alvgaona/tii-ratm-rosbag2

TII-RATM ROS2 Bags with OpenVINS VIO

Pre-recorded ROS2 bags from the TII-RATM drone racing dataset with OpenVINS visual-inertial odometry, ground truth, and synthetic gate detections. Ready to use for SLAM evaluation without needing to run OpenVINS.

Contents

Each flight directory contains a single mcap bag with the following topics:

Topic	Type	Description
/ov_msckf/odomimu	nav_msgs/Odometry	OpenVINS VIO odometry (~500Hz)
/ov_msckf/pathimu	nav_msgs/Path	VIO trajectory path
/tf	tf2_msgs/TFMessage	odom → base_link transform from OpenVINS
/clock	rosgraph_msgs/Clock	Sim time clock (2023 epoch)
/ground_truth/pose	geometry_msgs/PoseStamped	Mocap ground truth pose (earth frame)
/ground_truth/odometry	nav_msgs/Odometry	Mocap ground truth odometry (earth frame)
/ground_truth/gates	visualization_msgs/MarkerArray	Gate positions from mocap
/detections/gates	as2_msgs/PoseStampedWithIDArray	Synthetic gate detections (body-relative from GT)
/detections/markers/gates	visualization_msgs/MarkerArray	Detection visualization markers
/tf_static	tf2_msgs/TFMessage	Gate positions as static TF (earth frame)
/imu	sensor_msgs/Imu	Raw IMU data (500Hz)
/camera/image_raw	sensor_msgs/Image	Camera images (640x480, ~26Hz, downsampled from ~106Hz)
/camera/camera_info	sensor_msgs/CameraInfo	Calibrated equidistant fisheye intrinsics

Flights

Directory	Track	Duration	Distance	Avg Speed	VIO msgs	GT msgs
flight-01p-ellipse	Ellipse	~120s	479m	4.0 m/s	~53k	~33k
flight-02p-ellipse	Ellipse	~95s	446m	4.2 m/s	~47k	~29k
flight-03p-ellipse	Ellipse	~104s	380m	3.7 m/s	~46k	~28k
flight-07p-lemniscate	Lemniscate	~127s	444m	3.5 m/s	~55k	~35k
flight-08p-lemniscate	Lemniscate	~100s	367m	3.8 m/s	~47k	~26k
flight-09p-lemniscate	Lemniscate	~105s	447m	4.4 m/s	~50k	~28k

Gate Positions (earth/world frame)

gate_1: [4.0, 1.3, 1.13]
gate_2: [4.0, -1.34, 1.16]
gate_3: [-4.0, -1.29, 1.16]
gate_4: [-3.97, 1.28, 1.17]

OpenVINS Configuration

• Camera: ArduCam IMX219 fisheye, 640x480 @ ~106Hz
• Camera model: Equidistant (Kannala-Brandt)
• Intrinsics: fx=291.5, fy=390.0, cx=316.4, cy=240.4
• Distortion: [0.048, -0.028, 0.038, -0.018]
• IMU: SBG Ellipse, 500Hz, FLU body frame
• Camera tilt: ~28deg below horizontal
• Time offset: -11.7ms
• Online calibration: Disabled (production values from averaging 5 ellipse flights)

Ellipse flights use tii_ellipse config, lemniscate flights use tii_lemniscate config.

Detections

Gate detections are synthetic — computed from ground truth (mocap) drone poses and known gate positions. They represent ideal body-relative observations with zero noise. Each detection provides the relative SE3 transform from the drone body frame to each gate within 15m range.

Usage

# Play a bag
ros2 bag play flight-01p-ellipse/

# Play with sim time
ros2 bag play flight-01p-ellipse/ --clock

# Check bag contents
ros2 bag info flight-01p-ellipse/

Timestamp Epochs

• Message header.stamp values are in 2023 epoch (original TII-RATM sensor timestamps)
• Bag receive timestamps are in 2026 epoch (when recorded)
• /clock topic contains 2023 sim-time timestamps
• Use use_sim_time:=true for ROS2 nodes consuming these bags

Related

• TII-RATM Dataset — original raw dataset
• OpenVINS — VIO system used
• SemanticSlam — SLAM system for evaluation

Citation

If you use this data, please cite the TII-RATM dataset paper:

@ARTICLE{bosello2026oyo,
  author={Bosello, Michael and Pinzarrone, Flavio and Kiade, Sara and Aguiari, Davide and Keuter, Yvo and AlShehhi, Aaesha and Caminati, Gyordan and Wong, Kei Long and Chou, Ka Seng and Halepota, Junaid and Alneyadi, Fares and Panerati, Jacopo and Pau, Giovanni},
  journal={IEEE Robotics and Automation Letters},
  title={On Your Own: Pro-Level Autonomous Drone Racing in Uninstrumented Arenas},
  year={2026},
  volume={11},
  number={3},
  pages={2674-2681},
  doi={10.1109/LRA.2026.3653405}
}