1,992 research outputs found

    Evolutionary robotics and neuroscience

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    Evolution of central pattern generators for the control of a five-link bipedal walking mechanism

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    Central pattern generators (CPGs), with a basis is neurophysiological studies, are a type of neural network for the generation of rhythmic motion. While CPGs are being increasingly used in robot control, most applications are hand-tuned for a specific task and it is acknowledged in the field that generic methods and design principles for creating individual networks for a given task are lacking. This study presents an approach where the connectivity and oscillatory parameters of a CPG network are determined by an evolutionary algorithm with fitness evaluations in a realistic simulation with accurate physics. We apply this technique to a five-link planar walking mechanism to demonstrate its feasibility and performance. In addition, to see whether results from simulation can be acceptably transferred to real robot hardware, the best evolved CPG network is also tested on a real mechanism. Our results also confirm that the biologically inspired CPG model is well suited for legged locomotion, since a diverse manifestation of networks have been observed to succeed in fitness simulations during evolution.Comment: 11 pages, 9 figures; substantial revision of content, organization, and quantitative result

    The Translocal Event and the Polyrhythmic Diagram

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    This thesis identifies and analyses the key creative protocols in translocal performance practice, and ends with suggestions for new forms of transversal live and mediated performance practice, informed by theory. It argues that ontologies of emergence in dynamic systems nourish contemporary practice in the digital arts. Feedback in self-organised, recursive systems and organisms elicit change, and change transforms. The arguments trace concepts from chaos and complexity theory to virtual multiplicity, relationality, intuition and individuation (in the work of Bergson, Deleuze, Guattari, Simondon, Massumi, and other process theorists). It then examines the intersection of methodologies in philosophy, science and art and the radical contingencies implicit in the technicity of real-time, collaborative composition. Simultaneous forces or tendencies such as perception/memory, content/ expression and instinct/intellect produce composites (experience, meaning, and intuition- respectively) that affect the sensation of interplay. The translocal event is itself a diagram - an interstice between the forces of the local and the global, between the tendencies of the individual and the collective. The translocal is a point of reference for exploring the distribution of affect, parameters of control and emergent aesthetics. Translocal interplay, enabled by digital technologies and network protocols, is ontogenetic and autopoietic; diagrammatic and synaesthetic; intuitive and transductive. KeyWorx is a software application developed for realtime, distributed, multimodal media processing. As a technological tool created by artists, KeyWorx supports this intuitive type of creative experience: a real-time, translocal ā€œjammingā€ that transduces the lived experience of a ā€œbiogram,ā€ a synaesthetic hinge-dimension. The emerging aesthetics are processual ā€“ intuitive, diagrammatic and transversal

    Gathering Ecologies

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    What might an interactive artwork look like that enabled greater expressive potential for all of the components of the event? How can we radically shift our idea of interactivity towards an ecological conception of the term, emphasising the generation of complex relation over the stability of objects and subjects? Gathering Ecologies explores this ethical and political shift in thinking, examining the creative potential of differential relations through key concepts from the philosophies of A.N. Whitehead, Gilbert Simondon and Michel Serres. Utilising detailed examinations of work by artists such as Lygia Clark, Rafael Lozano-Hemmer, Nathaniel Stern and Joyce Hinterding, the book discusses the creative potential of movement, perception and sensation, interfacing, sound and generative algorithmic design to tune an event towards the conditions of its own ecological emergence

    A STUDY ON DYNAMIC SYSTEMS RESPONSE OF THE PERFORMANCE CHARACTERISTICS OF SOME MAJOR BIOPHYSICAL SYSTEMS

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    Dynamic responses of biophysical systems - performance characteristic

    Binding Mechanisms in Visual Perception and Their Link With Neural Oscillations: A Review of Evidence From tACS

