Remote control of muscle-driven miniature robots with battery-free wireless optoelectronics

Yongdeok Kim(University of Illinois Urbana-Champaign), Yongdeok Kim(Northwestern University), Yiyuan Yang(Northwestern University), Xiaotian Zhang(Northwestern University), Zhengwei Li(Northwestern University), Abraham Vázquez‐Guardado(Northwestern University), Insu Park(University of Illinois Urbana-Champaign), Jiaojiao Wang(Northwestern University), Andrew I. Efimov(Northwestern University), Zhi Dou(Northwestern University), Yue Wang(Northwestern University), Junehu Park(Northwestern University), Haiwen Luan(Northwestern University), Xinchen Ni(Northwestern University), Yun Seong Kim(University of Illinois Urbana-Champaign), Yun Seong Kim(Northwestern University), Janice Mihyun Baek(University of Illinois Urbana-Champaign), Joshua Jaehyung Park(Northwestern University), Zhaoqian Xie(University of Illinois Urbana-Champaign), Hangbo Zhao(Northwestern University), Mattia Gazzola(University of Illinois Urbana-Champaign), John A. Rogers(Northwestern University), Rashid Bashir(University of Illinois Urbana-Champaign)
Science Robotics
January 18, 2023
Cited by 116

Abstract

Bioengineering approaches that combine living cellular components with three-dimensional scaffolds to generate motion can be used to develop a new generation of miniature robots. Integrating on-board electronics and remote control in these biological machines will enable various applications across engineering, biology, and medicine. Here, we present hybrid bioelectronic robots equipped with battery-free and microinorganic light-emitting diodes for wireless control and real-time communication. Centimeter-scale walking robots were computationally designed and optimized to host on-board optoelectronics with independent stimulation of multiple optogenetic skeletal muscles, achieving remote command of walking, turning, plowing, and transport functions both at individual and collective levels. This work paves the way toward a class of biohybrid machines able to combine biological actuation and sensing with on-board computing.


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