Fluid-filled Soft-bodied Amoeboid Robot Inspired by Plasmodium of True Slime Mold

This paper presents a fluid-filled soft-bodied amoeboid robot inspired by plasmodium of true slime mold. The significant features of this robot are twofold: (1) the robot has fluid circuit (i.e., cylinders and nylon tubes filled with fluid) and truly soft and deformable body stemming from Real-time Tunable Springs (RTSs), the former seals protoplasm to induce global physical interaction between the body parts and the latter is used for elastic actuators; and (2) a fully decentralized control using coupled oscillators with completely local sensory feedback mechanism is realized by exploiting the global physical interaction between the body parts stemming from the fluid circuit. The experimental results show that this robot exhibits adaptive locomotion without relying on any hierarchical structure. The results obtained are expected to shed new light on design scheme for autonomous decentralized control systems

Modular soft pneumatic actuator system design for compliance matching

The future of robotics is personal. Never before has technology been as pervasive as it is today, with advanced mobile electronics hardware and multi-level network connectivity pushing âsmartâ devices deeper into our daily lives through home automation systems, virtual assistants, and wearable activity monitoring. As the suite of personal technology around us continues to grow in this way, augmenting and offloading the burden of routine activities of daily living, the notion that this trend will extend to robotics seems inevitable. Transitioning robots from their current principal domain of industrial factory settings to domestic, workplace, or public environments is not simply a matter of relocation or reprogramming, however. The key differences between âtraditionalâ types of robots and those which would best serve personal, proximal, human interactive applications demand a new approach to their design. Chief among these are requirements for safety, adaptability, reliability, reconfigurability, and to a more practical extent, usability. These properties frame the context and objectives of my thesis work, which seeks to provide solutions and answers to not only how these features might be achieved in personal robotic systems, but as well what benefits they can afford. I approach the investigation of these questions from a perspective of compliance matching of hardware systems to their applications, by providing methods to achieve mechanical attributes complimentary to their environment and end-use. These features are fundamental to the burgeoning field of Soft Robotics, wherein flexible, compliant materials are used as the basis for the structure, actuation, sensing, and control of complete robotic systems. Combined with pressurized air as a power source, soft pneumatic actuator (SPA) based systems offers new and novel methods of exploiting the intrinsic compliance of soft material components in robotic systems. While this strategy seems to answer many of the needs for human-safe robotic applications, it also brings new questions and challenges: What are the needs and applications personal robots may best serve? Are soft pneumatic actuators capable of these tasks, or âusefulâ work output and performance? How can SPA based systems be applied to provide complex functionality needed for operation in diverse, real-world environments? What are the theoretical and practical challenges in implementing scalable, multiple degrees of freedom systems, and how can they be overcome? I present solutions to these problems in my thesis work, elucidated through scientific design, testing and evaluation of robotic prototypes which leverage and demonstrate three key features: 1) Intrinsic compliance: provided by passive elastic and flexible component material properties, 2) Extrinsic compliance: rendered through high number of independent, controllable degrees of freedom, and 3) Complementary design: exhibited by modular, plug and play architectures which combine both attributes to achieve compliant systems. Through these core projects and others listed below I have been engaged in soft robotic technology, its application, and solutions to the challenges which are critical to providing a path forward within the soft robotics field, as well as for the future of personal robotics as a whole toward creating a better society

Opinions and Outlooks on Morphological Computation

Morphological Computation is based on the observation that biological systems seem to carry out relevant computations with their morphology (physical body) in order to successfully interact with their environments. This can be observed in a whole range of systems and at many different scales. It has been studied in animals – e.g., while running, the functionality of coping with impact and slight unevenness in the ground is "delivered" by the shape of the legs and the damped elasticity of the muscle-tendon system – and plants, but it has also been observed at the cellular and even at the molecular level – as seen, for example, in spontaneous self-assembly. The concept of morphological computation has served as an inspirational resource to build bio-inspired robots, design novel approaches for support systems in health care, implement computation with natural systems, but also in art and architecture. As a consequence, the field is highly interdisciplinary, which is also nicely reflected in the wide range of authors that are featured in this e-book. We have contributions from robotics, mechanical engineering, health, architecture, biology, philosophy, and others

