The Experts below are selected from a list of 324 Experts worldwide ranked by ideXlab platform

Edmond A. Jonckheere - One of the best experts on this subject based on the ideXlab platform.

  • GlobalSIP - Stationary regime for standing wave central Pattern Generator
    2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2015
    Co-Authors: Roberto Martin Del Campo, Edmond A. Jonckheere
    Abstract:

    The purpose of this research is to show that the spatio-temporal analysis on surface Electromyographic (sEMG) signals that originally confirmed existence of a standing wave Central Pattern Generator (CPG) along the spine are reproducible under less than ideal conditions and despite evolution of the entrainment technique, different hardware and data collection protocol. This analysis reveals a coherence at a distance between sEMG signals, which because of its large scale reproducibility could become a test for properly functioning Central Nervous System.

  • Stationary regime for standing wave central Pattern Generator
    2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2015
    Co-Authors: Roberto Martin Del Campo, Edmond A. Jonckheere
    Abstract:

    The purpose of this research is to show that the spatio-temporal analysis on surface Electromyographic (sEMG) signals that originally confirmed existence of a standing wave Central Pattern Generator (CPG) along the spine are reproducible under less than ideal conditions and despite evolution of the entrainment technique, different hardware and data collection protocol. This analysis reveals a coherence at a distance between sEMG signals, which because of its large scale reproducibility could become a test for properly functioning Central Nervous System.

J.w.jr. Clark - One of the best experts on this subject based on the ideXlab platform.

  • A model of the respiratory central Pattern Generator
    The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2004
    Co-Authors: B. Amini, A. Bidani, J.b. Zwischenberger, J.w.jr. Clark
    Abstract:

    We have developed a model of the mammalian respiratory central Pattern Generator (rCPG) to mimic the salient characteristics of its constituent medullary neurons. This model was designed as a network of Hodgkin-Huxley type medullary neurons under the hypothesis that synaptic and network effects predominate over ionic influences in determining the Pattern of firing seen in individual neurons. After obtaining satisfactory mimicry of these Patterns we validated the model to a different set of data in order to examine its robustness in the face of transient perturbations.

Maximilien Naveau - One of the best experts on this subject based on the ideXlab platform.

  • a reactive walking Pattern Generator based on nonlinear model predictive control
    International Conference on Robotics and Automation, 2017
    Co-Authors: Maximilien Naveau, Manuel Kudruss, Olivier Stasse, Christian Kirches, Katja Mombaur, Philippe Soueres
    Abstract:

    The contribution of this work is to show that real-time nonlinear model predictive control (NMPC) can be implemented on position controlled humanoid robots. Following the idea of “walking without thinking,” we propose a walking Pattern Generator that takes into account simultaneously the position and orientation of the feet. A requirement for an application in real-world scenarios is the avoidance of obstacles. Therefore, this letter shows an extension of the Pattern Generator that directly considers the avoidance of convex obstacles. The algorithm uses the whole-body dynamics to correct the center of mass trajectory of the underlying simplified model. The Pattern Generator runs in real-time on the embedded hardware of the humanoid robot HRP-2 and experiments demonstrate the increase in performance with the correction.

  • a versatile and efficient Pattern Generator for generalized legged locomotion
    International Conference on Robotics and Automation, 2016
    Co-Authors: Justin Carpentier, Maximilien Naveau, Olivier Stasse, Steve Tonneau, Nicolas Mansard
    Abstract:

    This paper presents a generic and efficient approach to generate dynamically consistent motions for under-actuated systems like humanoid or quadruped robots. The main contribution is a walking Pattern Generator, able to compute a stable trajectory of the center of mass of the robot along with the angular momentum, for any given configuration of contacts (e.g. on uneven, sloppy or slippery terrain, or with closed-gripper). Unlike existing methods, our solver is fast enough to be applied as a model-predictive controller. We then integrate this Pattern Generator in a complete framework: an acyclic contact planner is first used to automatically compute the contact sequence from a 3D model of the environment and a desired final posture; a stable walking Pattern is then computed by the proposed solver; a dynamically-stable whole-body trajectory is finally obtained using a second-order hierarchical inverse kinematics. The implementation of the whole pipeline is fast enough to plan a step while the previous one is executed. The interest of the method is demonstrated by real experiments on the HRP-2 robot, by performing long-step walking and climbing a staircase with handrail support.

Olivier Stasse - One of the best experts on this subject based on the ideXlab platform.

  • a reactive walking Pattern Generator based on nonlinear model predictive control
    International Conference on Robotics and Automation, 2017
    Co-Authors: Maximilien Naveau, Manuel Kudruss, Olivier Stasse, Christian Kirches, Katja Mombaur, Philippe Soueres
    Abstract:

    The contribution of this work is to show that real-time nonlinear model predictive control (NMPC) can be implemented on position controlled humanoid robots. Following the idea of “walking without thinking,” we propose a walking Pattern Generator that takes into account simultaneously the position and orientation of the feet. A requirement for an application in real-world scenarios is the avoidance of obstacles. Therefore, this letter shows an extension of the Pattern Generator that directly considers the avoidance of convex obstacles. The algorithm uses the whole-body dynamics to correct the center of mass trajectory of the underlying simplified model. The Pattern Generator runs in real-time on the embedded hardware of the humanoid robot HRP-2 and experiments demonstrate the increase in performance with the correction.

