├── LICENSE ├── README.md ├── images ├── 10_Spot2_LA_Subway_2.png ├── 12_Spot1_Loop_Kentucky_2.png ├── 13_Husky1_Kentucky_2.png ├── 3_Husky4_Urban_Alpha1_2.png ├── 4_Husky4_Tunnel_SR2_2.png ├── 5_Spot1_Valentine1_2.png ├── 6_Husky4_Tunnel_EX2_2.png ├── 8_Husky1_Urban_Beta2_2.png ├── Bruceton.png ├── Combined.png ├── Final.png ├── Husky4_Beta2_2.png ├── KentuckyUnderground.png ├── LASubway.png ├── Satsop.png ├── Spot1_Urban_Beta2_2_old.png ├── Valentine.png ├── all_robots.JPG ├── all_robots2.png ├── darpa1.png ├── darpa2.png ├── darpa2_old.png ├── darpa3.png ├── darpa4.png ├── darpa_prelim2_1.png ├── darpa_prelim2_2.png ├── husky_equpiment.jpg ├── husky_frames.png ├── kentucky.jpg ├── kentucky_cave2.jpg ├── kentucky_cave3.png ├── kentucky_cave4.png ├── la_old_subway.png ├── la_old_subway_old.jpeg ├── powerplant.jpg ├── spot.jpg ├── spot_equipment.png ├── spot_frames.png ├── tunnel_circuit.jpg ├── valentine_cave.jpg └── valentine_cave2.png └── pages ├── dataset.md ├── overview.md ├── run.md ├── topic_hovermap.md └── topic_lidar.md /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2022 NeBula Autonomy 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 |

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4 | 5 | # NeBula odometry dataset 6 | 7 | - [Overview](pages/overview.md) 8 | - [Download datasets](pages/dataset.md) 9 | - Topics and frame convention 10 | - [LiDAR dataset](pages/topic_lidar.md) 11 | - [Hovermap dataset](pages/topic_hovermap.md) 12 | 13 | 14 | 15 | drawing 16 | 17 | # Cite 18 | 19 | If you use this dataset in your research, we would kindly ask that you cite the following publication: 20 | 21 | ``` 22 | @article{reinke2022locus, 23 | title={LOCUS 2.0: Robust and Computationally Efficient Lidar Odometry for Real-Time 3D Mapping}, 24 | author={Reinke, Andrzej and Palieri, Matteo and Morrell, Benjamin and Chang, Yun and Ebadi, Kamak and Carlone, Luca and Agha-Mohammadi, Ali-Akbar}, 25 | journal={IEEE Robotics and Automation Letters}, 26 | volume={7}, 27 | number={4}, 28 | pages={9043--9050}, 29 | year={2022}, 30 | publisher={IEEE} 31 | } 32 | ``` 33 | 34 | IEEE Publication Link [here](https://ieeexplore.ieee.org/document/9793601) 35 | 36 | Paper available on arXiv [here](https://arxiv.org/abs/2205.11784) 37 | 38 | 39 | # Problems or clarification needed? 40 | Submit ticket [here](https://github.com/NeBula-Autonomy/nebula-odometry-dataset/issues) 41 | 42 | -------------------------------------------------------------------------------- /images/10_Spot2_LA_Subway_2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/NeBula-Autonomy/nebula-odometry-dataset/966c96dc187679b12c0efc6c39aac207cb3066f4/images/10_Spot2_LA_Subway_2.png -------------------------------------------------------------------------------- /images/12_Spot1_Loop_Kentucky_2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/NeBula-Autonomy/nebula-odometry-dataset/966c96dc187679b12c0efc6c39aac207cb3066f4/images/12_Spot1_Loop_Kentucky_2.png -------------------------------------------------------------------------------- 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4 | 5 | # Datasets 6 | 7 | Here, you can download the datasets. 