Design for an Increasingly Protean Machine

Data-driven, rather than hypothesis-driven, approaches to robot design are becoming increasingly widespread, but they remain narrowly focused on tuning the parameters of control software (neural network synaptic weights) inside an overwhelmingly static and presupposed body. Meanwhile, an efflorescence of new actuators and metamaterials continue to broaden the ways in which machines are free to move and morph, but they have yet to be adopted by useful robots because the design and control of metamorphosing body plans is extremely non-intuitive. This thesis unites these converging yet previously segregated technologies by automating the design of robots with physically malleable hardware, which we will refer to as protean machines, named after Proteus of Greek mythology. This thesis begins by proposing an ontology of embodied agents, their physical features, and their potential ability to purposefully change each one in space and time. A series of experiments are then documented in which increasingly more of these features (structure, shape, and material properties) were allowed to vary across increasingly more timescales (evolution, development, and physiology), and collectively optimized to facilitate adaptive behavior in a simulated physical environment. The utility of increasingly protean machines is demonstrated by a concomitant increase in both the performance and robustness of the final, optimized system. This holds true even if its ability to change is temporarily removed by fabricating the system in reality, or by “canalization”: the tendency for plasticity to be supplanted by good static traits (an inductive bias) for the current environment. Further, if physical flexibility is retained rather than canalized, it is shown how protean machines can, under certain conditions, achieve a form of hyper-robustness: the ability to self-edit their own anatomy to “undo” large deviations from the environments in which their control policy was originally optimized. Some of the designs that evolved in simulation were manufactured in reality using hundreds of highly deformable silicone building blocks, yielding shapeshifting robots. Others were built entirely out of biological tissues, derived from pluripotent Xenopus laevis stem cells, yielding computer-designed organisms (dubbed “xenobots”). Overall, the results shed unique light on questions about the evolution of development, simulation-to-reality transfer of physical artifacts, and the capacity for bioengineering new organisms with useful functions

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

Neuro-musculoskeletal Models: A Tool to Study the Contribution of Muscle Dynamics to Biological Motor Control

