Jonathan Patrick Arreguit O'Neill

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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 ...

Neural control of movement cannot be fully understood without careful consideration of interactions between the neural and biomechanical components. Recent advancements in mouse molecular genetics allow for the identification and manipulation of constituen ...

Physical simulation is an indispensable component of robotics simulation platforms that serves as the basis for a plethora of research directions. Looking strictly at robotics, the common characteristic of the most popular physics engines, such as ODE, DAR ...

Animal behavior emerges from an interaction between neural network dynamics, musculoskeletal properties and the physical environment. Accessing and understanding the interplay between these elements requires the development of integrative and morphological ...

Gait emergence and adaptation in animals is unmatched in robotic systems. Animals can create and recover locomotive functions "on-the-fly" after an injury whereas locomotion controllers for robots lack robustness to morphological changes. In this work, we ...

Many species such as eels, lampreys and leeches generate undulatory swimming locomotion adaptively. It is said that this coordinated locomotive patterns are produced by central pattern generators (CPGs) which generate rhythmic activities without any rhythm ...

Simulation is a core component of robotics workflows that can shed light on the complex interplay between a physical body, the environment and sensory feedback mechanisms in silico. To this goal several simulation methods, originating in rigid body dynamic ...

This study introduces a novel neuromechanical model employing a detailed spiking neural network to explore the role of axial proprioceptive sensory feedback, namely stretch feedback, in salamander locomotion. Unlike previous studies that often oversimplifi ...

We present a new method for multi-contact motion planning which efficiently encodes internal dynamics of the robot without needing to use full models. Our approach is based on a five-mass model which is formulated by Cartesian points instead of joint angle ...

A bio-inspired way to model locomotion is using a network of coupled phase oscillators to create a Central Pattern Generator (CPG). The recently developed feedback control method tegotae includes exteroceptive force feedback into the governing phase update ...

Jonathan Patrick Arreguit O'Neill

Chattez avec Graph Search

Neuromechanical Simulations of Animats with Decentralised Control

A Whole-Body Musculoskeletal Model of the Mouse

Gazebo Fluids: SPH-based simulation of fluid interaction with articulated rigid body dynamics

NeuroMechFly, a neuromechanical model of adult Drosophila melanogaster

Emergent adaptive gait generation through Hebbian sensor-motor maps by morphological probing

Undulatory Swimming Locomotion Driven by CPG with Multimodal Local Sensory Feedback

A smoothed particle hydrodynamics framework for fluid simulation in robotics

Balancing central control and sensory feedback produces adaptable and robust locomotor patterns in a spiking, neuromechanical model of the salamander spinal cord

Fast multi-contact whole-body motion planning with limb dynamics

Coupling-dependent convergence behavior of phase oscillators with tegotae-control