  • a versatile and efficient Pattern Generator for generalized legged locomotion
    International Conference on Robotics and Automation, 2016
    Co-Authors: Justin Carpentier, Maximilien Naveau, Olivier Stasse, Steve Tonneau, Nicolas Mansard
    Abstract:

    This paper presents a generic and efficient approach to generate dynamically consistent motions for under-actuated systems like humanoid or quadruped robots. The main contribution is a walking Pattern Generator, able to compute a stable trajectory of the center of mass of the robot along with the angular momentum, for any given configuration of contacts (e.g. on uneven, sloppy or slippery terrain, or with closed-gripper). Unlike existing methods, our solver is fast enough to be applied as a model-predictive controller. We then integrate this Pattern Generator in a complete framework: an acyclic contact planner is first used to automatically compute the contact sequence from a 3D model of the environment and a desired final posture; a stable walking Pattern is then computed by the proposed solver; a dynamically-stable whole-body trajectory is finally obtained using a second-order hierarchical inverse kinematics. The implementation of the whole pipeline is fast enough to plan a step while the previous one is executed. The interest of the method is demonstrated by real experiments on the HRP-2 robot, by performing long-step walking and climbing a staircase with handrail support.

J.j. Abbas - One of the best experts on this subject based on the ideXlab platform.

  • A VLSI circuit of lamprey unit Pattern Generator
    IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339), 1999
    Co-Authors: E.j. Brauer, R. Jung, B. Thompsen, J.j. Abbas
    Abstract:

    The purpose of this research is to develop an analog VLSI electronic circuit that mimics the behavior of the biological lamprey spinal cord. The lamprey is an eel-like lower vertebrate with a relatively simple nervous system. The Pattern Generator for locomotion is distributed along the 100 spinal segments of the lamprey spinal cord and can be treated as a chain of coupled unit Pattern Generators (uPG) with oscillatory properties. In this work we consider a 4 neuron uPG model. Bifurcation analysis of this model indicates a wide range of behaviors. In addition, a CMOS analog integrated circuit has been designed, fabricated and tested which models the biological lamprey unit Pattern Generator. Measurement results show that the electronic circuit behavior is qualitatively similar to that of the numerical model.

  • IJCNN - A VLSI circuit of lamprey unit Pattern Generator
    IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339), 1999
    Co-Authors: E.j. Brauer, R. Jung, B. Thompsen, J.j. Abbas
    Abstract:

    The purpose of this research is to develop an analog VLSI electronic circuit that mimics the behavior of the biological lamprey spinal cord. The lamprey is an eel-like lower vertebrate with a relatively simple nervous system. The Pattern Generator for locomotion is distributed along the 100 spinal segments of the lamprey spinal cord and can be treated as a chain of coupled unit Pattern Generators (uPG) with oscillatory properties. In this work we consider a 4 neuron uPG model. Bifurcation analysis of this model indicates a wide range of behaviors. In addition, a CMOS analog integrated circuit has been designed, fabricated and tested which models the biological lamprey unit Pattern Generator. Measurement results show that the electronic circuit behavior is qualitatively similar to that of the numerical model.

  • Neuromorphic aVLSI circuit of lamprey unit Pattern Generator
    42nd Midwest Symposium on Circuits and Systems (Cat. No.99CH36356), 1999
    Co-Authors: E.j. Brauer, R. Jung, B. Thompsen, J.j. Abbas
    Abstract:

    We have designed, built, and tested a neuromorphic model of the lamprey unit Pattern Generator using analog VLSI CMOS circuits. The lamprey is an eel-like fish with 100 segments in the spinal cord. Our neuromorphic single-segment model utilizes 6 neurons, 4 excitatory synapses, 8 inhibitory synapses, and 6 tonic synapses with simplified biophysical properties. The chip exhibits fixed point and oscillatory behaviors similar to the numerical model of the biological spinal cord.

  • Sensitivity analysis of an analog circuit model of lamprey unit Pattern Generator
    Proceedings of International Conference on Neural Networks (ICNN'97), 1997
    Co-Authors: E.j. Brauer, R. Jung, D. Wilson, J.j. Abbas
    Abstract:

    Neural circuitry within the spinal cord of the lamprey, a primitive vertebrate, can generate self-sustained oscillations for locomotion (swimming). This Pattern Generator can be modeled as a chain of oscillatory unit Pattern Generator segments which exhibit behavior depending on the parameter values in the network. Here, the authors present the results of a simulation study of an analog electronic circuit which mimics the behavior of the biological lamprey unit Pattern Generator. The circuitry mimics a neural network containing 6 neurons with simplified biophysical properties. The analog circuit exhibits symmetric oscillations, asymmetric oscillations, and fixed points, similar to the behavior of the mathematical model of the lamprey. This work is the first in a series of circuits designed to have possible applications in neuroscience research and in the development of artificial locomotor systems.

  • ICNN - Sensitivity analysis of an analog circuit model of lamprey unit Pattern Generator
    Proceedings of International Conference on Neural Networks (ICNN'97), 1997
    Co-Authors: E.j. Brauer, R. Jung, D. Wilson, J.j. Abbas
    Abstract:

    Neural circuitry within the spinal cord of the lamprey, a primitive vertebrate, can generate self-sustained oscillations for locomotion (swimming). This Pattern Generator can be modeled as a chain of oscillatory unit Pattern Generator segments which exhibit behavior depending on the parameter values in the network. Here, the authors present the results of a simulation study of an analog electronic circuit which mimics the behavior of the biological lamprey unit Pattern Generator. The circuitry mimics a neural network containing 6 neurons with simplified biophysical properties. The analog circuit exhibits symmetric oscillations, asymmetric oscillations, and fixed points, similar to the behavior of the mathematical model of the lamprey. This work is the first in a series of circuits designed to have possible applications in neuroscience research and in the development of artificial locomotor systems.