8 | - ```Rosbags``` - bag files to run 9 | - ```${robot_name}_lidar_*.bag``` - LiDAR scans (velodyne packets as well) 10 | - ```imu.bag``` - imu data from VN100 (covariance also included) 11 | - ```odometry.bag``` - different types of odometry data (wheeled, kinematic, visual) 12 | - ```Extra files```: 13 | - ```odometry.bag``` - rosbag file that has a ground truth trajectory 14 | - ```*.ply```, ```*.pcd``` - 3D map provides information of the scanned 3D map 15 | - ```fiducial_calibration_${robot_name}$.yaml``` - provides information of inital position in the map (and from where the ground truth starts) 16 | - ```${robot_name}_sensors.yaml``` - stores information about relative transformation between frames and sensors 17 | - ```2D image``` - provides information of the enviornment from bird's-eye-view 18 | 19 | # LiDARs dataset 20 | | ID | Place | Domain | Robot | Distance (m) | Duration (min) | rosbags | Size (GB) | Extra files | 2D image | 21 | |:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:| 22 | | A | Satsop Power Plant Elma, WA |Urban | Husky4 | 631.53 |59:56 |[click (updated)](https://drive.google.com/drive/folders/1I0YYGzKWB7Hb_Y5PWy9QGRET4TD-NKA_?usp=sharing) | 61.4 |[click (updated)](https://drive.google.com/drive/folders/1BHIwfdGbqFcSipjfTE4ZS9G-iOh0h4Fu?usp=sharing) | drawing 23 | | B | Satsop Power Plant Elma, WA |Urban | Spot1 | 664.27 |32:26 |[click (updated)](https://drive.google.com/drive/folders/1HFy_LfDCM-Aq8-a08erZ00ztCKisH5IK?usp=sharing) | 20.1 |[click (updated)](https://drive.google.com/drive/folders/1NUac0zEKcriPA3dgFTzQgF_VDJZhcjoo?usp=sharing) | drawing 24 | | C | Satsop Power Plant Elma, WA |Urban | Husky4 | 757.40 |24:21 |[click (updated)](https://drive.google.com/drive/folders/1eDZPNEZ0lVx__FoU9RRPcCjSPd-Jlvc1?usp=sharing) | 45.8 |[click (updated)](https://drive.google.com/drive/folders/1g3eac7QCyfdpf5hUObOa41dJLKWyoSmt?usp=sharing) | drawing 25 | | D | Bruceton Mine Pittsburgh, PA |Tunnel| Husky4 | 1795.88 |65:36 |[click (updated)](https://drive.google.com/drive/folders/1K8q-MpT2yns-gQ_AHLwsgf4qi84yFTHg?usp=sharing) | 31.5 |[click (updated)](https://drive.google.com/drive/folders/1EJCeJ6pmOKWHX94fmCBJiGpJIZ_qUPhg?usp=sharing) | drawing 26 | | E | Lava Beds National Monument, CA |Cave | Spot1 | 590.85 |25:20 |[click (updated)](https://drive.google.com/drive/folders/1aGARWd08QeOuPqaG8-llNn0uUpFKYCGl?usp=sharing) | 19.1 |[click (updated)](https://drive.google.com/drive/folders/1-n5By8zMEuV8tjdwPdjIZBtO3L2eVttJ?usp=sharing) | drawing 27 | | F | Bruceton Mine Pittsburgh, PA |Tunnel| Husky4 | 1569.73 |49:13 |[click (updated)](https://drive.google.com/drive/folders/1I2_LWf5bEFNu6W1Qj_HDCfyo0wL1fG0j?usp=sharing) | 36.8 |[click (updated)](https://drive.google.com/drive/folders/1RH4MvKKJeJNq2-D7x-QtbWMeWl3itl5o?usp=sharing) | drawing 28 | | G | Satsop Power Plant Elma, WA |Urban | Husky1 | 877.21 |93:10 |[click (updated)](https://drive.google.com/drive/folders/1m2qwRiZrMvUHxJDlQLFfda8WF_CRc5SZ?usp=sharing) | 61.4 |[click (updated)](https://drive.google.com/drive/folders/1eQS07CocMWgFBFXiE5p-GsaLrS7Lkhbg?usp=sharing) | drawing 29 | | H | Subway Station Los Angeles, CA |Urban | Spot2 | 1777.45 |46:57 |[click (updated)](https://drive.google.com/drive/folders/1d65GMBoaes43Y9GvzjNphCQsdtFkV5kz?usp=sharing) | 16.7 |[click (updated)](https://drive.google.com/drive/folders/15PCmHo8piWrL9-I_-DN0opvDc8C7yf8_?usp=sharing) | drawing 30 | | I | Kentucky Underground Limestone Mine, KY |Tunnel| Spot1 | 768.82 |19:28 |[click (updated)](https://drive.google.com/drive/folders/1uqn7Y_Gb17DeTGKDdGyyPzQ8NDQd-F74?usp=sharing) | 9.4 |[click (updated)](https://drive.google.com/drive/folders/1jRQh2nYmTNfpFg11LbMUYmLbWb-TDKzB?usp=sharing) | drawing 31 | | J | Kentucky Underground Limestone Mine, KY |Tunnel| Husky1 | 2339.81 |57:55 |[click (updated)](https://drive.google.com/drive/folders/1z9UNc06GuE_uOoCEU7ni1BWYcS6plPER?usp=sharing) | 79.0 |[click (updated)](https://drive.google.com/drive/folders/1CKx3RrP5DnkKnORpBGOZoXNNg_RFT6ZM?usp=sharing) | drawing 32 | | K | DARPA Final Louisville Cave, KY |Mix | Spot1 | 798.24 |30:56 |[click (updated)](https://drive.google.com/drive/folders/1Z_ABh8fiBSh872sfe8UGV3z2mgVoUmby?usp=sharing) | 15.5 |[click (updated)](https://drive.google.com/drive/folders/19kZWXaJ4Z91O0VsJ68wm4d2CMX_vgX-p?usp=sharing) | drawing 33 | | N | DARPA Final Louisville Cave, KY |Mix | Husky2 | 325.30 |24:08 |[click (updated)](https://drive.google.com/drive/folders/1XltO_PuvZuJ1XJoP1xjx6G6GQebOQsOr?usp=sharing)| 31.0 |[click (updated)](https://drive.google.com/drive/folders/1J2WNgKlKOwuSEX8aCojiS3339IBR3ClN?usp=sharing) | drawing 34 | | O | DARPA Final Louisville Cave, KY |Mix | Husky1 | 488.48 |23:48 |[click (updated)](https://drive.google.com/drive/folders/1wq1ZMpPG4FFoxSghgU9KY01NdSX3aQd2?usp=sharing) | 47.4 |[click (updated)](https://drive.google.com/drive/folders/1QRtmjMUf3uLCbB5B2nMTnuW8SyjSOOcW?usp=sharing) | drawing 35 | | P | DARPA Final Louisville Cave, KY |Mix | Spot1 | 571.79 |34:13 |[click (updated)](https://drive.google.com/drive/folders/1y8hWKj_GoXS1rhKq0El9GlNAppTEATt3?usp=sharing) | 12.3 |[click (updated)](https://drive.google.com/drive/folders/1CDif8WGy6PD8WIKTZbkg5M0dckRY_2N8?usp=sharing) | drawing 36 | 37 | 38 | # Ground truth 39 | 40 | To determine the ground truth of the robot in the environment, a survey-grade $3D$ map (provided by DARPA in the Subterranean Challenge or produced by the team) is used (see Extra files). 41 | The ground-truth trajectory is produced by running [LOCUS](https://github.com/NeBula-Autonomy/LOCUS) against the survey-grade map (i.e., scan-to-map is scan-to-survey-map). In this mode, LOCUS is tuned for maximum accuracy at the cost of computational efficiency, as it does not need to be run in real-time. 42 | The ground truth is stored in ```odometry.bag``` file. **It's important to remember that the trajectory does not start from (0,0,0)**. The initial position of the robot can be read from the file described [here](#initial-pose) 43 | 44 | # Recorded topics 45 | 46 | - LiDAR dataset (see [here](/pages/topic_lidar.md)) 47 | - Hovermap dataset (see [here](/pages/topic_hovermap.md)) 48 | 49 | # Extrinsic Calibration 50 | ```${robot}_sensors.yaml``` - provides information about relative transformation between sensors (LiDAR-LiDAR, IMU-LiDAR, etc.). The ```parent``` arch refers to the custom-designed device to carry LiDARs sensors. 