Add TII-RATM drone racing flights with paired odometry and capture ground truth ((root))
d005047 verified | license: cc-by-4.0 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/** | |
| annotations_creators: [] | |
| language: en | |
| size_categories: | |
| - n<1K | |
| task_categories: | |
| - robotics | |
| pretty_name: TII-RATM Drone Racing (FiftyOne multimodal MCAP) | |
| tags: | |
| - fiftyone | |
| - multimodal | |
| - mcap | |
| - drone | |
| - uav | |
| - slam | |
| - visual-inertial-odometry | |
| - ground-truth | |
| # TII-RATM Drone Racing → FiftyOne (Native Multimodal MCAP) | |
|  | |
| The | |
| [TII-RATM](https://github.com/tii-racing/tii-ratm-dataset) | |
| drone racing flights, as published with OpenVINS odometry in | |
| [alvgaona/tii-ratm-rosbag2](https://huggingface.co/datasets/alvgaona/tii-ratm-rosbag2), | |
| converted to native multimodal MCAP episodes. | |
| A quadrotor flies laps of a four-gate indoor track, three on an ellipse and | |
| three on a lemniscate. It carries a fisheye camera and a 500 Hz IMU, and a | |
| motion capture system watches the room throughout. | |
| What makes the set useful is that both numbers are present: the estimate the | |
| drone computed from its own camera and IMU, and the reference the capture | |
| system measured at the same instant. Every episode carries both, plus the | |
| distance between them. | |
| ## Installation | |
| ```bash | |
| pip install fiftyone | |
| ``` | |
| ## Usage | |
| ```python | |
| import fiftyone as fo | |
| import fiftyone.utils.huggingface as fouh | |
| dataset = fouh.load_from_hub( | |
| "Voxel51/TII-RATM-Drone-Racing", | |
| name="TII-RATM-Drone-Racing", | |
| persistent=True, | |
| ) | |
| fo.launch_app(dataset) | |
| ``` | |
| The flights the odometry found hardest: | |
| ```python | |
| view = dataset.sort_by("tracking_error_rmse_m", reverse=True) | |
| ``` | |
| ## What you get | |
| Six flights, 10.9 minutes and 2,563 metres flown. Each episode carries: | |
| - `/camera`, the onboard fisheye view at 640x480 and ~26 Hz, as | |
| `foxglove.CompressedVideo` | |
| - `/feature-tracks`, the same view with the points the odometry is tracking | |
| drawn on it | |
| - `/camera-calibration`, the equidistant fisheye intrinsics | |
| - `/imu.plot`, accelerometer and gyroscope at ~490 Hz | |
| - `/pose-ground-truth`, the motion capture pose | |
| - `/pose-vio`, the odometry pose, in the same frame | |
| - `/tracking-error.plot`, the distance between the two at each capture pose | |
| - `/trajectory`, both flown paths as line strips | |
| - `/points-slam` and `/points-msckf`, the feature points the estimator is | |
| holding | |
| - `/gates`, the four track gates as boxes | |
| - `/gate-range.plot`, the distance to each gate | |
| - `/tf`, the odometry and camera frames | |
| - `/instruction`, the track being flown | |
| Across the whole set that comes to 17,305 camera frames, 9,658 feature-track | |
| frames, **327,086 IMU samples**, 293,219 odometry poses and 179,283 capture | |
| poses. | |
| Episodes carry the fields `flight`, `track`, `distance_m`, `mean_speed_ms`, | |
| `max_speed_ms`, `tracking_error_rmse_m`, `tracking_error_median_m`, | |
| `tracking_error_max_m`, `tracking_error_final_m`, `num_camera_frames`, | |
| `num_feature_track_frames`, `num_imu_samples`, `num_vio_poses`, | |
| `num_ground_truth_poses`, `num_gates` and `duration`. | |
| | Flight | Track | Distance | ATE RMSE | ATE max | | |
| |---|---|---|---|---| | |
| | flight-03p-ellipse | ellipse | 380 m | 0.612 m | 2.349 m | | |
| | flight-02p-ellipse | ellipse | 446 m | 0.634 m | 3.455 m | | |
| | flight-09p-lemniscate | lemniscate | 447 m | 0.642 m | 1.699 m | | |
| | flight-08p-lemniscate | lemniscate | 367 m | 0.674 m | 2.194 m | | |
| | flight-01p-ellipse | ellipse | 479 m | 1.072 m | 3.482 m | | |
| | flight-07p-lemniscate | lemniscate | 444 m | 1.656 m | 3.784 m | | |
| ## Notes on the conversion | |
| The odometry and the capture system report in unrelated frames, since the | |
| estimator starts at its own origin with an arbitrary yaw. A rigid transform | |
| is fitted over every time-matched pose in the flight and applied to the | |
| odometry, which is the usual way an absolute trajectory error is measured. | |
| Scale is not fitted: the estimate is metric because it is inertial-aided, so | |
| solving for scale would hide drift rather than measure it. | |
| Because that fit spreads the residual across the whole flight, | |
| `/tracking-error.plot` does not start at zero and does not climb steadily. It | |
| is the distance from the reference at each instant, not the distance from a | |
| shared starting point. On `flight-08p-lemniscate` it runs 1.26 m at the start, | |
| dips to 0.15 m mid-flight and reaches 2.19 m by touchdown, where the estimate | |
| places the drone 1.4 m below the floor it has landed on. | |
| Video is re-encoded to Annex-B H.264 without B-frames. The source carries raw | |
| `bgr8` frames, which is most of its 44 GB. | |
| The camera uses an equidistant (Kannala-Brandt) fisheye model. The intrinsics | |
| are published as they were calibrated, and a viewer that assumes a pinhole or | |
| plumb-bob model will not undistort this correctly. | |
| Two source streams are not carried. `loop_depth` is typed as a 16-bit depth | |
| image but only a few dozen of its 307,200 pixels are ever set, so it is a | |
| sparse projection of loop-closure features rather than a depth map, and | |
| `points_aruco` is empty in every message of every flight. | |
| ## License & attribution | |
| The source release is distributed under | |
| [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/), and this conversion | |
| is distributed under the same license. | |
| Changes from the source: conversion to the FiftyOne MCAP flavor, re-encoding | |
| of the video to H.264, alignment of the odometry onto the capture frame, and | |
| encoding of the pose, IMU and detection streams as message streams. | |