Toward Self-Modifying Bio-Soft Robots

Soft robotics can dramatically increase the affinity between machines and biological systems. Designing the machine/device to be soft and deformable allows the biological system to interact with the robotic system(s) mechanically, electronically, and chemically. This advantage is evident from the rapid growth of collaborative robotics, where a robot can be mechanically guided by an operator to learn motions from them without the need for coding. This letter introduces a method for combining a soft robotic system with a biological system, demonstrated through a series of case studies of ongoing research projects. These various projects have a common purpose in creating self-modifying bio-soft robots.

Continuum Robotic Caterpillar with Wirelessly Powered Shape Memory Alloy Actuators

Wireless power transfer (WPT) has the significant potential for soft-bodied continuum robots to extend the operational time limitlessly and reduce weight. However, rigid power receiver coils, widely used in WPT, hinder the continuum deformation of the robot, and as a result, the function realization using the continuum deformation (e.g., locomotion) is impaired. Therefore, this article introduces that a soft-bodied continuum robot can be designed by using thin film receiver coils and an inductively coupled wireless powering solution without sacrificing the continuum deformation and locomotion ability. A system is described for powering and controlling a soft robotic caterpillar consisting of nothing more than its continuum structure, actuators, and thin/flexible power receiving coils.

Exploring Behaviors of Caterpillar-Like Soft Robots with a Central Pattern Generator-Based Controller and Reinforcement Learning

Due to their flexibility, soft-bodied robots can potentially achieve rich and various behaviors within a single body. However, to date, no methodology has effectively harnessed these robots to achieve such diverse desired functionalities. Controllers that accomplish only a limited range of behaviors in such robots have been handcrafted. Moreover, the behaviors of these robots should be determined through body–environment interactions because an appropriate behavior may not always be manifested even if the body dynamics are given. Therefore, we have proposed SenseCPG-PGPE, a method for automatically designing behaviors for caterpillar-like soft-bodied robots. This method optimizes mechanosensory feedback to a central pattern generator (CPG)-based controller, which controls actuators in a robot, using policy gradients with parameter-based exploration (PGPE). In this article, we deeply investigated this method. We found that PGPE can optimize a CPG-based controller for soft-bodied robots that exhibit viscoelasticity and large deformation, whereas other popular policy gradient methods, such as trust region policy optimization and proximal policy optimization, cannot. Scalability of the method was confirmed using simulation as well. Although SenseCPG-PGPE uses a CPG-based controller, it can achieve nonsteady motion such as climbing a step in a simulated robot. The approach also resulted in distinctive behaviors depending on different body–environment conditions. These results demonstrate that the proposed method enables soft robots to explore a variety of behaviors automatically.

Gait control in a soft robot by sensing interactions with the environment using self-deformation

All animals use mechanosensors to help them move in complex and changing environments. With few exceptions, these sensors are embedded in soft tissues that deform in normal use such that sensory feedback results from the interaction of an animal with its environment. Useful information about the environment is expected to be embedded in the mechanical responses of the tissues during movements. To explore how such sensory information can be used to control movements, we have developed a soft-bodied crawling robot inspired by a highly tractable animal model, the tobacco hornworm Manduca sexta. This robot uses deformations of its body to detect changes in friction force on a substrate. This information is used to provide local sensory feedback for coupled oscillators that control the robot's locomotion. The validity of the control strategy is demonstrated with both simulation and a highly deformable three-dimensionally printed soft robot. The results show that very simple oscillators are able to generate propagating waves and crawling/inching locomotion through the interplay of deformation in different body parts in a fully decentralized manner. Additionally, we confirmed numerically and experimentally that the gait pattern can switch depending on the surface contact points. These results are expected to help in the design of adaptable, robust locomotion control systems for soft robots and also suggest testable hypotheses about how soft animals use sensory feedback.

Softworms: the design and control of non-pneumatic, 3D-printed, deformable robots

Robots that can easily interact with humans and move through natural environments are becoming increasingly essential as assistive devices in the home, office and hospital. These machines need to be safe, effective, and easy to control. One strategy towards accomplishing these goals is to build the robots using soft and flexible materials to make them much more approachable and less likely to damage their environment. A major challenge is that comparatively little is known about how best to design, fabricate and control deformable machines. Here we describe the design, fabrication and control of a novel soft robotic platform (Softworms) as a modular device for research, education and public outreach. These robots are inspired by recent neuromechanical studies of crawling and climbing by larval moths and butterflies (Lepidoptera, caterpillars). Unlike most soft robots currently under development, the Softworms do not rely on pneumatic or fluidic actuators but are electrically powered and actuated using either shape-memory alloy microcoils or motor tendons, and they can be modified to accept other muscle-like actuators such as electroactive polymers. The technology is extremely versatile, and different designs can be quickly and cheaply fabricated by casting elastomeric polymers or by direct 3D printing. Softworms can crawl, inch or roll, and they are steerable and even climb steep inclines. Softworms can be made in any shape but here we describe modular and monolithic designs requiring little assembly. These modules can be combined to make multi-limbed devices. We also describe two approaches for controlling such highly deformable structures using either model-free state transition-reward matrices or distributed, mechanically coupled oscillators. In addition to their value as a research platform, these robots can be developed for use in environmental, medical and space applications where cheap, lightweight and shape-changing deformable robots will provide new performance capabilities.

