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基于rMAPPO的机器人调度方法用于H束和接工作单元
Jianbin Zheng1, Chuyi Zhou1, Yang Gao1
1Hubei Key Laboratory of Broadband Wireless Communication and Sensor Networks, School of Information Engineering, Wuhan University of Technology, Wuhan, Hubei, China.
PloS one
|September 4, 2025
概括
一个新的反复的多代理近距离策略优化 (rMAPPO) 算法通过优化机器人调度来增强H束制造. 这种智能制造方法显著提高了效率,并减少了机器人在自动化工作单元中的等待时间.
科学领域:
- 机器人和自动化
- 人工智能
- 制造工程
背景情况:
- 自动化H束处理涉及复杂的多剂协调,例如钉和接硬化板.
- 现有的H束和接工作单元在智能制造框架内具有未开发的生产力提升潜力.
研究的目的:
- 用一种新的强化学习算法来解决H束处理中的多代理调度问题.
- 提高制造效率并减少自动化H束工作单元的运行延迟.
主要方法:
- 开发一个循环多代理近接策略优化 (rMAPPO) 算法,结合循环神经网络和动作掩盖.
- 创建一个强化学习环境,用于H束处理任务的多代理调度.
- 在物理工作单元及其数字双胞胎上验证rMAPPO算法,并将其与基线多代理强化学习方法进行比较.
主要成果:
- 与基线方法 (MAPPO,MADDPG,MASAC) 相比,基于rMAPPO的调度方法有效地减少了机器人的等待时间.
- 在管理各种和接任务方面表现出更强的适应性.
- 在硬化H梁的整体制造效率上取得了显著的改进.
结论:
- 拟议的rMAPPO算法为自动化H束制造中的多代理调度提供了强大的解决方案.
- 这种方法通过优化机器人任务协调和提高生产效率来显著提高智能制造.
- 该方法的有效性在物理平台和模拟平台上得到了验证,突出了其实际适用性.
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