| --- |
| license: gpl-3.0 |
| viewer: false |
| task_categories: |
| - robotics |
| --- |
| |
| # JEPLO Dataset |
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| This dataset accompanies the paper [JEPLO: Joint-Embedding Predictive Learning for LiDAR-Based Legged Locomotion](https://huggingface.co/papers/2609.15770). |
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| **Authors:** Qihao Yuan, Yixuan Qiu, Ziyu Cao, Ming Cao, and Kailai Li. |
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| **Project website:** [JEPLO](https://asig-x.github.io/jeplo_web/) |
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| **Code:** [ASIG-X/JEPLO](https://github.com/ASIG-X/JEPLO) |
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| **Video:** [YouTube](https://youtu.be/HekLtX37ijs?si=uoCrwZoS4Y4LlFco) |
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| This dataset is recorded onboard a Unitree Go2 using a Livox Mid360 LiDAR running a perceptive locomotion policy enabled by JEPLO. The dataset can be used for evaluating legged odometry systems in challenging scenarios using proprioceptive and exteroceptive sensors. |
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| ## Dataset Overview |
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| Publicly released to support the legged robotics community, the dataset comprises **eight sequences** recorded during our experiments: **five indoor sequences** and **three mixed indoor–outdoor sequences**. |
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| The sequences were recorded with a Unitree Go2 quadruped equipped with a Livox Mid360 LiDAR mounted upside down on the robot's head. The dataset provides complete proprioceptive and exteroceptive recordings, including: |
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| - Livox Mid360 LiDAR point clouds. |
| - Measurements from the LiDAR's built-in IMU. |
| - Joint encoder measurements. |
| - 6-DoF ground-truth trajectories. |
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| ## Ground Truth |
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| Indoor ground-truth 6-DoF poses are recorded at **100 Hz** in a **10 m × 4 m** test area using **eight Qualisys Miqus M3 motion-capture cameras**. |
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| Ground-truth trajectories are provided for each sequence in the `gt/` directory. Each trajectory is stored in **TUM trajectory format**, with one pose per line: |
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| ```text |
| timestamp tx ty tz qx qy qz qw |
| ``` |
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| The ground truth represents the **6-DoF pose of the LiDAR frame**. The fields `tx`, `ty`, and `tz` describe translation, and `qx`, `qy`, `qz`, and `qw` describe orientation as a quaternion. |
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| ## Custom ROS 2 Message |
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| Joint encoder measurements are published using the custom ROS 2 message `unitree_msgs/msg/LowStateStamped`. The message definition is available in `unitree_msgs/msg/`. |
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| `LowStateStamped` is a timestamped variant of the standard Unitree Go2 `LowState` message. It contains the robot's low-level state, including joint encoder measurements. |
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| ## Sensor Extrinsics |
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| The extrinsics below specify transformations **from the named source frame to the LiDAR frame**. Quaternion values use the order **`(qw, qx, qy, qz)`**, and translations are in **meters**. |
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| ### Built-in IMU Frame to LiDAR Frame |
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| ```yaml |
| q_li: [1, 0, 0, 0] # (qw, qx, qy, qz) |
| t_li: [0.011, 0.02329, -0.04412] # meters |
| ``` |
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| ### Robot Base Frame to LiDAR Frame |
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| ```yaml |
| q_lr: [0.0, 1.0, 0.0, 0.0] # (qw, qx, qy, qz) |
| t_lr: [-0.275263, 0.000458, 0.148998] # meters |
| ``` |
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| **Quaternion ordering:** The ground-truth trajectory files use `(qx, qy, qz, qw)`, whereas the sensor extrinsics above use `(qw, qx, qy, qz)`. |
