Point cloud Dateset

Citation Author(s):
Qingxin
Zhang
Submitted by:
Qingxin Zhang
Last updated:
Wed, 03/05/2025 - 19:27
DOI:
10.21227/n9rr-fv23
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Abstract 

This dataset is specifically designed for the recognition and localization of electric vehicle (EV) charging ports using point cloud data, rather than traditional image-based methods. It includes raw point cloud data collected from advanced sensing technologies such as LiDAR or depth cameras, along with detailed experimental records that encompass sensor parameters, pose annotations, and environmental variables. The raw data consists of high-resolution 3D point clouds that capture the charging ports from multiple perspectives, enabling a comprehensive understanding of their spatial characteristics under various conditions. This dataset is particularly valuable for developing and testing algorithms in 3D object recognition, pose estimation, and autonomous systems, as it provides a rich and diverse set of point cloud data that reflects real-world scenarios. By leveraging this dataset, researchers and engineers can enhance the accuracy and robustness of EV charging port detection systems, which is crucial for the advancement of autonomous driving and smart infrastructure technologies.

Instructions: 

Please to see Readme file.

Comments

这部分数据集是我为自己的实验环境进行的点云采集,大家可以分享一下供参考

Submitted by Qingxin Zhang on Wed, 03/05/2025 - 19:32

Documentation

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File Readme.txt391 bytes