社会适应性认知架构用于工业环境中的人机协作
Ismael T Freire1, Oscar Guerrero-Rosado1, Adrián F Amil1
1Donders Institute for Brain, Cognition and Behaviour Radboud University, Nijmegen, Netherlands.
Frontiers in robotics and AI
|June 25, 2024
概括
本研究介绍了DAC-HRC,这是一个新的认知架构,用于优化工业4.0环境中的人机协作 (HRC). 它通过适应性,个性化交互来增强回收工厂运营,提高效率和安全性.
科学领域:
- 机器人和人工智能 机器人和人工智能
- 人与计算机的交互
- 工业自动化 工业自动化
背景情况:
- 有效的人机协作 (HRC) 对工业4.0至关重要.
- 现有的HRC系统往往缺乏适应个人人类用户的适应性.
- 优化HRC需要整合诸如联合意向性和相互依赖性等认知原则.
研究的目的:
- 引入DAC-HRC,一种用于工业环境中增强HRC的新型认知架构.
- 将DAC-HRC应用于废弃电气和电子设备 (WEEE) 的回收,以改善拆卸和回收过程.
- 开发一个新的社会熟练和高效的人机器人协作范式.
主要方法:
- 开发了基于分布式自适应控制理论的DAC-HRC架构.
- 集成的认知模块在多个时间尺度和抽象级别运行.
- 在混合回收工厂设置中应用了WEEE拆卸的架构.
主要成果:
- 证明了针对个人用户量身定制的个性化协作.
- 展示了包括自适应轮流,错误处理,安全措施和基于手势的通信在内的功能.
- 在试点研究中实现了实时机器人适应人类需求和偏好.
结论:
- DAC-HRC显著提高了工业回收工业中的人机协作.
- 该架构通过社会熟练的认知系统促进了无和高效的协作.
- DAC-HRC有助于推进工业4.0环境中的HRC的未来.
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