Year: 2023
Type: article
Abstract: Reconfigurable morphing surfaces provide new opportunities for advanced human-machine interfaces and bio-inspired robotics. Morphing into arbitrary surfaces on demand requires a device with a sufficiently large number of actuators and an inverse control strategy. Developing compact, efficient control interfaces and algorithms is vital for broader adoption. In this work, we describe a passively addressed robotic morphing surface (PARMS) composed of matrix-arranged ionic actuators. To reduce the complexity of the physical control interface, we introduce passive matrix addressing. Matrix addressing allows the control of N 2 independent actuators using only 2 N control inputs, which is substantially lower than traditional direct addressing ( N 2 control inputs). Using machine learning with finite element simulations for training, our control algorithm enables real-time, high-precision forward and inverse control, allowing PARMS to dynamically morph into arbitrary achievable predefined surfaces on demand. These innovations may enable the future implementation of PARMS in wearables, haptics, and augmented reality/virtual reality.
Source: Science Advances
Authors: Jue Wang, Michael Sotzing, Mina Lee, Alex Chortos
Institution: Purdue University West Lafayette
Language: English
Field: Materials Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $4,500
Funder: Purdue University
OpenAlex ID: W4385063883