Embodying physical computing into soft robots

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Authors: Jun Wang, Ziyang Zhou, Ardalan Kahak, Suyi Li
Cited by: 3
References: 135

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. Physical computing in soft robots reveals new principles of mechanical intelligence. The authors show that embodied oscillators, reservoir dynamics and mechanical logic enable robots to sense act and move without conventional electronics.

Fields of Study & Subjects

Neural Networks and Reservoir Computing Advanced Memory and Neural Computing Ferroelectric and Negative Capacitance Devices

Publication details

Journal / source
Nature Communications
Publisher
Springer Science and Business Media LLC
Volume
17
Issue
1
Publication date
15 March 2026
Language
EN