ROOAD
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RELLIS Off-road Odometry Analysis Dataset
ROOAD: RELLIS Off-road Odometry Analysis Dataset
George Chustz1 and Srikanth Saripalli1
[Download All] [Cite Us]
Updates
9/15/2021 Initial release
Overview
Localization is one of the fundamental problems in robotics. Visual Inertial Odometry is a set of algorithms which attempt to estimate the position and orientation of a subject using only camera(s) and an inertial measurement unit (IMU). We release the RELLIS Off-road Odometry Analysis Dataset to fill a void in available VIO datasets to provide high-quality, accurately time stamped off-road traversal data sequences for VIO researchers and developers. Across our data sequences, there is over 20,000 images, 250,000 IMU readings, and 6,000 RTK + heading measurements.
Data Collection Platform
Sensor Suite
Dimensions in cm.
- Basler Pylon Camera - 1920x1200 @ 30FPS, PTP enabled, Driver here
- Vectornav VN300 IMU - 400 Hz, GPS denied, Driver here
- Ardusimple simpleRTK2B kit - 10 Hz, RTK GPS + heading, Driver here
ROS Bag
Data included in raw ROS bagfiles:
| Topic Name | Message Type | Message Descriptison |
|---|---|---|
| /pylon_camera_node/image_raw | sensor_msgs/Image | Images from the Basler Pylon Camera |
| /vectornav/IMU | sensor_msgs/Imu | Imu data from VectorNav-VN300 |
| /UBX/hpposllh | ubxtranslator/hpposllh | GPS data from the ground truth RTK GPS |
| /UBX/relpos2D | ubxtranslator/relpos2D |
ROS BAG file, ground truth, and calibration results download links:
| Dataset | Bag | Result/Ground truth |
|---|---|---|
| rt4_calib | Bag Download [6GB] | Kalibr Results TXT |
| rt4_gravel | Bag Download [8GB] | Ground Truth CSV |
| rt4_rim | Bag Download [5GB] | Ground Truth CSV |
| rt4_updown | Bag Download [12GB] | Ground Truth CSV |
| rt5_calib | Bag Download [6GB] | Kalibr Results TXT |
| rt5_gravel | Bag Download [7GB] | Ground Truth CSV |
| rt5_rim | Bag Download [5GB] | Ground Truth CSV |
| rt5_updown | Bag Download [10GB] | Ground Truth CSV |
VIO Evaluation
To complement our data contribution, we have also evaluated two leading VIO implementations on our datasets, OpenVINS and VINS-Fusion. Their estimated trajectories and videos of their performances can be found below.
RT5 Gravel
OpenVINS
VINS-Fusion
RT5 Rim
OpenVINS
VINS-Fusion
RT5 Updown
OpenVINS
VINS-Fusion
Kalibr Evaluation Dataset
In order to determine the efficacy of Kalibr's extrinsics calibration tool, we collected an additional 11 ROS bags of camera-IMU extrinsic calibration motion.
- Calibration Datasets Download 38GB
- The IMU, camera, and target parameters are given here.
Cite Us
@misc{chustz2021rooad,
title={ROOAD: RELLIS Off-road Odometry Analysis Dataset},
author={George Chustz and Srikanth Saripalli},
year={2021},
eprint={2109.08228},
archivePrefix={arXiv},
primaryClass={cs.RO}
}
License
All datasets and code on this page are copyright by us and published under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License.
Related Work
RELLIS-3D: A Multi-modal Dataset for Off-Road Robotics
A RUGD Dataset for Autonomous Navigation and Visual Perception inUnstructured Outdoor Environments
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