automine dataset

Automine Dataset

Overview

AutoMine is the first autonomous driving dataset for perception and localization in mine scenarios which is unstructured special scenarios . Automine can provide data assistance for research in autonomous driving, computer vision, deep learning and so on. Automine is freely open to non-commercial using.

In 2021, we collected 18+ hours of mine driving data, covering more than 70 scenarios, and annotated 36,000 lidar and image frames for 3D perception.

Task

At present, AutoMine supports two major autonomous driving tasks. More tasks will be taken into account in the future.

Localization

w to maximum learning potential.

We offer the abundant vehicle location information based on the GPS and IMU. We recommend users to utilize the lidar-based, lidar-inertia SLAM (Simultaneous Localization and Mapping), pure vision, vision-inertia SLAM and fusion SLAM methods on our dataset.

Perception

There are 36k frames of data in the whole perception dataset (12k frames per platform on average). We annotated data provides roll and pitch angles, especially pitch angles. We hope that researchers can explore all the 9 DoF (degrees of freedom), with special attention to roll and pitch, which is essential for safe driving in strip mines rather than just the yaw angle.

Each student has access to the best possible learning technologies, as well having guest classes from industry professionals. We believe this better prepares your child for their careers or own businesses.

References

Yuchen Li, Zixuan Li, Siyu Teng, Yu Zhang, Yuhang Zhou, Yuchang Zhu,Bin Tian, Yunfeng Ai, Dongpu Cao, Zhe Xuanyuan, Long Chen AutoMine: An Unmanned Mine Dataset [CVPR2022-9913]

Each student has access to the best possible learning technologies, as well having guest classes from industry professionals. We believe this better prepares your child for their careers or own businesses.

Contact Us

We are Automine team, free to support with comments, feedback.