协作共赢：敏捷工业环境下的系统效率与韧性优化
Collaborating for Success: Optimizing System Efficiency and Resilience Under Agile Industrial Settings
AI总结：
针对敏捷工业人机协作中效率与韧性兼顾的难题，提出融合2D激光与3D视觉的分层控制方案，通过扩展安全监测区与速度调节，经实验验证可有效缩短任务时长与响应延迟。
摘要：
设计一种高效且具韧性的人机协作策略，既要保障共享工作空间的安全性与工效学，又要提升协作装置的性能与敏捷性，这在环境感知与机器人控制方面带来了重大挑战。本研究提出一种协作环境监测与机器人运动调节的新方法，以解决这一多维度问题。我们的研究提出了符合ISO 13855与TS 15066标准的安全监测区的新型计算与划分方式，利用2D激光信息实现。这些监测区不仅采用标准的三层结构配置，还扩展至两个相邻象限，从而提升系统正常运行时间并避免不必要的死锁。此外，我们还利用3D视觉信息追踪人体动态关节运动与延伸侵入行为。基于2D与3D感知空间的融合传感数据，我们提出的分层控制器可稳定调节机器人速度，该控制器已通过拉萨尔不变性原理验证。实证评估表明，我们的方法显著缩短了任务执行时间与系统响应延迟，提升了协作场景下的效率与韧性。
英文摘要：
Designing an efficient and resilient human-robot collaboration strategy that not only upholds the safety and ergonomics of shared workspace but also enhances the performance and agility of collaborative setup presents significant challenges concerning environment perception and robot control. In this research, we introduce a novel approach for collaborative environment monitoring and robot motion regulation to address this multifaceted problem. Our study proposes novel computation and division of safety monitoring zones, adhering to ISO 13855 and TS 15066 standards, utilizing 2D lasers information. These zones are not only configured in the standard three-layer arrangement but are also expanded into two adjacent quadrants, thereby enhancing system uptime and preventing unnecessary deadlocks. Moreover, we also leverage 3D visual information to track dynamic human articulations and extended intrusions. Drawing upon the fused sensory data from 2D and 3D perceptual spaces, our proposed hierarchical controller stably regulates robot velocity, validated using Lasalle in-variance principle. Empirical evaluations demonstrate that our approach significantly reduces task execution time and system response delay, resulting in improved efficiency and resilience within collaborative settings.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
