Comparative study of forced oscillators for the adaptive generation of rhythmic movements in robot controllers

Jouaiti, Mélanie; Hénaff, Patrick

doi:10.1007/s00422-019-00807-8

Cited by 9 publications

(2 citation statements)

References 61 publications

(66 reference statements)

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“…While this model produces patterns of spiking in a simple way, its linearity leads to a poor ability to adapt oscillation frequency [52]. Importantly, unlike biological neurons, the spiking rate is insensitive to changes in tonic input [53].…”

Section: Neuron Modelmentioning

confidence: 99%

Central pattern generators evolved for real-time adaptation to rhythmic stimuli

2023

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For a robot to be both autonomous and collaborative requires the ability to adapt its movement to a variety of external stimuli, whether these come from humans or other robots. Typically, legged robots have oscillation periods explicitly defined as a control parameter, limiting the adaptability of walking gaits. Here we demonstrate a virtual quadruped robot employing a bio-inspired central pattern generator (CPG) that can spontaneously synchronize its movement to a range of rhythmic stimuli. Multi-objective evolutionary algorithms were used to optimize the variation of movement speed and direction as a function of the brain stem drive and the center of mass control respectively. This was followed by optimization of an additional layer of neurons that filters fluctuating inputs. As a result, a range of CPGs were able to adjust their gait pattern and/or frequency to match the input period. We show how this can be used to facilitate coordinated movement despite differences in morphology, as well as to learn new movement patterns.

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Section: Neuron Modelmentioning

confidence: 99%

Central pattern generators evolved for real-time adaptation to rhythmic stimuli

2023

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“…The sought-for-control system must also be adaptive and universal as the size and geometry of the foreign body can vary widely, i.e., it must have oscillating stability despite perturbation and the variety of behaviors․ One of the main distinctive features of our control problem is the realization of both the rhythmic and discrete motions. Therefore, a Rowat-Selverston neuron-based CPG controller [28] is selected among all known CPGs. Now we proceed to the next step, i.e., the control of the legs and DEA segments deformations to reach the necessary wave-like rhythmic and discrete movements.…”

Section: : A-opening Of the Mouth And B-peristaltic Motion Simulation...mentioning

confidence: 99%

Conceptual Design and Bio-Inspired Control of a New Surgical Soft Robotic Gripper

Zakaryan,

Harutyunyan,

Sarkissyan

2023

Mechanics, Machine Science, Machine-Building

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This paper describes the design and development of a novel soft robotic gripper for minimally invasive surgery (MIS) intended to remove foreign bodies from the patient's body by imitating human esophageal swallowing motions. The robotic gripper operates as follows: after locating and contacting the foreign body, the last segment of the gripper is expanding or contracting to match the size and catch the targeted object, then pushes forward, or bends it with its legs and starts to remove the object by a rhythmic peristaltic (periodically repeated) motion. This mode of the gripper’s operation allows removing bodies of different sizes from the human body without damaging the surrounding tissues, especially the blood vessels. Both the segments and legs of the gripper are made of dielectric elastomer actuators (DEAs) capable of large deformations under the influence of an external electric field (EEF). A central pattern generator (CPG)- based controller and a Rowat-Selverston type oscillator are selected to control both discrete and rhythmic motions based on electrical voltage – equivalent elastic strain relations of the orthotropic silicone elastomer obtained by the finite element analysis (FEA). The robotic gripper is modelled and studied by the ANSYS Workbench and Matlab/Simulink software. The performed computer modeling shows that due to the simple modular structure and CPG controller, the proposed robotic gripper is much faster, more adaptive and shows better response compared with its pneumatic actuated analogues.

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