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    Neurophysiological studies in humans employing magneto- (MEG) and electro- (EEG) encephalography increasingly suggest that oscillatory rhythmic activity of the brain may be a core mechanism for binding sensory information across space, time, and object features to generate a unified perceptual representation. To distinguish whether oscillatory activity is causally related to binding processes or whether, on the contrary, it is a mere epiphenomenon, one possibility is to employ neuromodulatory techniques such as transcranial alternating current stimulation (tACS). tACS has seen a rising interest due to its ability to modulate brain oscillations in a frequency-dependent manner. In the present review, we critically summarize current tACS evidence for a causal role of oscillatory activity in spatial, temporal, and feature binding in the context of visual perception. For temporal binding, the emerging picture supports a causal link with the power and the frequency of occipital alpha rhythms (8ā€“12 Hz); however, there is no consistent evidence on the causal role of the phase of occipital tACS. For feature binding, the only study available showed a modulation by occipital alpha tACS. The majority of studies that successfully modulated oscillatory activity and behavioral performance in spatial binding targeted parietal areas, with the main rhythms causally linked being the theta (~7 Hz) and beta (~18 Hz) frequency bands. On the other hand, spatio-temporal binding has been directly modulated by parieto-occipital gamma (~40ā€“60 Hz) and alpha (10 Hz) tACS, suggesting a potential role of cross-frequency coupling when binding across space and time. Nonetheless, negative or partial results have also been observed, suggesting methodological limitations that should be addressed in future research. Overall, the emerging picture seems to support a causal role of brain oscillations in binding processes and, consequently, a certain degree of plasticity for shaping binding mechanisms in visual perception, which, if proved to have long lasting effects, can find applications in different clinical populations

    Synchronisation effects on the behavioural performance and information dynamics of a simulated minimally cognitive robotic agent

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    Oscillatory activity is ubiquitous in nervous systems, with solid evidence that synchronisation mechanisms underpin cognitive processes. Nevertheless, its informational content and relationship with behaviour are still to be fully understood. In addition, cognitive systems cannot be properly appreciated without taking into account brainā€“bodyā€“ environment interactions. In this paper, we developed a model based on the Kuramoto Model of coupled phase oscillators to explore the role of neural synchronisation in the performance of a simulated robotic agent in two different minimally cognitive tasks. We show that there is a statistically significant difference in performance and evolvability depending on the synchronisation regime of the network. In both tasks, a combination of information flow and dynamical analyses show that networks with a definite, but not too strong, propensity for synchronisation are more able to reconfigure, to organise themselves functionally and to adapt to different behavioural conditions. The results highlight the asymmetry of information flow and its behavioural correspondence. Importantly, it also shows that neural synchronisation dynamics, when suitably flexible and reconfigurable, can generate minimally cognitive embodied behaviour

    Chaotic exploration and learning of locomotion behaviours

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    We present a general and fully dynamic neural system, which exploits intrinsic chaotic dynamics, for the real-time goal-directed exploration and learning of the possible locomotion patterns of an articulated robot of an arbitrary morphology in an unknown environment. The controller is modeled as a network of neural oscillators that are initially coupled only through physical embodiment, and goal-directed exploration of coordinated motor patterns is achieved by chaotic search using adaptive bifurcation. The phase space of the indirectly coupled neural-body-environment system contains multiple transient or permanent self-organized dynamics, each of which is a candidate for a locomotion behavior. The adaptive bifurcation enables the system orbit to wander through various phase-coordinated states, using its intrinsic chaotic dynamics as a driving force, and stabilizes on to one of the states matching the given goal criteria. In order to improve the sustainability of useful transient patterns, sensory homeostasis has been introduced, which results in an increased diversity of motor outputs, thus achieving multiscale exploration. A rhythmic pattern discovered by this process is memorized and sustained by changing the wiring between initially disconnected oscillators using an adaptive synchronization method. Our results show that the novel neurorobotic system is able to create and learn multiple locomotion behaviors for a wide range of body configurations and physical environments and can readapt in realtime after sustaining damage
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