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Keynote lecture, Today, the concept of morphological computation, i.e. the idea that the control of a system is at least partially embodied in its functional physical or chemical dynamics, has become a well - established approach in robotics. Novel designs that exhibit robust behavior and adaptability result from a blurring of the distinction between hard- and software. Such designs are often inspired by biology: Not only by the means (i.e. materials) of nature but also by the ways (organizational principles) nature employs. Remarkably, morphological control connects technology and biology in a bi – directional manner. We apply the concepts of morphological control in order to support, complement and substitute physiological processes in medical problem settings. Thereby, we exploit the ideas of morphological control in systems on different length scales and governed by classical as well as statistical mechanics. In a first group of investigations, we aim at the implementation of an inflatable support system for patients with movement impairments. Quite often, the loss of the ability to control one’s movements is interpreted as a decrease of the computational power of neural system. Based on experimental evidence, we hypothesize that at least in some cases neural control is still at its full power. But due to changes of the mechanical properties of the aging body, the control problem has become more difficult, i.e. the body experiences a decrease of its morphological control power. By the use of inflatable exoskeletal devices, we aspire to influence the mechanical properties of the body in such a manner that morphological control is re – established. The inflatable structures we employ are based on the “tensairity” principle. Recent research demonstrated the feasibility of actuated soft structures based on tenairity. In that sense, soft robotics meets morphological control in the medical field. On the microscopic level, we focus on cell – dynamics. We assume the cell as a system tha

This book is published jointly by the editors Helmut Hauser, Rudolf M. Füchslin and Rolf Pfeifer. It is a free ebook and distribution is encouraged., 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. On one hand, the beautiful richness of this interdisciplinarity has a lot of potential, but on the other, it poses a number of serious challenges. For example, people with different backgrounds have a different understanding of the concepts involved. They use different terms for the same ideas or, even more problematic, they use the same terms to mean something often substantially different. Also, the tools and methods are frequently quite apart, as illustrated, e.g., by engineering and neuroscience. Nevertheless, we strongly believe that this interdisciplinarity is a big opportunity, which enables the field to grow and to cross-fertilize. Scientists from other areas can provide novel points of view, they can challenge long standing, many times implicit and unquestioned assumptions inherent to a field, and th

Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch), The control of compliant robots is, due to their often nonlinear and complex dynamics, inherently difficult. The vision of morphological computation proposes to view these aspects not only as problems, but rather also as parts of the solution. Non-rigid body parts are not seen anymore as imperfect realizations of rigid body parts, but rather as potential computational resources. The applicability of this vision has already been demonstrated for a variety of complex robot control problems. Nevertheless, a theoretical basis for understanding the capabilities and limitations of morphological computation has been missing so far. We present a model for morphological computation with compliant bodies, where a precise mathematical characterization of the potential computational contribution of a complex physical body is feasible. The theory suggests that complexity and nonlinearity, typically unwanted properties of robots, are desired features in order to provide computational power. We demonstrate that simple generic models of physical bodies, based on mass-spring systems, can be used to implement complex nonlinear operators. By adding a simple readout (which is static and linear) to the morphology such devices are able to emulate complex mappings of input to output streams in continuous time. Hence, by outsourcing parts of the computation to the physical body, the difficult problem of learning to control a complex body, could be reduced to a simple and perspicuous learning task, which can not get stuck in local minima of an error function.

Erworben im Rahmen der Schweizer Nationallizenzen (www.nationallizenzen.ch), The generation of robust periodic movements of complex nonlinear robotic systems is inherently difficult, especially, if parts of the robots are compliant. It has previously been proposed that complex nonlinear features of a robot, similarly as in biological organisms, might possibly facilitate its control. This bold hypothesis, commonly referred to as morphological computation, has recently received some theoretical support by Hauser et al. We show in this article that this theoretical support can be extended to cover not only the case of fading memory responses to external signals, but also the essential case of autonomous generation of adaptive periodic patterns, as, e.g., needed for locomotion. The theory predicts that feedback into the morphological computing system is necessary and sufficient for such tasks, for which a fading memory is insufficient. We demonstrate the viability of this theoretical analysis through computer simulations of complex nonlinear mass-spring systems that are trained to generate a large diversity of periodic movements by adapting the weights of a simple linear feedback device. Hence, the results of this article substantially enlarge the theoretically tractable application domain of morphological computation in robotics, and also provide new paradigms for understanding control principles of biological organisms.

Designing robots for applications in space flight requires a different prioritization of design criteria than for systems operating on Earth. In this article, we argue that the field of soft robotics offers novel approaches meeting the specific requirements of space flight. We present one especially promising construction principle, so called Tensairity, in some detail. Tensairity, as the name suggests, takes ideas from Tensegrity, but uses inflatable structures instead of cables and struts. Soft robots pose substantial challenges with respect to control. One way to meet these challenges is given by the concept of morphological computation and control. Morphological computation can be loosely defined as the exploitation of the shape, material properties, and dynamics of a physical system to improve the efficiency of computation and to deal with systems for which it is difficult to construct a virtual representation using a kinematic model. We discuss fundamental aspects of morphological control and their relevance for space flight. Besides low weight, small consumption of space in the inactive state and advantageous properties with respect to intrinsic safety and energy consumption, we discuss how the blurring of the discrimination of hard- and software leads to control strategies that require only very little and very simple electronic circuitry (which is beneficial in an environment with high irradiation). Finally, we present a research strategy that bundles activities in space flight with research and development in medicine, especially for support systems for an aging population, that are faced with similar morphological computing challenges to astronauts. Such a combination meets the demands for research that is not only effective, but also efficient with respect to economic resources.

Morphological computation can be loosely defined as the exploitation of the shape, material properties, and physical dynamics of a physical system to improve the efficiency of a computation. Morphological control is the application of morphological computing to a control task. In its theoretical part, this article sharpens and extends these definitions by suggesting new formalized definitions and identifying areas in which the definitions we propose are still inadequate. We go on to describe three ongoing studies, in which we are applying morphological control to problems in medicine and in chemistry. The first involves an inflatable support system for patients with impaired movement, and is based on macroscopic physics and concepts already tested in robotics. The two other case studies (self-assembly of chemical microreactors; models of induced cell repair in radio-oncology) describe processes and devices on the micrometer scale, in which the emergent dynamics of the underlying physical system (e.g., phase transitions) are dominated by stochastic processes such as diffusion.

Robot arms equipped with an additional network of masses and springs enable a facilitation of control by the exploitation of morphological properties. Typically, these mass-spring networks are being generated randomly. This approach comes in its basic form unhandy when the network should obey specific constraints, such as spring lengths, angles between springs or, e.g., the physical expansion range of the network. We present an approach of emulating a growth process on the basis of L-systems. Therefore, we have developed a simulation environment to define L-systems and instructions to translate the produced strings into mass-spring networks.