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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. [ABSTRACT FROM AUTHOR]

An introduction to the journal is presented in which the editor discusses various reports within the issue on topics including formalization of the concept of morphological computation, the influence of morphology on locomotion, and the link of emotions with changes in morphology.

Anthropomimetic robotics differs from conventional approaches by capitalizing on the replication of the inner structures of the human body, such as muscles, tendons, bones, and joints. Here we present our results of more than three years of research in constructing, simulating, and, most importantly, controlling anthropomimetic robots. We manufactured four physical torsos, each more complex than its predecessor, and developed the tools required to simulate their behavior. Furthermore, six different control approaches, inspired by classical control theory, machine learning, and neuroscience, were developed and evaluated via these simulations or in small-scale setups. While the obtained results are encouraging, we are aware that we have barely exploited the potential of the anthropomimetic design so far. But, with the tools developed, we are confident that this novel approach will contribute to our understanding of morphological computation and human motor control in the future. [ABSTRACT FROM AUTHOR]

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. (Biol Cybern 105:355-370, doi:, ). 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. [ABSTRACT FROM AUTHOR]

The decay in structure size of manufacturing products has yielded new demands on spontaneous composition methods. The key for the realization of small-sized robots lies in how to achieve the efficient assembly sequence in a bottom-up manner, where most of the parts have only limited (or no) computational (i.e. deliberative) abilities. In this paper, based on a novel self-assembly platform consisting of self-propulsive centimetre-sized modules capable of aggregation on the surface of water, we study the effect of stochasticity and morphology (shape) on the yield of targeted formations in self-assembly processes. Specifically, we focus on a unique phenomenon: that a number of modules instantly compose a target product without forming intermediate subassemblies, some of which constitute undesired geometrical formations (termed one-shot aggregation). Together with a focus on the role that the morphology of the modules plays, we validate the effect of one-shot aggregation with a kinetic rate mathematical model. Moreover, we examined the degree of parallelism of the assembly process, which is an essential factor in self-assembly, but is not systematically taken into account by existing frameworks. [ABSTRACT FROM AUTHOR]

How is our body imprinted in our brain? This seemingly simple question is a subject of investigations of diverse disciplines, psychology, and philosophy originally complemented by neurosciences more recently. Despite substantial efforts, the mysteries of body representations are far from uncovered. The most widely used notions—body image and body schema—are still waiting to be clearly defined. The mechanisms that underlie body representations are coresponsible for the admiring capabilities that humans or many mammals can display: combining information from multiple sensory modalities, controlling their complex bodies, adapting to growth, failures, or using tools. These features are also desirable in robots. This paper surveys the body representations in biology from a functional or computational perspective to set ground for a review of the concept of body schema in robotics. First, we examine application-oriented research: how a robot can improve its capabilities by being able to automatically synthesize, extend, or adapt a model of its body. Second, we summarize the research area in which robots are used as tools to verify hypotheses on the mechanisms underlying biological body representations. We identify trends in these research areas and propose future research directions. [ABSTRACT FROM PUBLISHER]

Abstract: Traditionally, in robotics, artificial intelligence and neuroscience, there has been a focus on the study of the control or the neural system itself. Recently there has been an increasing interest in the notion of embodiment not only in robotics and artificial intelligence, but also in the neurosciences, psychology and philosophy. In this paper, we introduce the notion of morphological computation, and demonstrate how it can be exploited on the one hand for designing intelligent, adaptive robotic systems, and on the other hand for understanding natural systems. While embodiment has often been used in its trivial meaning, i.e. “intelligence requires a body”, the concept has deeper and more important implications, concerned with the relation between physical and information (neural, control) processes. Morphological computation is about connecting body, brain and environment. A number of case studies are presented to illustrate the concept. We conclude with some speculations about potential lessons for neuroscience and robotics. [Copyright &y& Elsevier]

New robotics is an approach to robotics that, in contrast to traditional robotics, employs ideas and principles from biology. While in the traditional approach there are generally accepted methods (e. g., from control theory), designing agents in the new robotics approach is still largely considered an art. In recent years, we have been developing a set of heuristics, or design principles, that on the one hand capture theoretical insights about intelligent (adaptive) behavior, and on the other provide guidance in actually designing and building systems. In this article we provide an overview of all the principles but focus on the principles of ecological balance, which concerns the relation between environment, morphology, materials, and control, and sensory-motor coordination, which concerns self-generated sensory stimulation as the agent interacts with the environment and which is a key to the development of high-level intelligence. As we argue, artificial evolution together with morphogenesis is not only "nice to have" but is in fact a necessary tool for designing embodied agents. [ABSTRACT FROM AUTHOR]

Developmental robotics is an emerging field located at the intersection of robotics, cognitive science and developmental sciences. This paper elucidates the main reasons and key motivations behind the convergence of fields with seemingly disparate interests, and shows why developmental robotics might prove to be beneficial for all fields involved. The methodology advocated is synthetic and two-pronged: on the one hand, it employs robots to instantiate models originating from developmental sciences; on the other hand, it aims to develop better robotic systems by exploiting insights gained from studies on ontogenetic development. This paper gives a survey of the relevant research issues and points to some future research directions. [ABSTRACT FROM AUTHOR]

Abstract: Many different animal species rely on whiskers for a variety of tasks. Among the most basic are obstacle avoidance and wall-following. We show that fast and reliable evaluation of distances can be greatly improved by an appropriate sensory morphology that matches the physical space of the agent. To investigate morphologies and material properties of whiskers, we conduct experiments both on a real robot and in simulation using artificial evolution. We find that the morphology that is most successful at following a wall strongly resembles the morphologies of natural whiskers. This can be better understood by considering the relation of the agent body to its tactile sensing range, as well as the challenges of various tasks faced by agents endowed with different sensory modalities. [Copyright &y& Elsevier]