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Auke Jan Ijspeert - One of the best experts on this subject based on the ideXlab platform.

  • biped gait controller for large speed variations combining reflexes and a Central Pattern Generator in a neuromuscular model
    International Conference on Robotics and Automation, 2015
    Co-Authors: Nicolas Van Der Noot, Auke Jan Ijspeert, Renaud Ronsse
    Abstract:

    Controllers based on neuromuscular models hold the promise of energy-efficient and human-like walkers. However, most of them rely on optimizations or cumbersome hand-tuning to find controller parameters which, in turn, are usually working for a specific gait or forward speed only. Consequently, designing neuromuscular controllers for a large variety of gaits is usually challenging and highly sensitive. In this contribution, we propose a neuromuscular controller combining reflexes and a Central Pattern Generator able to generate gaits across a large range of speeds, within a single optimization. Applying this controller to the model of COMAN, a 95 cm tall humanoid robot, we were able to get energy-efficient gaits ranging from 0.4 m/s to 0.9 m/s. This covers normal human walking speeds once scaled to the robot height. In the proposed controller, the robot speed could be continuously commanded within this range by changing three high-level parameters as linear functions of the target speed. This allowed large speed transitions with no additional tuning. By combining reflexes and a Central Pattern Generator, this approach can also predict when the next strike will occur and modulate the step length to step over a hole.

  • Integration of vision and Central Pattern Generator based locomotion for path planning of a non-holonomic crawling humanoid robot
    2010
    Co-Authors: S.a b Gay, Sarah Dégallier, Ugo Pattacini, Auke Jan Ijspeert, José Santos Victor
    Abstract:

    In this paper we present our work on integrating a locomotion controller based on Central Pattern Generator (CPG) and a motion planning algorithm using artificial potential fields for a non-holonomic crawling humanoid robot, the iCub. We also integrated a vision tracker and an inverse kinematics solver to perform reaching tasks. We study the influence of the various parameters of the potential field equations on the performance of the system and prove the efficiency of our framework by testing it on a physics-based robotics simulator and partially on the real iCub.

  • boxybot a swimming and crawling fish robot controlled by a Central Pattern Generator
    IEEE International Conference on Biomedical Robotics and Biomechatronics, 2006
    Co-Authors: D Lachat, Alessandro Crespi, Auke Jan Ijspeert
    Abstract:

    We present a novel fish robot capable of swimming and crawling. The robot is driven by DC motors and has three actuated fins, with two pectoral fins and one caudal fin. It is loosely inspired from the boxfish. The control architecture of the robot is constructed around a Central Pattern Generator (CPG) implemented as a system of coupled nonlinear oscillators, which, like its biological counterpart, can produce coordinated Patterns of rhythmic activity while being modulated by simple control parameters. Using the CPG model, the robot is capable of performing and switching between a variety of different locomotor behaviors such as swimming forwards, swimming backwards, turning, rolling, moving upwards/downwards, and crawling. These behaviors are triggered and modulated by sensory input provided by light and water sensors. Results are presented demonstrating the agility of the robot, and interesting properties of a CPG-based control approach such as stability of the rhythmic Patterns due to limit cycle behavior, and the production of smooth trajectories despite abrupt changes of control parameters

  • amphibot ii an amphibious snake robot that crawls and swims using a Central Pattern Generator
    Proceedings of the 9th International Conference on Climbing and Walking Robots (CLAWAR 2006), 2006
    Co-Authors: Alessandro Crespi, Auke Jan Ijspeert
    Abstract:

    This article presents AmphiBot II, an am- phibious snake robot designed for both serpentine loco- motion (crawling) and swimming. It is controlled by an on-board Central Pattern Generator (CPG) inspired by those found in vertebrates. The CPG is modelled as a chain of coupled nonlinear oscillators, and is designed to produce travelling waves. Its parameters can be modi- fled on the ∞y. We present the hardware of the robot and the structure of the CPG, then the systematic parameter tests done in simulation and with the real robot to char- acterize how the speed of locomotion depends on the parameters determining the frequency, amplitude and wavelength of the body undulation.

  • distributed Central Pattern Generator model for robotics application based on phase sensitivity analysis
    Lecture Notes in Computer Science, 2004
    Co-Authors: Jonas Buchli, Auke Jan Ijspeert
    Abstract:

    A method is presented to predict phase relationships between coupled phase oscillators. As an illustration of how the method can be applied, a distributed Central Pattern Generator (CPG) model based on amplitude controlled phase oscillators is presented. Representative results of numerical integration of the CPG model are presented to illustrate its excellent properties in terms of transition speeds, robustness and independence on initial conditions. A particularly interesting feature of the CPG is the possibility to switch between different stable gaits by varying a single parameter. These characteristics make the CPG model an interesting solution for the deCentralized control of multi-legged robots. The approach is discussed in the more general framework of coupled nonlinear systems, and design tools for nonlinear distributed control schemes applicable to Information Technology and Robotics.

