ONR TBD: Octopus-Inspired Autonomous Arms for Soft Robots with Adaptive Motions
We propose to create a framework for design, rapid prototyping and control of robust, energy-efficient, autonomous soft arms with octopus-inspired distributed neuromuscular sensing and actuation. The arms will be capable of continuous deformation through the use of hydrogel “muscles” and distributed sensing through the use of embedded silver “neuron” interconnections. Such a unique octopus-inspired design forms a built-in local “sensing-actuation” feedback loop to achieve adaptive reconfiguration in response to the local environment. Such local adaptation will enable the robot to perform high-level tasks such as locomotion and reversible adhesion without coordination from a central controller in a highly accurate, rapid, and energy-efficient way. This study will also produce fundamental principles and theory for the modeling and control of soft robots in a way which leverages their unique capabilities and is inspired by how cephalopod appendages interact with their environment. Our cross-disciplinary team unifies biological neuromuscular studies, novel responsive soft material development, new distributed sensing and dynamic control theories, and rapid prototyping manufacturing technique to achieve the aforementioned goals.
Ximin He (PI), Arizona State University
Matthew M. Peet (co-PI), Arizona State University
Spring Berman (co-PI), Arizona State University
Hamid Marvi (co-PI), Arizona State University
Dan Aukes (co-PI), Arizona State University
Rebecca Fischer (co-PI), University of Arizona