LAUSR

Due to an infinite number of degrees of freedom, soft robotic arms remain challenging to control when underactuated. Past work has drawn inspiration from biological structures–for example the elephant trunk–to design and control biomimetic soft robotic arms. However, to date, the models used to inform the control of biomimetic arms lack generalizability, and largely rely on qualitative assumptions. Here, we present a computationally efficient methodology to control fiber-based slender soft robotic arms inspired by the theory of active filaments. Our approach seeks to optimize fibrillar activation under prescribed control objectives. We evaluate the methodology under various control objectives, and consider several distinct fiber architectures. Our results suggest that we can efficiently compute fibrillar activations required to match the imposed control objective. Based on our findings, we discuss the effect of actuator complexity on actuation capabilities as a function of the number and arrangement of fibers. Our method can be applied universally towards the control and design of slender soft robotic arms with embedded fibers.