True-slime-mould-inspired hydrostatically coupled oscillator system exhibiting versatile behaviours

Behavioural diversity is an indispensable attribute of living systems, which makes them intrinsically adaptive and responsive to the demands of a dynamically changing environment. In contrast, conventional engineering approaches struggle to suppress behavioural diversity in artificial systems to reach optimal performance in given environments for desired tasks. The goals of this research include understanding the essential mechanism that endows living systems with behavioural diversity and implementing the mechanism in robots to exhibit adaptive behaviours. For this purpose, we have focused on an amoeba-like unicellular organism: the plasmodium of true slime mould. Despite the absence of a central nervous system, the plasmodium exhibits versatile spatiotemporal oscillatory patterns and switches spontaneously among these patterns. By exploiting this behavioural diversity, it is able to exhibit adaptive behaviour according to the situation encountered. Inspired by this organism, we built a real physical robot using hydrostatically coupled oscillators that produce versatile oscillatory patterns and spontaneous transitions among the patterns. The experimental results show that exploiting physical hydrostatic interplay—the physical dynamics of the robot—allows simple phase oscillators to promote versatile behaviours. The results can contribute to an understanding of how a living system generates versatile and adaptive behaviours with physical interplays among body parts.

Fully decentralized control of a soft-bodied robot inspired by true slime mold

Animals exhibit astoundingly adaptive and supple locomotion under real world constraints. In order to endow robots with similar capabilities, we must implement many degrees of freedom, equivalent to animals, into the robots' bodies. For taming many degrees of freedom, the concept of autonomous decentralized control plays a pivotal role. However a systematic way of designing such autonomous decentralized control system is still missing. Aiming at understanding the principles that underlie animals' locomotion, we have focused on a true slime mold, a primitive living organism, and extracted a design scheme for autonomous decentralized control system. In order to validate this design scheme, this article presents a soft-bodied amoeboid robot inspired by the true slime mold. Significant features of this robot are twofold: (1) the robot has a truly soft and deformable body stemming from real-time tunable springs and protoplasm, the former is used for an outer skin of the body and the latter is to satisfy the law of conservation of mass; and (2) fully decentralized control using coupled oscillators with completely local sensory feedback mechanism is realized by exploiting the long-distance physical interaction between the body parts stemming from the law of conservation of protoplasmic mass. Simulation results show that this robot exhibits highly supple and adaptive locomotion without relying on any hierarchical structure. The results obtained are expected to shed new light on design methodology for autonomous decentralized control system.

An Amoeboid Locomotion That Exploits Real-Time Tunable Springs and Law of Conservation of Protoplasmic Mass

The control and mechanical systems of an embodied agent should be tightly coupled so as to emerge useful functionalities such as adaptivity. This indicates that the mechanical system as well as the control system should be responsible for a certain amount of computation for generating the behavior. However, there still leaves much to be understood about how such “computational offloading” from the control system to the mechanical system can be achieved. In order to intensively investigate this, here we particularly focus on the “softness” of the body, and show how the computational offloading derived from this property is exploited to simplify the control system and to increase the degree of adaptivity. To this end, we employ a two-dimensional amoeboid robot as a practical example, consisting of incompressive fluid (i.e. protoplasm) covered with an outer skin composed of a network of real-time tunable springs. Preliminary simulation results show that the exploitation of the “long-distant interaction” stemming from “the law of conservation of protoplasmic mass” allows us to simplify the control mechanism; and that adaptive amoeboid locomotion can be realized without the need of a central controller. The results obtained are expected to shed light on how control and mechanical systems should be coupled, and what the “brain-body-interaction” carefully designed brings to the resulting behavior.

Development of a Real-Time Tunable Spring - Toward Independent Control of Position and Stiffness of Joints -

Traditionally, robot control has been done typically by “highly precise control algorithms”: their joint angle trajectories are accurately determined at any time with vast amount of computation. This, however, causes serious problems, particularly in terms of adaptability and energy efficiency. On the other hand, an extreme approach has been gaining a lot of attention recently. A good instantiation is the passive dynamic walker, driven only by exploiting the intrinsic dynamics of its mechanical system. However, mechanical system is not everything as well as control system is not everything: “well-balanced” coupling between control and mechanical systems should be considered. In addition, the “meeting point” between the two systems should be varied according to the environment encountered. In light of these facts, this study particularly focuses on the stiffness of robots’ joints, since this strongly contributes to tuning the dominance relationship between control and mechanical systems. More specifically, the aim of this study is to develop a “Real-time tunable spring” that can smoothly change its elasticity without changing its natural length, allowing robot’s joints to change their position and stiffness independently.