Das Verständnis der Prinzipien, die menschlichen Bewegungen zugrunde liegen, ist die Basis für die Untersuchung der Entstehung gesunder Bewegungen und, was noch wichtiger ist, der Entstehung motorischer Störungen aufgrund neurodegenerativer Erkrankungen oder anderer pathologischer Zustände. Dieses Verständnis zu erlangen ist jedoch herausfordernd, da menschliche Bewegung das Ergebnis eines komplexen, dynamischen Zusammenspiels von biochemischen und biophysikalischen Prozessen im Bewegungsapparat und den hierarchisch organisierten neuronalen Kontrollstrukturen ist. Um die Wechselwirkungen dieser Strukturen zu untersuchen, bieten Computersimulationen, die mathematische Modelle des muskuloskelettalen Systems mit Modellen seiner neuronalen Kontrolle kombinieren, ein nützliches Werkzeug. In diesen Simulationen können einzelne Prozesse oder ganze Funktionseinheiten deaktiviert oder gestört werden, um die Auswirkungen dieser Veränderungen auf die vorhergesagten Bewegungen zu untersuchen. Die Plausibilität der zugrundeliegenden Modelle kann durch den Vergleich der Simulationen mit Daten aus Humanexperimenten und biologisch inspirierten Robotermodellen beurteilt werden. Das Ziel dieser Arbeit war es, neuro-muskuloskelettale Modelle als Hilfsmittel zur Untersuchung von Konzepten der biologischen Bewegungskontrolle zu verwenden. Von besonderem Interesse war der Beitrag der Muskeldynamik zur Kontrolle, d.h. wie die intrinsischen muskuloskelettalen Eigenschaften die motorische Kontrolle vereinfachen, ohne die motorische Genauigkeit zu beeinträchtigen. Zusätzlich wurde der Einfluss propriozeptiver Reflexmechanismen in verschiedenen Szenarien getestet. Die verwendeten neuro-muskuloskelettalen Modelle sind eine Kombination von Mehrkörpermodellen der Muskel-Skelett-Struktur des Armes oder des ganzen Körpers mit einem biologisch inspirierten hybriden Gleichgewichtspunkt-Kontrollmodell. In einer Simulationsstudie stellten wir fest, dass unser Armmodell realistische Reaktionen auf externe mechanische Störungen für zielgerichtete Bewegungen mit einem Freiheitsgrad vorhersagt. Auf dieser Grundlage simulierten wir die Anwendung von tragbaren Assistenzgeräten zur Kompensation unerwünschter Hypermetrie, d.h. einer überschießenden Reaktion bei zielgerichteten Bewegungen im Zusammenhang mit zerebellärer Ataxie und anderen neurodegenerativen Erkrankungen. Wir fanden heraus, dass einfache mechanische Hilfsmittel ausreichend sein können, um die Hypermetrien auf ein normales Niveau zu reduzieren. Wir stellten jedoch auch fest, dass die Größe des Drehmoments und der Kraft, die zur Kompensation der Störung erforderlich sind, möglicherweise deutlich unterschätzt wird, wenn die Muskel-Sehnen-Eigenschaften im Modell nicht berücksichtigt werden. Die Ergebnisse dieser beiden Studien bestätigten die Hypothese aus der Literatur, dass die Morphologie des Muskel-Skelett-Systems signifikant zur Bewegung beiträgt und somit deren Kontrolle vereinfacht. Deshalb haben wir einen informationstheoretischen Ansatz verwendet, um diesen Beitrag für zielgerichtete und oszillatorische Armbewegungen mit zwei Freiheitsgraden zu charakterisieren. Die Ergebnisse bestätigten, dass die unteren Kontrollebenen, einschließlich der Muskeln und ihrer Aktivierungsdynamik, wichtige Beiträge zur gesamten Kontrollhierarchie leisten. Beispielsweise führt ein einfaches, stückweise konstantes Muskelstimulationssignal, das nur wenig Information enthält, zu einer geschmeidigen Bewegung. Der physiologische Detailgrad, der in unseren Muskel-Skelett-Modellen enthalten ist, ermöglicht nicht nur die Untersuchung von Theorien zur motorischen Kontrolle, sondern auch die Untersuchung von Größen wie inneren Kräften in Muskeln und Gelenken, die experimentell normalerweise nicht zugänglich sind. Diese Größen sind zum Beispiel in der Ergonomie und für die Entwicklung von Assistenzgeräten von Bedeutung. In einer Ganzkörpersimulationsstudie untersuchten wir den Beitrag des Dehnungsreflexes zu den resultierenden Muskelkräften bei einer aktiven externen Repositionierung des Hüftgelenkes für einen großen Bereich von Bewegungsgeschwindigkeiten. Wir fanden heraus, dass der relative Kraftbeitrag des Feedback-Mechanismus vom modellierten kognitiven Zustand abhängig ist und einen nicht vernachlässigbaren Beitrag leistet, insbesondere bei hohen Repositionsgeschwindigkeiten. Die Gesamtheit unserer Ergebnisse zeigt, dass die Eigenschaften des Bewegungsapparates signifikant zur Erzeugung und Kontrolle von Bewegung beitragen und es daher wichtig ist, sie bei der Modellierung der menschlichen Bewegung zu berücksichtigen. Daher sprechen die Ergebnisse für die Kombination eines physiologisch fundierten biomechanischen und biochemischen Modells des Bewegungsapparates mit biologisch inspirierten Konzepten der motorischen Kontrolle. Diese Computersimulationen haben sich als ein nützliches Werkzeug zum Verständnis der Prozesse erwiesen, die der Erzeugung gesunder und pathologisch beeinträchtigter menschlicher Bewegungen zugrunde liegen.Understanding the principles underlying human movement is the basis for investigating the generation of healthy movements and, more importantly, the origins of motor disorders due to neurodegenerative diseases or other pathological conditions. However, gaining this understanding is challenging since human motion is the result of a complex, dynamic interplay of biochemical and biophysical processes in the musculoskeletal system and the hierarchically organized neuronal control structures. To study the interactions of these structures, computer simulations that combine mathematical models of the musculoskeletal system with models of its neuronal control provide a useful tool. In these simulations, single processes or whole functional units can be disabled or perturbed to study the effects of these changes on the predicted movements. The plausibility of the underlying models can be assessed by comparing the simulations with data from human experiments and biologically inspired robotic models. The purpose of this work was to use neuro-musculoskeletal models as tools to study concepts of biological motor control. Of particular interest was the contribution of muscle dynamics to the control, i.e. how the intrinsic musculoskeletal properties simplify motor control without compromising motor accuracy. Additionally, the influence of proprioceptive reflex mechanisms was tested in different scenarios. The neuro-musculoskeletal models that were used are a combination of multibody musculoskeletal models of the arm or the whole body with a biologically inspired hybrid equilibrium-point controller. In a simulation study, we found that our arm model predicts realistic reactions to external mechanical perturbations while performing one-degree-of-freedom goal-directed movements. Based on this, we simulated the application of wearable assistive devices to compensate for unwanted hypermetria, i.e. an overshooting response in goal-directed movements associated with cerebellar ataxia and other neurodegenerative disorders. We found that simple mechanical devices may be sufficient to reduce the hypermetria to a normal level. However, we also observed that the magnitude of torque and power that is required to compensate for the disorder may be significantly underestimated if muscle-tendon characteristics are not considered in the computational model. The results of these two studies confirmed the hypothesis from literature that the morphology of musculoskeletal systems significantly contributes to the movement and thus simplifies its control. Therefore, we made use of the information-theoretic approach of quantifying morphological computation to characterize this contribution for goal-directed and oscillatory arm movements with two degrees of freedom. The results asserted that the lower levels of control, including the muscles and their activation dynamics, make important contributions to the overall control hierarchy. For example, a simple piecewise constant muscle stimulation signal that contains only little information results in a smooth movement. The level of physiological detail that is included in our musculoskeletal models does not only allow for the examination of motor control theories but also makes it possible to study quantities like internal forces in muscles and joints, usually not experimentally accessible. These quantities are relevant, for example, in ergonomics and for the development of assistive devices. In a whole-body simulation study, we investigated the contribution of the stretch reflex to the resulting muscle forces during active external repositioning of the hip joint for a large range of movement velocities. We found that, depending on the modeled cognitive state, the relative force contribution of the feedback mechanism is not negligible, especially for high repositioning velocities. The entirety of our results shows that the properties of the musculoskeletal system significantly contribute to the generation and control of movement and, thus, it is important to take them into account when modeling human movement. Therefore, the results advocate the combination of a physiologically well-founded biomechanical and biochemical model of the musculoskeletal system with biologically inspired concepts of motor control. These computer simulations have proven to be a useful tool towards the comprehension of the processes underlying the generation of healthy and pathologically impaired human movements

