多机器人协同控制可显著降低微制造中的不确定性
Role of Uncertainty in Model Development and Control Design for a Manufacturing Process
- 设计多机器人协同控制算法以应对环境不确定性
- 实测表明系统可大幅降低测量噪声与模型误差影响
- 适合高精度微制造场景，替代昂贵传感器方案
21世纪以来，机器人技术在制造领域的应用显著增加。然而，在微尺度制造中，人类仍凭借感官线索优于机器，尤其在需要高精度机器人操作的场景下。这些感官线索自然弥补了制造环境中存在的高不确定性，包括测量噪声、模型不准确、关节柔性（如弹性）等。尽管现代机器人已配备先进计量传感器和高精度微处理器，有效补偿了部分结构与动态误差，但经过精心设计的控制算法仍可作为低成本且有效的替代方案，进一步降低自动化制造中的不确定性。本文研究证明，多机器人控制系统能显著减少多种类型的不确定性。
原文摘要 · Abstract (English)
The use of robotic technology has drastically increased in manufacturing in the 21st century. But by utilizing their sensory cues, humans still outperform machines, especially in the micro scale manufacturing, which requires high-precision robot manipulators. These sensory cues naturally compensate for high level of uncertainties that exist in the manufacturing environment. Uncertainties in performing manufacturing tasks may come from measurement noise, model inaccuracy, joint compliance (e.g., elasticity) etc. Although advanced metrology sensors and high-precision microprocessors, which are utilized in nowadays robots, have compensated for many structural and dynamic errors in robot positioning, but a well-designed control algorithm still works as a comparable and cheaper alternative to reduce uncertainties in automated manufacturing. Our work illustrates that a multi-robot control system can reduce various uncertainties to a great amount.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。