A soft body as a reservoir: case studies in a dynamic model of octopus-inspired soft robotic arm

Abstract

The behaviors of the animals or embodied agents are characterized by the dynamic coupling between the brain, the body, and the environment. This implies that control, which is conventionally thought to be handled by the brain or a controller, can partially be outsourced to the physical body and the interaction with the environment. This idea has been demonstrated in a number of recently constructed robots, in particular from the field of “soft robotics”. Soft robots are made of a soft material introducing high-dimensionality, non-linearity, and elasticity, which often makes the robots difficult to control. Biological systems such as the octopus are mastering their complex bodies in highly sophisticated manners by capitalizing on their body dynamics. We will demonstrate that the structure of the octopus arm cannot only be exploited for generating behavior but also, in a sense, as a computational resource. By using a soft robotic arm inspired by the octopus we show in a number of experiments how control is partially incorporated into the physical arm's dynamics and how the arm's dynamics can be exploited to approximate non-linear dynamical systems and embed non-linear limit cycles. Future application scenarios as well as the implications of the results for the octopus biology are also discussed.

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

“…Then, it is possible to autonomously generate a broad class of limit cycles, such as the Van der Pol oscillator, quadratic limit cycle, and Lissajous figures [28]. Importantly, these have been demonstrated in two different physical (simulated) reservoir computing setups: a mass-spring system [28] and an octopus arm [57].…”

“…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).…”

“…However, this approach was further complicated in a quadrupedal robot [19]. Nakajima et al [57] have used a model of a soft robotic arm inspired by the octopus. 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]).…”

Embodiment design of soft continuum robots

“…[30][31][32] It was then observed that the body dynamics may be used to control the arm's motion in a closed-loop manner by embedding nonlinear limit cycles. 8 However, the final step of bridging the gap between these findings and a robotic application was missing in previous works.…”

Active Shape Discrimination with Compliant Bodies as Reservoir Computers

“…Nakajima et al [26] extended the spring network to a biologically-inspired three-dimensional structure and it was shown that this body could also approximate filters and generate limit cycles. Finally, Zhao et al [36] replaced the spring network with the body of a spine-driven quadruped robot, referred to as 'Kitty', and used it to generate both locomotion and its own control signals.…”