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Movement Curvature Planning through Force Field Internal Models

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Publications associées (39)

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Higher-order organization of multivariate time series

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Time series analysis has proven to be a powerful method to characterize several phenomena in biology, neuroscience and economics, and to understand some of their underlying dynamical features. Several methods have been proposed for the analysis of multivar ...

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Geometric Learning: Leveraging differential geometry for learning and control

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In this thesis, we concentrate on advancing high-level behavioral control policies for robotic systems within the framework of Dynamical Systems (DS). Throughout the course of this research, a unifying thread weaving through diverse fields emerges, and tha ...

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Neuronal correlates of goal-directed sensorimotor transformation in sensory, motor and higher-order cortical areas

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An important function of the brain is to interpret incoming sensory information from the outside world to guide adaptive behavior. Understanding how and where sensory information is transformed into motor commands in a context- and learning-dependent manne ...

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On the number of regions of piecewise linear neural networks

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Many feedforward neural networks (NNs) generate continuous and piecewise-linear (CPWL) mappings. Specifically, they partition the input domain into regions on which the mapping is affine. The number of these so-called linear regions offers a natural metric ...

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Neuromechanical Simulations of Animats with Decentralised Control

Jonathan Patrick Arreguit O'Neill

The transition from aquatic to terrestrial environments represents a significant event in the history of evolution. For this transition to occur, animals had to adapt their morphology, physiology and locomotory skills to handle the challenges and interacti ...

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A Comparison of Residual-based Methods on Fault Detection

Olga Fink, Gaëtan Michel Frusque

An important initial step in fault detection for complex industrial systems is gaining an understanding of their health condition. Subsequently, continuous monitoring of this health condition becomes crucial to observe its evolution, track changes over tim ...

PHM Society2023

Optimizing Dynamic Aperture Studies with Active Learning

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Dynamic aperture is an important concept for the study of non-linear beam dynamics in circular accelerators. It describes the extent of the phase-space region where a particle's motion remains bounded over a given number of turns. Understanding the feature ...

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Data-Driven Control Synthesis using Koopman Operator: A Robust Approach

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This paper proposes a data-driven control design method for nonlinear systems that builds upon the Koopman operator framework. In particular, the Koopman operator is used to lift the nonlinear dynamics to a higher-dimensional space where the so-called obse ...

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Contrasting action and posture coding with hierarchical deep neural network models of proprioception

Alexander Mathis, Mackenzie Mathis, Matthias Bethge, Kai Jappe Sandbrink

Biological motor control is versatile, efficient, and depends on proprioceptive feedback. Muscles are flexible and undergo continuous changes, requiring distributed adaptive control mechanisms that continuously account for the body's state. The canonical r ...

eLIFE SCIENCES PUBL LTD2023

Investigating neural resource allocation in the sensorimotor control of extra limbs

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The rise of robotic body augmentation brings forth new developments that will transform robotics, human-machine interaction, and wearable electronics. Extra robotic limbs, although building upon restorative technologies, bring their own set of challenges i ...

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Neurophysiological underpinnings of an intensive protocol for upper limb motor recovery in subacute and chronic stroke patients

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ABS T R A C T BACKGROUND: Upper limb (UL) motor impairment following stroke is a leading cause of functional limitations in activities of daily living. Robot-assisted therapy supports rehabilitation, but how its efficacy and the underlying neural mechanism ...

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Subcortical correlates of consciousness with human single neuron recordings

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Subcortical brain structures such as the basal ganglia or the thalamus are involved in regulating motor and cognitive behavior. However, their contribution to perceptual consciousness is still unclear, due to the inherent difficulties of recording subcorti ...

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Computational chemistry aims to simulate reactions and molecular properties at the atomic scale, advancing the design of novel compounds and materials with economic, environmental, and societal implications. However, the field relies on approximate quantum ...

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The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

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Dynamic modeling of folding joints is critical for predicting dynamic behavior, optimizing design parameters, and developing control strategies for origami robots and machines. Although kinematics of the folded joints exists, little research describes thei ...

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Animal behaviour alternates between stochastic exploration and goal-directed actions, which are generated by the underlying neural dynamics. Previously, we demonstrated that the compositional Restricted Boltzmann Machine (cRBM) can decompose whole-brain ac ...

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Reinforcement learning (RL) is crucial for learning to adapt to new environments. In RL, the prediction error is an important component that compares the expected and actual rewards. Dopamine plays a critical role in encoding these prediction errors. In my ...

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