The shift from a linear to a circular economy has the potential to simultaneously reduce uncertainties of material supplies and waste generation. To date, the development of robotic and, more generally, autonomous systems have been rarely integrated into circular economy implementation strategies. In this review, we merge deep-learning vision, compartmental dynamical thermodynamics, and robotic manipulation into a theoretically-coherent physics-based research framework to lay the foundations of circular flow designs of materials, and hence, to speed-up the transition from linearity to circularity. Then, we discuss opportunities for robotics in circular economy.

翻译：从线性经济向循环经济的转型有望同时降低材料供应和废物产生的不确定性。迄今为止，机器人及更广泛的自主系统的发展很少被纳入循环经济的实施策略中。本综述将深度学习视觉、区室化动态热力学与机器人操作整合为一个理论自洽的基于物理学的研究框架，旨在为材料的循环流动设计奠定基础，从而加速从线性模式向循环模式的转变。最后，我们探讨了机器人在循环经济中的应用前景。