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Background: Minimally invasive surgery attracts more and more attention because of the advantages of minimal trauma, less bleeding and pain and low complication rate. However, minimally invasive surgery for beating hearts is still a challenge. Our goal is to develop a soft robot surgical system for single-port minimally invasive surgery on a beating heart.Materials and Methods: The soft robot described in this paper is inspired by the octopus arm. Although the octopus arm is soft and has more degrees of freedom (DOFs), it can be controlled flexibly. The soft robot is driven by cables that are embedded into the soft robot manipulator and can control the direction of the end and middle of the soft robot manipulator. The forward, backward and rotation movement of the soft robot is driven by a propulsion plant. The soft robot can move freely by properly controlling the cables and the propulsion plant. The soft surgical robot system can perform different thoracic operations by changing surgical instruments. To evaluate the flexibility, controllability and reachability of the designed soft robot surgical system, some testing experiments have been conducted in vivo on a swine.Results: Through the subxiphoid, the soft robot manipulator could enter into the thoracic cavity and pericardial cavity smoothly and perform some operations such as biopsy, ligation and ablation. The operations were performed successfully and did not cause any damage to the surrounding soft tissues. From the experiments, the flexibility, controllability and reachability of the soft robot surgical system have been verified. Also, it has been shown that this system can be used in the thoracic and pericardial cavity for different operations.Conclusions: Compared with other endoscopy robots, the soft robot surgical system is safer, has more DOFs and is more flexible for control. When performing operations in a beating heart, this system maybe more suitable than traditional endoscopy robots. [ABSTRACT FROM AUTHOR]

In mammals, the development of reflexes is often regarded as an innate process. However, recent findings show that fetuses are endowed with favorable conditions for ontogenetic development. In this article, we hypothesize that the circuitry of at least some mammalian reflexes can be self-organized from the sensory and motor interactions brought forth in a musculoskeletal system. We focus mainly on three reflexes: the myotatic reflex, the reciprocal inhibition reflex, and the reverse myotatic reflex. To test our hypothesis, we conducted a set of experiments on a simulated musculoskeletal system using pairs of agonist and antagonist muscles. The reflex connectivity is obtained by producing spontaneous motor activity in each muscle and by correlating the resulting sensor and motor signals. Our results show that, under biologically plausible conditions, the reflex circuitry thus obtained is consistent with that identified in relation to the analogous mammalian reflexes. In addition, they show that the reflex connectivity obtained depends on the morphology of the musculoskeletal system as well as on the environment that it is embedded in. [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 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. [ABSTRACT FROM AUTHOR]

The last two decades in the field of artificial intelligence have clearly shown that true intelligence always requires the interaction of an agent with a real physical and social environment. The concept of embodiment that has been introduced to designate the modern approach to designing intelligence has far-reaching implications. Rather than studying computation alone, we must consider the interplay between morphology, materials, brain (control), and the environment. A number of case studies are presented, and it is demonstrated how artificial evolution and morphogenesis can be used to systematically investigate this interplay. Taking these ideas into account requires entirely novel ways of thinking, and often leads to surprising results. [ABSTRACT FROM AUTHOR]

'Produktlinienanalyse' (PLA) and life cycle assessment are analytical approaches which are used as instruments to survey the life cycle of a product, but whose main purpose can be viewed as being the optimization of this life cycle. The lesser known instrument of PLA includes an appraisal of product utility, and assesses the life cycle not only according to environmental, but also according to economic and social impacts. Moreover, PLA involves the agents relevance to the life cycle. This case study, a comparison between filament lamps and compact fluorescent lamps, shows that the purely environmental perspective is insufficient and omits a series of relevant criteria. It illustrates that additional social and economic parameters, and the examination of the utility of a product, have a great impact upon this comparison. The method of product system improvement with agent cooperation is put forward as a technique for the transposition of the results into concrete action. This study was financed from own funds of the Öko-Institut e.V., Freiburg. [ABSTRACT FROM AUTHOR]

Building artificial lifelike autonomous agents is still considered an art, rather than a science. A generally accepted precise methodology is missing, and—given the properties of the real world—it is doubtful whether such a methodology will ever be developed. Nevertheless, it is possible to define criteria and provide heuristics for good designs. We have developed a number of design principles which, when applied, lead to what we would consider good designs from a cognitive science or artificial life (ALife) perspective. The paper illustrates some of these principles using a case study of classification. [ABSTRACT FROM AUTHOR]

Soft machines have recently gained prominence due to their inherent softness and the resulting safety and resilience in applications. However, these machines also have disadvantages, as they respond with complex body dynamics when stimulated. These dynamics exhibit a variety of properties, including nonlinearity, memory, and potentially infinitely many degrees of freedom, which are often difficult to control. Here, we demonstrate that these seemingly undesirable properties can in fact be assets that can be exploited for real-time computation. Using body dynamics generated from a soft silicone arm, we show that they can be employed to emulate desired nonlinear dynamical systems. First, by using benchmark tasks, we demonstrate that the nonlinearity and memory within the body dynamics can increase the computational performance. Second, we characterize our system's computational capability by comparing its task performance with a standard machine learning technique and identify its range of validity and limitation. Our results suggest that soft bodies are not only impressive in their deformability and flexibility but can also be potentially used as computational resources on top and for free. [ABSTRACT FROM AUTHOR]