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.

What Is Morphological Computation? On How the Body Contributes to Cognition and Control

“…This very much blurs the boundaries between the brain as the seat of computing and the "mere physical body," in accordance with biological reality, which will be discussed in the next section. However, thus far the examples of this type [28,57,58,11,19,37] have a theoretical or proof-of-concept character, and their applicability remains to be proven ( Figure 9I-J).…”

“…In a simulated arm in an underwater environment, they successfully embedded the same benchmarks used by Hauser et al in the open-loop system (2nd-and 10th-order dynamical system and Volterra series [27]) and in the system with feedback (Van der Pol equations, quadratic limit cycle, and Lissajous curve [28]). Extensions on an actual physical silicone arm in a water tank were presented in [58].…”

“…The eye of the fly (e), artificial compound eye (f) [23], cochlea (g), and whiskers of a rat (h) are examples of morphology facilitating perception. Morphological computation is represented by the spring-mass computer [28] and the octopus arm reservoir [58]. Of course, the preprocessing performed by the morphology tells only half of the story-a passive perception one in this case.…”

Stable propagation of mechanical signals in soft media using stored elastic energy

“…soft | mechanical signal | stable propagation | instability S oft, highly deformable materials have enabled the design of new classes of tunable and responsive systems and devices, including bioinspired soft robots (1, 2), self-regulating microfluidics (3), adaptive optics (4), reusable energy-absorbing systems (5,6), structures with highly programmable responses (7), and morphological computing paradigms (8). However, their highly deformable and dissipative nature also poses unique challenges.…”

Morphological Computing and Cognitive Agency

“…The role of such computation in cognitive systems includes the off-loading of control onto the body and its interaction with the environment thus enabling flexible and adaptive behavior [2][3][4][5][6][7]. In a more general sense, cognitive agency instantiated by the interaction processes of morphological structures in networks of networks of cognitive agents from cells to organisms and societies is a basis of understanding of embodiment of cognition on variety of levels of (self-)organisation of physical matter from its basic physical structures via chemistry and biology with life itself as cognitive process [1].…”