51 | 52 | # Initial Pose 53 | 54 | ```fiducial_calibration_${robot_name}.yaml``` contains the initial position and orientation (pose) of the robot in the global reference frame according to the 3D map. 55 | 56 | # Hovermap dataset 57 | 58 | These datasets have a rotating lidar from hovermap. These are not the focus on this dataset release, but are made available for interested researchers. 59 | 60 | | ID | Place | Domain | Robot | Distance (m) | Duration (min) | rosbags | Extra files | 2D image | 61 | |:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:| 62 | | L | DARPA Final Louisville Cave, KY |Mix | Spot3 | 245.13 |11:41 |[click (updated)](https://drive.google.com/drive/folders/1Zgwd-cXTEAAGDwK7mhhZ3LU4dJ_8b46b?usp=sharing) |[click (updated)](https://drive.google.com/drive/folders/1hO6mnAebFKhwMQ34v5yAbt2iUIIQfJp3?usp=sharing) | drawing 63 | | M | DARPA Final Louisville Cave, KY |Mix | Spot4 | 722.37 |19:57 |[click (updated)](https://drive.google.com/drive/folders/1YJBz58W_AlPnRCkBmpt6_E_TLv_TE8qx?usp=sharing) |[click (updated)](https://drive.google.com/drive/folders/1pkRB6k2DC08OwBH2fZ1Gd31E4iixhChW?usp=sharing) | drawing 64 | | N | DARPA Final Louisville Cave, KY |Mix | Husky2 | 325.30 |24:08 |[click (updated)](https://drive.google.com/drive/folders/1XltO_PuvZuJ1XJoP1xjx6G6GQebOQsOr?usp=sharing) |[click (updated)](https://drive.google.com/drive/folders/1ns3O4DagfqB2-Hmc27EZPy38RgJhm-JP?usp=sharing) | drawing 65 | | O | DARPA Final Louisville Cave, KY |Mix | Husky1 | 488.48 |23:48 |[click (updated)](https://drive.google.com/drive/folders/1wq1ZMpPG4FFoxSghgU9KY01NdSX3aQd2?usp=sharing) |[click (updated)](https://drive.google.com/drive/folders/1OhxBRJir-Fx7BPndHWrO9ycEMD_p6S2A?usp=sharing) | drawing 66 | | Q | DARPA Final Louisville Cave, KY |Mix | Spot3 | 744.60 |26:55 |[click (updated)](https://drive.google.com/drive/folders/1HiWlP0v_HtxJNUCs7KxaH6kdVFJw-TFc?usp=sharing) |[click (updated)](https://drive.google.com/drive/folders/1m1HePXOzFUHWUV36hoB-QliR_k-hnYL0?usp=sharing) | drawing 67 | | R | DARPA Final Louisville Cave, KY |Mix | Spot4 | 328.42 |13:02 |[click (updated)](https://drive.google.com/drive/folders/131HZsAJqkl3Y8byyomc3znbeK34nHa66?usp=sharing) |[click (updated)](https://drive.google.com/drive/folders/1cqe7yvrMU8bo3aKEMbp_JyNC0ESqCcbu?usp=sharing) | drawing 68 | 69 | 70 | -------------------------------------------------------------------------------- /pages/overview.md: -------------------------------------------------------------------------------- 1 |

2 | drawing 3 |

4 | 5 | # Overview. 6 | 7 | The dataset is provided by the [Team CoSTAR](https://costar.jpl.nasa.gov/) that has been intensively testing the multi-robot system in real world environments such as caves, tunnels, abandoned factories and industrial plants for [DARPA Subterranean Challenge](https://www.google.com/search?q=darpa+subt+challenge&oq=darpa+subt&aqs=chrome.1.69i57j35i39j0i512l2j69i60l2j69i65j69i60.2114j0j7&sourceid=chrome&ie=UTF-8) 8 | 9 | 10 | # Dataset real-world places. 