虚拟,增强和混合现实机器人辅助深度强化学习向智能制造迈进
Than Le1, Le Quang Vinh2, Van Huy Pham3
1Institute of Engineering and Technology, Thu Dau Mot University, Thu Dau Mot 75100, Vietnam.
Sensors (Basel, Switzerland)
|September 19, 2025
概括
这项研究通过使用虚拟,增强和混合现实 (VAM) 和深度增强学习 (DRL) 来增强接机器人模拟. 这提高了智能制造中的机器人精度和效率.
科学领域:
- 机器人和自动化 机器人和自动化
- 制造业 工程 制造工程
- 计算机科学 计算机科学
背景情况:
- 接机器人对于现代制造业的精度和效率至关重要.
- 精确的模拟对于优化接机器人的性能和最大限度地减少错误至关重要.
- 现有的模拟方法需要改进,以获得更高的现实性和真实性.
研究的目的:
- 介绍一种用于增强接机器人模拟的新方法.
- 为了提高机器人行为模拟的真实性和真实性.
- 用先进的技术加速学习和优化接机器人操作.
主要方法:
- 将虚拟,增强和混合现实 (VAM) 模拟平台与现有技术集成.
- 深度强化学习 (DRL) 的应用用于任务卸载和实时轨迹规划.
- 使用自适应神经模糊推理系统 (ANFIS) 进行控制策略比较.
主要成果:
- 该VAM平台提供了一个动态和现实的环境来模拟机器人的行动和互动.
- DRL集成提高了模拟准确度,并改善了机器人的实时决策.
- 实验结果表明,ANFIS在准确性和融合速度方面优于传统的PID和模糊逻辑控制 (FLC).
结论:
- 将像VAM这样的先进模拟平台与机器学习 (特别是DRL) 结合起来,大大提高了工业机器人的能力.
- 拟议的方法提高了接机器人模拟现实性和智能制造中的运营效率.
- 在接机器人控制方面,ANFIS表现出比PID和FLC更好的性能.
相关概念视频
02:16Stereotype Content Model
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence categorization, a person will feel...
01:16Non-equilibrium in the Cell
An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...