集装箱码头桥吊作业的强化学习优化

Reinforcement Learning Optimization of Bridge Craner Opearations at Container Terminals

对码头桥吊装卸操作进行强化学习优化,通过Unity建立码头桥吊的模型及训练环境,用PPO算法对码头桥吊进行装卸操作训练,最终使桥吊学习在海浪及大风对集装箱船和吊具造成晃动影响时的平稳下落行为,提高桥吊抓取准确性并优化桥吊路径,实现更高效智能的码头装卸作业。

In this paper,reinforcement learning was used to optimize the loading and unloading operations of quay bridge cranes,a model and training environment was built for cranes through Unity,and PPO algorithm was used to train the loading and unloading operations of cranes,so that the cranes can learn to lower smoothly when waves and high winds affect the container ship and lifting gears.Eventually this can improve the accuracy of crane grasping and optimize the path of cranes to achieve more efficient and intelligent loading and unloading operations at terminals.