11 | 12 | ## [Power plant located in Elma, WA](https://www.google.com/maps/place/Satsop+Nuclear+Power+Plant/@46.9616165,-123.472372,16z/data=!4m5!3m4!1s0x0:0x8a108aba7feb7724!8m2!3d46.9616231!4d-123.4675564) 13 | 14 | drawing 15 | 16 | ## [Los Angeles Subway Station](https://www.google.com/maps/place/425+S+Hill+St,+Los+Angeles,+CA+90013/@34.0489961,-118.251699,18z/data=!4m8!1m2!2m1!1sSouth+Hill+Street+near+Pershing+Square!3m4!1s0x80c2c64b6a30ca9f:0x1cd85506387e59f5!8m2!3d34.0497312!4d-118.2510744) 17 | 18 | drawing 19 | 20 | ## [Bruceton Research Mine in Pittsburgh, PA](https://www.google.com/maps/place/Bruceton+Research+Mine/@40.3040108,-79.978597,15z/data=!4m2!3m1!1s0x0:0xa44441e8bb7eb69f?sa=X&ved=2ahUKEwi4vrCP4Yn3AhVumIsKHT19BY4Q_BJ6BAhGEAM) 21 | 22 | drawing 23 | 24 | ## [Valentine Cave](https://www.google.com/maps?q=valentine+cave&um=1&ie=UTF-8&sa=X&ved=2ahUKEwjA5ouf4Yn3AhWLuYsKHYgoCzYQ_AUoAnoECAEQBA) 25 | 26 | drawing 27 | 28 | ## [Kentucky Underground Mine](https://www.google.com/maps?q=Kentucky+Underground&um=1&ie=UTF-8&sa=X&ved=2ahUKEwjMkY_p0ZL3AhWbKkQIHUTRDfkQ_AUoAXoECAEQAw) 29 | 30 | drawing 31 | 32 | ## [Louisville Mine, artificially made circuit](https://www.google.com/maps?q=Louisville+Mine&um=1&ie=UTF-8&sa=X&ved=2ahUKEwjFiLa47In3AhXpk4sKHb7pAZIQ_AUoAnoECAEQBA) 33 | 34 | drawing 35 | 36 | Each dataset is selected to contain components that are challenging for LiDAR odometry. The datasets have different duration lengths from 20 min up to 1 h (see [here](dataset.md)). The dataset provides LiDAR scans, [Hovermap scans](https://www.emesent.io/hovermap/), Inertial Measurement Unit (IMU) and wheeled and kinematic inertial odometry (WIO) measurements. All datasets have been recorded on different robotics platforms, e.g., Husky and Spot with vibrations and large, sudden accelerations as is characteristic of both a skid-steer wheeled robot traversing rough terrain (husky) and a legged robot that slips and acts dynamically in rough terrain (spot). 37 | The dataset is synchronized by window time stamp approach where the current time stamp looks for the closest time stamps available with maximum threshold time distance. 38 | LiDAR scans are recorded at 10 Hz. WIO and IMU are recorded at 50 Hz in the Urban datasets, while a higher-rate IMU recording (100 Hz) is available for the Tunnel and Cave dataset. 39 | 40 | # Robot Equipment 41 | 42 | ## Husky 43 | 44 | drawing 45 | 46 | ### Equipment 47 | - 3 on-board [Velodyne’s Puck lidar sensor (VLP-16)](https://velodynelidar.com/products/puck/) LiDAR sensors (one flat, one pitched forward ~30 °, one pitched backward ~30 °) 48 | - ```velodyne``` 49 | - ```velodyne_front``` 50 | - ```velodyne_rear``` 51 | - [IMU VN100](https://www.vectornav.com/products/detail/vn-100?gclid=Cj0KCQjwxtSSBhDYARIsAEn0thQy4ZSoNNRcvUZzJBFEtlZtiIb9PiUJty0BAxZwOUEK2bK6l9XtnLIaAtTnEALw_wcB) 52 | - wheel encoders from Clearpath (see [here](https://clearpathrobotics.com/husky-unmanned-ground-vehicle-robot/)) 53 | - [Hovermap](https://www.emesent.io/hovermap/) (see associated datasets [here](dataset.md)) 54 | 55 | ## Spot 56 | drawing 57 | 58 | ### Equipment 59 | - 1 on-board [Velodyne’s Puck lidar sensor (VLP-16)](https://velodynelidar.com/products/puck/) LiDAR sensors 60 | - Out-of-the-box kinematic-ineratial odometry (KIO) and visual-inertial odometry (VIO) measurements implemented by [Boston Dynamics](https://www.bostondynamics.com/products/spot) 61 | - [IMU VN100](https://www.vectornav.com/products/detail/vn-100?gclid=Cj0KCQjwxtSSBhDYARIsAEn0thQy4ZSoNNRcvUZzJBFEtlZtiIb9PiUJty0BAxZwOUEK2bK6l9XtnLIaAtTnEALw_wcB) 62 | - [Hovermap](https://www.emesent.io/hovermap/) (see associated datasets [here](dataset.md)) 63 | -------------------------------------------------------------------------------- /pages/run.