate the release of the new dataset in the near future.

2023/05/26 BaiduYun is available.

2022/11/08 ~~The data download link is available.~~

Sensors

Data format

We store the data captured by sensors in rosbag format. All the topics are listed in the above table. Note that xxx stands for the code of different robots, e.g., Alpha, Bob, Carol. And we provide the ground-truth as text files in UTM coordinates.

Calibration

We provide the well calibration between the left camera and other sensors in the yaml file (Alpha, Bob, Carol).

Baselines

License

This work is under the Apache 2.0 license.

Citation

@misc{https://doi.org/10.48550/arxiv.2210.13723,
  doi = {10.48550/ARXIV.2210.13723},
  url = {https://arxiv.org/abs/2210.13723},
  author = {Feng, Dapeng and Qi, Yuhua and Zhong, Shipeng and Chen, Zhiqiang and Jiao, Yudu and Chen, Qiming and Jiang, Tao and Chen, Hongbo},
  keywords = {Robotics (cs.RO), Computer Vision and Pattern Recognition (cs.CV), FOS: Computer and information sciences, FOS: Computer and information sciences},
  title = {S3E: A Large-scale Multimodal Dataset for Collaborative SLAM},
  publisher = {arXiv},
  year = {2022},
  copyright = {arXiv.org perpetual, non-exclusive license}
}