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      Peristaltic Waves as Optimal Gaits in Metameric Bio-Inspired Robots

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          Abstract

          Peristalsis, i.e., a motion pattern arising from the propagation of muscle contraction and expansion waves along the body, is a common locomotion strategy for limbless animals. Mimicking peristalsis in bio-inspired robots has attracted considerable attention in the literature. It has recently been observed that maximal velocity in a metameric earthworm-like robot is achieved by actuating the segments using a “phase coordination” principle. This paper shows that, in fact, peristalsis (which requires not only phase coordination, but also that all segments oscillate at same frequency and amplitude) emerges from optimization principles. More precisely, basing our analysis on the assumption of small deformations, we show that peristaltic waves provide the optimal actuation solution in the ideal case of a periodic infinite system, and that this is approximately true, modulo edge effects, for the real, finite length system. Therefore, this paper confirms the effectiveness of mimicking peristalsis in bio-inspired robots, at least in the small-deformation regime. Further research will be required to test the effectiveness of this strategy if large deformations are allowed.

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          Most cited references27

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          Central pattern generators for locomotion control in animals and robots: a review.

          The problem of controlling locomotion is an area in which neuroscience and robotics can fruitfully interact. In this article, I will review research carried out on locomotor central pattern generators (CPGs), i.e. neural circuits capable of producing coordinated patterns of high-dimensional rhythmic output signals while receiving only simple, low-dimensional, input signals. The review will first cover neurobiological observations concerning locomotor CPGs and their numerical modelling, with a special focus on vertebrates. It will then cover how CPG models implemented as neural networks or systems of coupled oscillators can be used in robotics for controlling the locomotion of articulated robots. The review also presents how robots can be used as scientific tools to obtain a better understanding of the functioning of biological CPGs. Finally, various methods for designing CPGs to control specific modes of locomotion will be briefly reviewed. In this process, I will discuss different types of CPG models, the pros and cons of using CPGs with robots, and the pros and cons of using robots as scientific tools. Open research topics both in biology and in robotics will also be discussed.
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            Central pattern generators and the control of rhythmic movements.

            Central pattern generators are neuronal circuits that when activated can produce rhythmic motor patterns such as walking, breathing, flying, and swimming in the absence of sensory or descending inputs that carry specific timing information. General principles of the organization of these circuits and their control by higher brain centers have come from the study of smaller circuits found in invertebrates. Recent work on vertebrates highlights the importance of neuro-modulatory control pathways in enabling spinal cord and brain stem circuits to generate meaningful motor patterns. Because rhythmic motor patterns are easily quantified and studied, central pattern generators will provide important testing grounds for understanding the effects of numerous genetic mutations on behavior. Moreover, further understanding of the modulation of spinal cord circuitry used in rhythmic behaviors should facilitate the development of new treatments to enhance recovery after spinal cord damage.
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              Biological pattern generation: the cellular and computational logic of networks in motion.

              In 1900, Ramón y Cajal advanced the neuron doctrine, defining the neuron as the fundamental signaling unit of the nervous system. Over a century later, neurobiologists address the circuit doctrine: the logic of the core units of neuronal circuitry that control animal behavior. These are circuits that can be called into action for perceptual, conceptual, and motor tasks, and we now need to understand whether there are coherent and overriding principles that govern the design and function of these modules. The discovery of central motor programs has provided crucial insight into the logic of one prototypic set of neural circuits: those that generate motor patterns. In this review, I discuss the mode of operation of these pattern generator networks and consider the neural mechanisms through which they are selected and activated. In addition, I will outline the utility of computational models in analysis of the dynamic actions of these motor networks.
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                Author and article information

                Contributors
                Journal
                Front Robot AI
                Front Robot AI
                Front. Robot. AI
                Frontiers in Robotics and AI
                Frontiers Media S.A.
                2296-9144
                05 September 2018
                2018
                : 5
                : 99
                Affiliations
                [1] 1International School for Advanced Studies (SISSA) , Trieste, Italy
                [2] 2Centre de Mathématiques Appliquées, École Polytéchnique, Université Paris-Saclay , Paris, France
                [3] 3The BioRobotics Institute, Sant'Anna School for Advanced Studies , Pisa, Italy
                Author notes

                Edited by: Matteo Cianchetti, Scuola Sant'Anna di Studi Avanzati, Italy

                Reviewed by: Shinya Aoi, Kyoto University, Japan; Barbara Mazzolai, Fondazione Istituto Italiano di Technologia, Italy

                *Correspondence: Antonio DeSimone desimone@ 123456sissa.it

                This article was submitted to Soft Robotics, a section of the journal Frontiers in Robotics and AI

                Article
                10.3389/frobt.2018.00099
                7806059
                0da5560f-59cc-4b6f-bbc0-cdeed0a0cd2d
                Copyright © 2018 Agostinelli, Alouges and DeSimone.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 15 April 2018
                : 31 July 2018
                Page count
                Figures: 11, Tables: 0, Equations: 122, References: 27, Pages: 15, Words: 6657
                Funding
                Funded by: European Research Council 10.13039/501100000781
                Award ID: MicroMotility - 340685
                Categories
                Robotics and AI
                Original Research

                crawling motility,lumbricus terrestris,peristalsis,self-propulsion,metameric robots,biomimetic robots,soft robotics,optimization

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