Open AccessComputationally Assisted Design and Selection of Maneuverable Biological Walking Machines
Author(s) -
Wang Jiaojiao,
Zhang Xiaotian,
Park Junehu,
Park Insu,
Kilicarslan Evin,
Kim Yongdeok,
Dou Zhi,
Bashir Rashid,
Gazzola Mattia
Publication year - 2021
Publication title -
advanced intelligent systems
Language(s) - English
Resource type - Journals
ISSN - 2640-4567
DOI - 10.1002/aisy.202000237
Subject(s) - robotics , robot , computer science , dual (grammatical number) , biomimetics , actuator , variety (cybernetics) , artificial intelligence , control engineering , simulation , engineering , art , literature
The intriguing opportunities enabled by the use of living components in biological machines have spurred the development of a variety of muscle‐powered biohybrid robots in recent years. Among them, several generations of tissue‐engineered biohybrid walkers have been established as reliable platforms to study untethered locomotion. However, despite these advances, such technology is not mature yet, and major challenges remain. Herein, steps are taken to address two of them: the lack of systematic design approaches, common to biohybrid robotics in general, and in the case of biohybrid walkers specifically, the lack of maneuverability. A dual‐ring biobot is presented which is computationally designed and selected to exhibit robust forward motion and rotational steering. This dual‐ring biobot consists of two independent muscle actuators and a four‐legged scaffold asymmetric in the fore/aft direction. The integration of multiple muscles within its body architecture, combined with differential electrical stimulation, allows the robot to maneuver. The dual‐ring robot design is then fabricated and experimentally tested, confirming computational predictions and turning abilities. Overall, a design approach based on modeling, simulation, and fabrication exemplified in this versatile robot represents a route to efficiently engineer complex biological machines with adaptive functionalities.