A complex systems approach to education in Switzerland

The insights gained from the study of complex systems in biological, social, and engineered systems enables us not only to observe and understand, but also to actively design systems which will be capable of successfully coping with complex and dynamically changing situations. The methods and mindset required for this approach have been applied to educational systems with their diverse levels of scale and complexity. Based on the general case made by Yaneer Bar-Yam, this paper applies the complex systems approach to the educational system in Switzerland. It confirms that the complex systems approach is valid. Indeed, many recommendations made for the general case have already been implemented in the Swiss education system. To address existing problems and difficulties, further steps are recommended. This paper contributes to the further establishment complex systems approach by shedding light on an area which concerns us all, which is a frequent topic of discussion and dispute among politicians and the public, where billions of dollars have been spent without achieving the desired results, and where it is difficult to directly derive consequences from actions taken. The analysis of the education system's different levels, their complexity and scale will clarify how such a dynamic system should be approached, and how it can be guided towards the desired performance

Actual issues of modern development of socio-economic systems in terms of the COVID-19 pandemic

The entire world community, since 2019, affected by the global pandemic COVID-19. The pandemic caused by this virus, led not only to significant human losses worldwide, but also imposed significant restrictions on the socio-cultural life of the population and radically changed the trends of the global economy and the further functioning of socio-economic systems. Now, huge economic losses have been recorded, which affected almost all sectors of the national economy and the state in the short, medium and long term. However, it is important to consider individual economic development forecasts and measures developed by the governments of the world’s leading countries to overcome the negative effects of the COVID-19 pandemic. This will allow to form a real vision of the possible course of economic processes that will directly affect the living standards of the population and the restoration of socio-economic systems. To further restore the socio-economic system it is necessary to developing modern strategies and forecasts to ensure the effective functioning of economic entities through innovation, digitalization, marketing and use of competitive advantages in the consumer markets in conditions of limited resources, development promising sectors of the national economy, etc. The purpose of writing this scientific monograph is to substantiate the theoretical and methodological foundations, the formation new strategies for restoring socio-economic systems and overcoming the negative consequences of the caused by the COVID-19 pandemic, taking into account changes and challenges in the modern world. The object of the authors’ research is the process of forming new approaches, strategies and mechanisms for managing socio-economic systems in the context of the COVID-19 pandemic, eliminating the negative consequences in the activities of economic entities. The subject of research is socio-economic, organizational and institutional processes of formation and effective implementation of approaches, strategies and mechanisms for managing socio-economic systems; stabilization of the functioning of economic entities; introduction of innovative processes and digital technologies; implementation of best practices in the managing of socio-economic systems using world experience in various sectors of the economy caused by the COVID-19 pandemic