Author:
Chen Yuheng,Wu Hongyun,Sui Qiru,Chen Yinghao,Wang Rongyao,Chen Bei,Chen Bingzheng,Li Jingwei,Yin Boling,Wang Chunlai
Abstract
Deep sea mining, as a frontier area in China, urgently needs to make progress in automatic navigation technology. In order to improve the operation efficiency of the seabed mining machine on the soft seabed, the submarine mining vehicle which complete the mining work in a certain mining area need to enter the next mining area quickly and economically. As a classical algorithm, the majority of scholars consider that A * algorithm is the most practical path planning search algorithm. Considering the limitation of operation conditions, the three-dimensional diagram is transformed into two-dimensional diagram by interpolation method when the seabed terrain conditions allow, and then the obstacles can be marked in two-dimensional diagram. A* algorithm was applied into the path planning of mining truck. The simulation results of the paper show that path cost, turning time and turning mode should be considered in the process of avoiding obstacles.
Reference9 articles.
1. Status and Progress on Researches and Developments of Deep Ocean Mining Equipments
2. Chen Feng. Research on motion modeling and control of deep seabed mining machine and truck [D]. Central south university, 2005.
3. YUAN Jing-ni,YANG Lin, Xiao-feng TANG, Ao-wen CHE. Autonomous Vehicle Motion Planning based on Improved RRT* Algorithm and Trajectory Optimization [J/OL]. Acta automatica sinica:1-10[2019-12-03]
4. Yeu Tae-Kyeong & Yoon Sukmin & Park Soung-jea & Hong Sup & Kim Hyungwoo & Lee Chang-Ho & Choi Jong-Su & Sung Ki-Young. (2012). Study on path tracking approach for underwater mining robot. 1–5. 10.1109/OCEANS-Yeosu.2012.6263579.
5. Pratama Pandu & Jeong Jae & Jeong Sang & Kim Hak-Kyeong & Kim Hwan & Yeu T K & Hong Sup & Kim Sang. (2016).
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献