Ronald L Calabrese - One of the best experts on this subject based on the ideXlab platform.

  • constancy and variability in the output of a Central Pattern Generator
    The Journal of Neuroscience, 2011
    Co-Authors: Brian J Norris, Angela Wenning, Terrence Michael Wright, Ronald L Calabrese
    Abstract:

    Experimental and corresponding modeling studies have demonstrated a twofold to fivefold variation of intrinsic and synaptic parameters across animals, whereas functional output is maintained. These studies have led to the hypothesis that correlated, compensatory changes in particular parameters can at least partially explain the biological variability in parameters. Using the leech heartbeat Central Pattern Generator (CPG), we selected three different segmental motor neurons that fire in a functional phase progression but receive input from the same four premotor interneurons. Previous work suggested that the phase progression arises because the Pattern of relative strength of the four inputs varies systematically across the segmental motor neurons. Nevertheless, there was considerable animal-to-animal variation in the absolute strengths of these connections. We tested the hypothesis that functional output is maintained in the face of variation in the absolute strength of connections because relative strengths onto particular motor neurons are maintained. We found that relative strength is not strictly maintained across animals even as functional output is maintained, and animal-to-animal variations in relative strength of particular inputs do not correlate strongly with output phase. In parallel with this variation in synaptic strength, the firing phase of the premotor inputs to these motor neurons varies considerably across individuals. We conclude that the number (four) of inputs to each motor neuron, which each vary in strength, and the phase diversity of the temporal Pattern of input from the CPG diminish the influence of individual inputs. We hypothesize that each animal arrives at a unique solution for how the network produces functional output.

  • a Central Pattern Generator producing alternative outputs Pattern strength and dynamics of premotor synaptic input to leech heart motor neurons
    Journal of Neurophysiology, 2007
    Co-Authors: Brian J Norris, Adam L Weaver, Angela Wenning, Paul S Garcia, Ronald L Calabrese
    Abstract:

    The Central Pattern Generator (CPG) for heartbeat in medicinal leeches consists of seven identified pairs of segmental heart interneurons and one unidentified pair. Four of the identified pairs and...

  • a Central Pattern Generator producing alternative outputs temporal Pattern of premotor activity
    Journal of Neurophysiology, 2006
    Co-Authors: Brian J Norris, Adam L Weaver, Lee G Morris, Angela Wenning, Paul A Garcia, Ronald L Calabrese
    Abstract:

    The Central Pattern Generator for heartbeat in medicinal leeches constitutes seven identified pairs of segmental heart interneurons. Four identified pairs of heart interneurons make a staggered pat...

  • Detailed model of intersegmental coordination in the timing network of the leech heartbeat Central Pattern Generator.
    Journal of Neurophysiology, 2003
    Co-Authors: Sami H. Jezzini, Andrew A. V. Hill, Pavlo Kuzyk, Ronald L Calabrese
    Abstract:

    To address the general problem of intersegmental coordination of oscillatory neuronal networks, we have studied the leech heartbeat Central Pattern Generator. The core of this Pattern Generator is ...

Brian J Norris - One of the best experts on this subject based on the ideXlab platform.

  • constancy and variability in the output of a Central Pattern Generator
    The Journal of Neuroscience, 2011
    Co-Authors: Brian J Norris, Angela Wenning, Terrence Michael Wright, Ronald L Calabrese
    Abstract:

    Experimental and corresponding modeling studies have demonstrated a twofold to fivefold variation of intrinsic and synaptic parameters across animals, whereas functional output is maintained. These studies have led to the hypothesis that correlated, compensatory changes in particular parameters can at least partially explain the biological variability in parameters. Using the leech heartbeat Central Pattern Generator (CPG), we selected three different segmental motor neurons that fire in a functional phase progression but receive input from the same four premotor interneurons. Previous work suggested that the phase progression arises because the Pattern of relative strength of the four inputs varies systematically across the segmental motor neurons. Nevertheless, there was considerable animal-to-animal variation in the absolute strengths of these connections. We tested the hypothesis that functional output is maintained in the face of variation in the absolute strength of connections because relative strengths onto particular motor neurons are maintained. We found that relative strength is not strictly maintained across animals even as functional output is maintained, and animal-to-animal variations in relative strength of particular inputs do not correlate strongly with output phase. In parallel with this variation in synaptic strength, the firing phase of the premotor inputs to these motor neurons varies considerably across individuals. We conclude that the number (four) of inputs to each motor neuron, which each vary in strength, and the phase diversity of the temporal Pattern of input from the CPG diminish the influence of individual inputs. We hypothesize that each animal arrives at a unique solution for how the network produces functional output.

