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

The role of feedback in morphological computation with compliant bodies

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 etal. (Biol Cybern 105:355-370, doi: 10.1007/s00422-012-0471-0 , 2012). 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 organism

Towards a theoretical foundation for morphological computation with compliant bodies

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 functio

Towards a theoretical foundation for morphological computation with compliant bodies

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

Employing L-systems to generate mass-spring networks for morphological computing

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

Thermal Stability and Material Balance of Nanomaterials in Waste Incineration

Nanostructured materials are widely used to improve the properties of consumer products such as tires, cosmetics, light weight equipment etc. Due to their complex composition these products are hardly recycled and thermal treatment is preferred. In this study we investigated the thermal stability and material balance of nanostructured metal oxides in flames and in an industrial waste incinerator. We studied the size distribution of nanostructured metal oxides (CeO₂, TiO₂, SiO₂) in a flame reactor and in a heated reaction tube. In the premixed ethylene/air flame, nano-structured CeO₂ partly evaporates forming a new particle mode. This is probably due to chemical reactions in the flame. In addition sintering of agglomerates takes place in the flame. In the electrically heated reaction tube however only sintering of the agglomerated nanomaterials is observed. Ceria has a low background in waste incinerators and is therefore a suitable tracer for investigating the fate of nanostructured materials. Low concentrations of Ceria were introduced by a two-phase nozzle into the post-combustion zone of a waste incinerator. By the incineration of coal dust in a burning chamber the Ceria nanoparticles are mainly found in the size range of the fly ash (1 – 10 µm) because of agglomeration. With gas as a fuel less agglomeration was observed and the Ceria nanoparticles were in the particle size range below 1 µm