Untethered Small-Scale Machines for Microrobotic Manipulation: From Individual and Multiple to Collective Machines
Qianqian Wang, Jiachen Zhang, Jiangfan Yu, Ji Lang, Zhiyang Lyu, Yunfei Chen, Li Zhang
Abstract
Untethered small-scale machines (USSMs) that can actively adjust their motion, deformation, and collective states in response to external stimuli have gained enormous interest in various manipulation, sensing, and biomedical applications. Because they can be efficiently operated in confined and tortuous environments, USSMs are capable of conducting wireless microrobotic manipulation tasks that tethered machines find hard to achieve. Over the past decade of development, significant research progress has been achieved in designing USSM-based manipulation strategies, which are enabled by investigating machine-object, machine-environment, and machine-machine interactions. This review summarizes the latest developments in USSMs for microrobotic manipulation by utilizing individual machines, coordinating multiple machines, and inducing collective behaviors. Providing recent studies and relevant applications in microrobotic and biomedical areas, we also discuss the challenges and future perspectives facing USSMs-based intelligent manipulation systems to achieve manipulation in complex environments with imaging-guided processes and increasing autonomy levels.