Perspective of self-learning robotics for disassembly automation
Perspective of self-learning robotics for disassembly automation
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DOI：
10.1109/icac55051.2022.9911085
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发表时间：
2022-09
期刊：
影响因子：
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通讯作者：
Farzaneh Goli;Yongjing Wang;M. Saadat
中科院分区：
文献类型：
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作者：
Farzaneh Goli;Yongjing Wang;M. Saadat
再制造在环境保护和循环经济中的重要作用日益受到重视。回收是再制造、维修和回收的关键操作。几个机器人拆卸的发展表明，使用机器人拆卸是可行的，但是，机器人的编程通常是复杂的，基于时间表，和耗时的。最近关于自学习机器人和人机协作的研究为无调度机器人创造了机会，其中开发了各种机器学习和深度学习技术。本文综述了自学习机器人的发展及其在机器人拆卸与再制造中的应用。重点分析了关键算法、设计、控制方法和未来的研究方向。这篇综述论文为机器人、智能再制造和拆卸自动化领域的研究人员提供了有用的资源。
Increasing attention has been paid to remanufacturing which plays an important role in environmental protection and circular economy. Disassembly is a key operation in remanufacturing, repair, and recycling. Several robotic disassembly developments have shown that the use of robots in disassembly is feasible; however, the programming of robots is usually complex, schedule-based, and time-consuming. Recent research about self-learning robotics and human-robot collaboration have created an opportunity for schedule-free robotics, in which various machine learning and deep learning techniques have been developed. This paper attempts to review the development of self-learning robots with applications in robotic disassembly and remanufacturing. Key algorithms, designs, control methods, and future research directions have been highlighted and analysed. This review paper serves as a useful resource for researchers in the areas of robotics, smart remanufacturing, and disassembly automation.