Embodying Physical Computing into Soft Robots

TL;DR

This paper explores integrating physical computing into soft robots to enhance their robustness and intelligence, enabling complex behaviors without traditional electronics through embodied mechanical computation strategies.

Contribution

It proposes a framework for embedding physical computing in soft robots and reviews three innovative strategies: analog oscillators, physical reservoir computing, and physical algorithmic computing.

Findings

Enables soft robots to perform obstacle avoidance and locomotion.

Allows classification of payload weight and orientation.

Supports programmable operations based on logical rules.

Abstract

Softening and onboarding computers and controllers is one of the final frontiers in soft robotics towards their robustness and intelligence for everyday use. In this regard, embodying soft and physical computing presents exciting potential. Physical computing seeks to encode inputs into a mechanical computing kernel and leverage the internal interactions among this kernel's constituent elements to compute the output. Moreover, such input-to-output evolution can be re-programmable. This perspective paper proposes a framework for embodying physical computing into soft robots and discusses three unique strategies in the literature: analog oscillators, physical reservoir computing, and physical algorithmic computing. These embodied computers enable the soft robot to perform complex behaviors that would otherwise require CMOS-based electronics -- including coordinated locomotion with obstacle avoidance, payload weight and orientation classification, and programmable operation based on logical rules. This paper will detail the working principles of these embodied physical computing methods, survey the current state-of-the-art, and present a perspective for future development.