title: Information processing via physical soft body.
abstract: Soft machines have recently gained prominence due to their inherent softness and the resulting safety and resilience in applications. However, these machines also have disadvantages, as they respond with complex body dynamics when stimulated. These dynamics exhibit a variety of properties, including nonlinearity, memory, and potentially infinitely many degrees of freedom, which are often difficult to control. Here, we demonstrate that these seemingly undesirable properties can in fact be assets that can be exploited for real-time computation. Using body dynamics generated from a soft silicone arm, we show that they can be employed to emulate desired nonlinear dynamical systems. First, by using benchmark tasks, we demonstrate that the nonlinearity and memory within the body dynamics can increase the computational performance. Second, we characterize our system's computational capability by comparing its task performance with a standard machine learning technique and identify its range of validity and limitation. Our results suggest that soft bodies are not only impressive in their deformability and flexibility but can also be potentially used as computational resources on top and for free.
authors.affiliation: The Hakubi Center for Advanced Research &Graduate School of Informatics, Kyoto University, 606-8501 Kyoto, Japan.
authors.forename: Kohei
authors.initials: K
authors.lastname: Nakajima
authors.affiliation: Department of Engineering Mathematics, University of Bristol, Bristol BS8 1UB, United Kingdom.
authors.forename: Helmut
authors.initials: H
authors.lastname: Hauser
authors.affiliation: Department of Engineering and Information Technology, Bern University of Applied Sciences, 2501 Biel, Switzerland.
authors.forename: Tao
authors.initials: T
authors.lastname: Li
authors.affiliation: 1] Institute for Academic Initiatives, Osaka University, Osaka 560-8531, Japan [2] Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China.
authors.forename: Rolf
authors.initials: R
authors.lastname: Pfeifer