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Kimera-Multi-Data: A large-Scale Multi-Robot Dataset for Multi-Robot SLAM

Description:

Sequence # Robots Traversal (m) Duration (min)
Campus-Outdoor 6 6044 19
Campus-Tunnels 8 6753 28
Campus-Hybrid 8 7785 27

Platforms

We use a single set of camera intrinsic and extrinsic parameters for all the robots. The parameters follow the Kimera-VIO format and can be downloaded below.

Data format

The datasets are in compressed rosbag format. For best results, decompress the rosbags before usage.

rosbag decompress *.bag
Topic Type Description
/xxx/forward/color/image_raw/compressed sensor_msgs/CompressedImage RGB Image from D455
/xxx/forward/color/camera_info sensor_msgs/CameraInfo RGB Image Camera Info
/xxx/forward/depth/image_rect_raw sensor_msgs/Image Depth Image from D455
/xxx/forward/depth/camera_info sensor_msgs/CameraInfo Depth Image Camera Info
/xxx/forward/infra1/image_rect_raw/compressed sensor_msgs/CompressedImage Compressed Gray Scale Stereo Left
/xxx/forward/infra1/camera_info sensor_msgs/CameraInfo Stereo Left Camera Info
/xxx/forward/infra2/image_rect_raw/compressed sensor_msgs/CompressedImage Compressed Gray Scale Stereo Right
/xxx/forward/infra2/camera_info sensor_msgs/CameraInfo Stereo Right Camera Info
/xxx/forward/imu sensor_msgs/Imu IMU from D455
/xxx/jackal_velocity_controller/odom nav_msgs/Odometry Wheel Odometry
/xxx/lidar_points sensor_msgs/PointCloud2 Lidar Point Cloud

Ground Truth

The ground truth trajectory is generated using GPS and total-station assisted LiDAR SLAM based on LOCUS and LAMP. The process is described in further detail in our paper. You can download the ground truth trajectory and reference point cloud below.

Citation

If you found the dataset to be useful, we would appreciate it if you can cite the following paper:

  • Y. Tian, Y. Chang, L. Quang, A. Schang, C. Nieto-Granda, J. P. How, and L. Carlone, "Resilient and Distributed Multi-Robot Visual SLAM: Datasets, Experiments, and Lessons Learned," arXiv preprint arXiv:2304.04362, 2023.
@ARTICLE{tian23arxiv_kimeramultiexperiments,
  author={Yulun Tian and Yun Chang and Long Quang and Arthur Schang and Carlos Nieto-Granda and Jonathan P. How and Luca Carlone},
  title={Resilient and Distributed Multi-Robot Visual SLAM: Datasets, Experiments, and Lessons Learned}, 
  year={2023},
  eprint={2304.04362},
  archivePrefix={arXiv},
  primaryClass={cs.RO}
}

Download

Name Rosbags GT Photos Trajectory
Campus-Outdoor request link drawing drawing
Campus-Tunnels request link drawing drawing
Campus-Hybrid request link drawing drawing

The camera calibration parameters used for our experiments can be found here.

The point cloud of the reference ground truth map can be downloaded here.

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A large-scale multi-robot dataset for multi-robot SLAM

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