49 research outputs found

    Design of artificial neural oscillatory circuits for the control of lamprey- and salamander-like locomotion using evolutionary algorithms

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    This dissertation investigates the evolutionary design of oscillatory artificial neural networks for the control of animal-like locomotion. It is inspired by the neural organ¬ isation of locomotor circuitries in vertebrates, and explores in particular the control of undulatory swimming and walking. The difficulty with designing such controllers is to find mechanisms which can transform commands concerning the direction and the speed of motion into the multiple rhythmic signals sent to the multiple actuators typically involved in animal-like locomotion. In vertebrates, such control mechanisms are provided by central pattern generators which are neural circuits capable of pro¬ ducing the patterns of oscillations necessary for locomotion without oscillatory input from higher control centres or from sensory feedback. This thesis explores the space of possible neural configurations for the control of undulatory locomotion, and addresses the problem of how biologically plausible neural controllers can be automatically generated.Evolutionary algorithms are used to design connectionist models of central pattern generators for the motion of simulated lampreys and salamanders. This work is inspired by Ekeberg's neuronal and mechanical simulation of the lamprey [Ekeberg 93]. The first part of the thesis consists of developing alternative neural controllers for a similar mechanical simulation. Using a genetic algorithm and an incremental approach, a variety of controllers other than the biological configuration are successfully developed which can control swimming with at least the same efficiency. The same method is then used to generate synaptic weights for a controller which has the observed biological connectivity in order to illustrate how the genetic algorithm could be used for developing neurobiological models. Biologically plausible controllers are evolved which better fit physiological observations than Ekeberg's hand-crafted model. Finally, in collaboration with Jerome Kodjabachian, swimming controllers are designed using a developmental encoding scheme, in which developmental programs are evolved which determine how neurons divide and get connected to each other on a two-dimensional substrate.The second part of this dissertation examines the control of salamander-like swimming and trotting. Salamanders swim like lampreys but, on the ground, they switch to a trotting gait in which the trunk performs a standing wave with the nodes at the girdles. Little is known about the locomotion circuitry of the salamander, but neurobiologists have hypothesised that it is based on a lamprey-like organisation. A mechanical sim¬ ulation of a salamander-like animat is developed, and neural controllers capable of exhibiting the two types of gaits are evolved. The controllers are made of two neural oscillators projecting to the limb motoneurons and to lamprey-like trunk circuitry. By modulating the tonic input applied to the networks, the type of gait, the speed and the direction of motion can be varied.By developing neural controllers for lamprey- and salamander-like locomotion, this thesis provides insights into the biological control of undulatory swimming and walking, and shows how evolutionary algorithms can be used for developing neurobiological models and for generating neural controllers for locomotion. Such a method could potentially be used for designing controllers for swimming or walking robots, for instance

    Evolutionary robotics and neuroscience

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    The Effect of Proprioceptive Feedback on the Distribution of Sensory Information in a Model of an Undulatory Organism

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    In an animal, a crucial factor concerning the arrival of information at the sensors and subsequent transmission to the effectors, is how it is distributed. At the same time, higher animals also employ proprioceptive feedback so that their respective neural circuits have information regarding the state of the animal body. In order to disseminate what this practically means for the distribution of sensory information, we have modeled a segmented swimming organism (animat) coevolving its nervous system and body plan morphology. In a simulated aquatic environment, we find that animats artificially endowed with proprioceptive feedback are able to evolve completely decoupled central pattern generators (CPGs) meaning that they emerge without any connections made to neural circuits in adjacent body segments. Without such feedback however, we also find that the distribution of sensory information from the head of the animat becomes far more important, with adjacent CPG circuits becoming interconnected. Crucially, this demonstrates that where proprioceptive mechanisms are lacking, more effective delivery of sensory input is essential

    Biologically inspired neural controllers for motor control in a quadruped robot

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    A simulation model of the locomotion controllers for the nematode Caenorhabditis elegans

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    This paper presents a simple yet biologicallygrounded model of the C. elegans neural circuit for forward locomotive control. The model considers a limited subset of the C. elegans nervous system, within a minimal two-dimensional environment. Despite its reductionist approach, this model is sufficiently rich to generate patterns of undulations that are reminiscent of the biological worm’s behaviour and qualitatively similar to patterns which have been shown to generate locomotion in a model of a richer physical environment. Interestingly, and contrary to conventional wisdom about neural circuits for motor control, our results are consistent with the conjecture that the worm may be relying on feedback from the shape of its body to generate undulations that propel it forward or backward
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