  • a Central Pattern Generator producing alternative outputs Pattern strength and dynamics of premotor synaptic input to leech heart motor neurons
    Journal of Neurophysiology, 2007
    Co-Authors: Brian J Norris, Adam L Weaver, Angela Wenning, Paul S Garcia, Ronald L Calabrese
    Abstract:

    The Central Pattern Generator (CPG) for heartbeat in medicinal leeches consists of seven identified pairs of segmental heart interneurons and one unidentified pair. Four of the identified pairs and...

  • a Central Pattern Generator producing alternative outputs temporal Pattern of premotor activity
    Journal of Neurophysiology, 2006
    Co-Authors: Brian J Norris, Adam L Weaver, Lee G Morris, Angela Wenning, Paul A Garcia, Ronald L Calabrese
    Abstract:

    The Central Pattern Generator for heartbeat in medicinal leeches constitutes seven identified pairs of segmental heart interneurons. Four identified pairs of heart interneurons make a staggered pat...

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.

  • on a standing wave Central Pattern Generator and the coherence problem
    Biomedical Signal Processing and Control, 2010
    Co-Authors: Edmond A. Jonckheere, Poonsuk Lohsoonthorn, Srideep Musuvathy, Vikram Mahajan, Margareta Stefanovic
    Abstract:

    Abstract An electrophysiological phenomenon running up and down the spine, elicited by light pressure contact at very precise points and thereafter taking the external appearance of an undulatory motion of the spine, is analyzed from its standing wave, coherence, and synchronization-at-a-distance properties. This standing spinal wave can be elicited in both normal and quadriplegic subjects, which demonstrates that the neuronal circuitry is embedded in the spine. The latter, along with the inherent rhythmicity of the motion, its wave properties, and the absence of external sensory input once the phenomenon is elicited reveal a Central Pattern Generator (CPG). The major investigative tool is surface electromyographic (sEMG) wavelet signal analysis at various points along the paraspinal muscles. Statistical correlation among the various points is used to establish the standing wave phenomenon on a specific subband of the Daubechies wavelet decomposition of the sEMG signals. More precisely, ∼ 10  Hz coherent bursts reveal synchronization between sensory-motor loops at a distance larger, and a frequency slower, than those already reported. As a potential therapeutic application, it is shown that partial recovery from spinal cord injury can be assessed by the correlation between the sEMG signals on both sides of the injury.

Joseph Ayers - One of the best experts on this subject based on the ideXlab platform.

  • low power high pvt variation tolerant Central Pattern Generator design for a bio hybrid micro robot
    International Midwest Symposium on Circuits and Systems, 2012
    Co-Authors: Jing Lu, Jing Yang, Joseph Ayers
    Abstract:

    This paper presents a low power circuit design for an electronic nervous system composed of Central Pattern Generator (CPG) to control a biomimetic robot that mimics the lamprey swimming system. The circuit has been designed using 65nm CMOS technology model at 0.8V supply. The design challenges of narrow voltage design margin and high sensitivity to parameter variation are addressed by circuit optimization techniques as well as amplitude and time parameter scaling. The electronic CPG consists of electronic neurons connected through electronic synapses, where the behaviors of the neuron and synapse adopt Hindmarsh-Rose (HR) dynamics to replicate biological neurons and a first order chemical synapse model is utilized to achieve active synapses. The simulation results validate the electronic CPG performance at 0.8V supply voltage with parameter variation tolerance of 5% dissipating 3.28mW. The die size of the chip is 1.1mm2 including I/O pads.

  • low power cmos electronic Central Pattern Generator design for a biomimetic underwater robot
    Neurocomputing, 2007
    Co-Authors: Joseph Ayers
    Abstract:

    This paper presents a feasibility study of a Central Pattern Generator-based analog controller for an autonomous robot. The operation of a neuronal circuit formed of electronic neurons based on Hindmarsh-Rose neuron dynamics and first order chemical synapses is modeled. The controller is based on a standard [email protected] CMOS process with 2V supply voltage. In order to achieve low power consumption, CMOS subthreshold circuit techniques are used. The controller generates an excellent replica of the walking motor program and allows switching between walking in different directions in response to different command inputs. The simulated power consumption is 4.8mW and die size including I/O pads is 2.2mm by 2.2mm. Simulation results demonstrate that the proposed design can generate adaptive walking motor programs to control the legs of autonomous robots.