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/NeBula-Autonomy/nebula-odometry-dataset/966c96dc187679b12c0efc6c39aac207cb3066f4/pages/run.md -------------------------------------------------------------------------------- /pages/topic_hovermap.md: -------------------------------------------------------------------------------- 1 | # Hovermap dataset 2 | 3 | ## Husky 4 | --- 5 | drawing 6 | 7 | - **LiDAR/Hovermap data** (```${robot_name}_lidar_*.bag```) 8 | - Hovermap topics ```sensor_msgs/PointCloud2``` 9 | - ```${robot_name}/hvm/lidar/points``` 10 | - frame_id: ```${robot_name}/hovermap``` 11 | - LiDAR topics (```sensor_msgs/PointCloud2```) 12 | - ```${robot_name}/velodyne/velodyne_points``` 13 | - frame_id: ```${robot_name}/velodyne``` 14 | - ```${robot_name}/velodyne_front/velodyne_points``` 15 | - frame_id: ```${robot_name}/velodyne_front``` 16 | - ```${robot_name}/velodyne_rear/velodyne_points``` 17 | - frame_id: ```${robot_name}/velodyne_rear``` 18 | - LiDAR packet topics (```velodyne_msgs/VelodyneScan```) 19 | - ```${robot_name}/velodyne_packets``` 20 | - frame_id: ```${robot_name}/velodyne``` 21 | - ```${robot_name}/velodyne_front/velodyne_packets``` 22 | - frame_id: ```${robot_name}/velodyne_front``` 23 | - ```${robot_name}/velodyne_rear/velodyne_packets``` 24 | - frame_id: ```${robot_name}/velodyne_rear``` 25 | - topics that you should not care about: 26 | - ```${robot_name}/velodyne_points_min_dist``` 27 | 28 | - **IMU data** (```imu.bag```) 29 | - ```${robot_name}/vn100/imu``` 30 | - frame_id: ```${robot_name}/vn100``` 31 | - ```${robot_name}/vn100/imu_wori_wcov``` 32 | - frame_id: ```${robot_name}/vn100``` 33 | 34 | - **Odometry data** (```odometry.bag```) 35 | - ```${robot_name}hero/wio_ekf/odom``` (wheeled-inertial odometry done by ) 36 | - frame_id: ```${robot_name}/odom``` 37 | - ```${robot_name}wheel_odom``` 38 | - frame_id: ```${robot_name}/odom``` 39 | - ```${robot_name}/hvm/odometry``` (output of Emesent Hovermap odometry) 40 | - frame_id: ```${robot_name}/odom``` 41 | - ```${robot_name}/hvm/odometry_transformed``` (output of Emesent Hovermap odometry transformed to ) 42 | - frame_id: ```${robot_name}/odom``` 43 | 44 | ## Spot 45 | --- 46 | drawing 47 | 48 | - **LiDAR/Hovermap data** (```${robot_name}_lidar_*.bag```) 49 | - LiDAR topics ```sensor_msgs/PointCloud2``` 50 | - ```${robot_name}/velodyne/velodyne_points``` 51 | - frame_id: ```${robot_name}/velodyne``` 52 | - LiDAR packet topics (```velodyne_msgs/VelodyneScan```) 53 | - ```${robot_name}/velodyne_packets``` 54 | - Spot Realsense Point Cloud (```sensor_msgs/PointCloud2```) 55 | - ```/${robot_name}/spot_driver/local_grid``` 56 | - topics that you should not care about: 57 | - ```${robot_name}/velodyne_points_min_dist``` 58 | 59 | - **IMU data** (```imu.bag```) **(Note: keep in mind that in B, E IMU is not available)** 60 | - ```${robot_name}/vn100/imu``` 61 | - frame_id: ```${robot_name}/vn100``` 62 | - ```${robot_name}/vn100/imu_wori_wcov``` 63 | - frame_id: ```${robot_name}/vn100``` 64 | 65 | - **Odometry data** (```odometry.bag```) 66 | - ```${robot_name}/kinematic_odom``` (sometimes called legged odometry) 67 | - frame_id: ```${robot_name}/odom``` 68 | - ```${robot_name}/visual_odom``` (output of Boston Dynamics visual odometry algorithm) 69 | - frame_id: ```${robot_name}/odom``` 70 | - ```${robot_name}/hvm/odometry``` (output of Emesent Hovermap odometry) 71 | - frame_id: ```${robot_name}/odom``` 72 | - ```${robot_name}/hvm/odometry_transformed``` (output of Emesent Hovermap odometry transformed to ) 73 | - frame_id: ```${robot_name}/odom``` 74 | -------------------------------------------------------------------------------- /pages/topic_lidar.md: -------------------------------------------------------------------------------- 1 | # LiDAR dataset 2 | 3 | ## Husky 4 | --- 5 | drawing 6 | 7 | - LiDAR data (```${robot_name}_lidar_*.bag```) 8 | - LiDAR topics (```sensor_msgs/PointCloud2```) 9 | - ```${robot_name}/velodyne/velodyne_points``` 10 | - frame_id: ```${robot_name}/velodyne``` 11 | - ```${robot_name}/velodyne_front/velodyne_points``` 12 | - frame_id: ```${robot_name}/velodyne_front``` 13 | - ```${robot_name}/velodyne_rear/velodyne_points``` 14 | - frame_id: ```${robot_name}/velodyne_rear``` 15 | - LiDAR packet topics (```velodyne_msgs/VelodyneScan```) 16 | - ```${robot_name}/velodyne_packets``` 17 | - frame_id: ```${robot_name}/velodyne``` 18 | - ```${robot_name}/velodyne_front/velodyne_packets``` 19 | - frame_id: ```${robot_name}/velodyne_front``` 20 | - ```${robot_name}/velodyne_rear/velodyne_packets``` 21 | - frame_id: ```${robot_name}/velodyne_rear``` 22 | - topics that you should not care about: 23 | - ```${robot_name}/velodyne_points_min_dist``` 24 | 25 | - IMU data (```imu.bag```) 26 | - ```${robot_name}/vn100/imu``` 27 | - frame_id: ```${robot_name}/vn100``` 28 | - ```${robot_name}/vn100/imu_wori_wcov``` 29 | - frame_id: ```${robot_name}/vn100``` 30 | 31 | - Odometry data (```odometry.bag```) 32 | - ```${robot_name}hero/wio_ekf/odom``` (wheeled-inertial odometry done by ) 33 | - frame_id: ```${robot_name}/odom``` 34 | - ```${robot_name}wheel_odom``` 35 | - frame_id: ```${robot_name}/odom``` 36 | 37 | ## Spot 38 | --- 39 | drawing 40 | 41 | - **LiDAR data** (```${robot_name}_lidar_*.bag```) 42 | - LiDAR ```sensor_msgs/PointCloud2``` topics 43 | - ```${robot_name}/velodyne/velodyne_points``` 44 | - frame_id: ```${robot_name}/velodyne``` 45 | - LiDAR packet topics (```velodyne_msgs/VelodyneScan```) 46 | - ```${robot_name}/velodyne_packets``` 47 | - Spot Realsense Point Cloud (```sensor_msgs/PointCloud2```) 48 | - ```/${robot_name}/spot_driver/local_grid``` 49 | - topics that you should not care about: 50 | - ```${robot_name}/velodyne_points_min_dist``` 51 | 52 | - **IMU data** (```imu.bag```) **(Note: keep in mind that in B, E IMU is not available)** 53 | - ```${robot_name}/vn100/imu``` 54 | - frame_id: ```${robot_name}/vn100``` 55 | - ```${robot_name}/vn100/imu_wori_wcov``` 56 | - frame_id: ```${robot_name}/vn100``` 57 | 58 | - **Odometry data** (```odometry.bag```) 59 | - ```${robot_name}/kinematic_odom``` (sometimes called legged odometry) 60 | - frame_id: ```${robot_name}/odom``` 61 | - ```${robot_name}/visual_odom``` (output of Boston Dynamics visual odometry algorithm) 62 | - frame_id: ```${robot_name}/odom``` --------------------------------------------------------------------------------