ASIG-Lab/JEPLO-Dataset

JEPLO Dataset

This dataset accompanies the paper JEPLO: Joint-Embedding Predictive Learning for LiDAR-Based Legged Locomotion.

Authors: Qihao Yuan, Yixuan Qiu, Ziyu Cao, Ming Cao, and Kailai Li.

Project website: JEPLO

Code: ASIG-X/JEPLO

Video: YouTube

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.

Dataset Overview

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.

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:

• Livox Mid360 LiDAR point clouds.
• Measurements from the LiDAR's built-in IMU.
• Joint encoder measurements.
• 6-DoF ground-truth trajectories.

Ground Truth

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.

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:

timestamp tx ty tz qx qy qz qw

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.

Custom ROS 2 Message

Joint encoder measurements are published using the custom ROS 2 message unitree_msgs/msg/LowStateStamped. The message definition is available in unitree_msgs/msg/.

LowStateStamped is a timestamped variant of the standard Unitree Go2 LowState message. It contains the robot's low-level state, including joint encoder measurements.

Sensor Extrinsics

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.

Built-in IMU Frame to LiDAR Frame

q_li: [1, 0, 0, 0] # (qw, qx, qy, qz)
t_li: [0.011, 0.02329, -0.04412] # meters

Robot Base Frame to LiDAR Frame

q_lr: [0.0, 1.0, 0.0, 0.0] # (qw, qx, qy, qz)
t_lr: [-0.275263, 0.000458, 0.148998] # meters

Quaternion ordering: The ground-truth trajectory files use (qx, qy, qz, qw), whereas the sensor extrinsics above use (qw, qx, qy, qz).