@inproceedings{f9f855d2fac440659c1fa2b75d08cdc2,
title = "Point cloud based path planning for tower crane lifting",
abstract = "This paper discusses automatic path planning for tower crane lifting in highly complex environments to be digitized using point cloud representation. A mathematical optimization technique is developed to identify the lifting path with GPU accelerated massively parallel genetic algorithm. A continuous collision detection method is designed for real time application of collision avoidance during the crane lifting process.",
keywords = "Automatic lifting path planning, Collision check, Complex environment, Depth map, Genetic algorithm, Point cloud, Rasterization, Tower crane",
author = "Lihui Huang and Yuzhe Zhang and Jianmin Zheng and Panpan Cai and Souravik Dutta and Yufeng Yue and Nadia Thalmann and Yiyu Cai",
note = "Publisher Copyright: {\textcopyright} 2018 ACM.; 2018 Computer Graphics International Conference, CGI 2018 ; Conference date: 11-06-2018 Through 14-06-2018",
year = "2018",
month = jun,
day = "11",
doi = "10.1145/3208159.3208186",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "211--215",
booktitle = "Proceedings of Computer Graphics International, CGI 2018",
}