Title
Generating spatiotemporal joint torque patterns from dynamical synchronization of distributed pattern generators.
Abstract
Pattern generators found in the spinal cord are no more seen as simple rhythmic oscillators for motion control. Indeed, they achieve flexible and dynamical coordination in interaction with the body and the environment dynamics giving to rise motor synergies. Discovering the mechanisms underlying the control of motor synergies constitutes an important research question not only for neuroscience but also for robotics: the motors coordination of high dimensional robotic systems is still a drawback and new control methods based on biological solutions may reduce their overall complexity. We propose to model the flexible combination of motor synergies in embodied systems via partial phase synchronization of distributed chaotic systems; for specific coupling strength, chaotic systems are able to phase synchronize their dynamics to the resonant frequencies of one external force. We take advantage of this property to explore and exploit the intrinsic dynamics of one specified embodied system. In two experiments with bipedal walkers, we show how motor synergies emerge when the controllers phase synchronize to the body's dynamics, entraining it to its intrinsic behavioral patterns. This stage is characterized by directed information flow from the sensors to the motors exhibiting the optimal situation when the body dynamics drive the controllers (mutual entrainment). Based on our results, we discuss the relevance of our findings for modeling the modular control of distributed pattern generators exhibited in the spinal cord, and for exploring the motor synergies in robots.
Year
DOI
Venue
2009
10.3389/neuro.12.002.2009
Front. Neurorobot.
Keywords
Field
DocType
causal information flow,motor synergies,phase synchronization,sensorimotor coordination,bioinformatics,biomedical research
Behavioral pattern,Motion control,Synchronization,Torque,Communication,Computer science,Phase synchronization,Artificial intelligence,Modular design,Robot,Robotics,Machine learning
Journal
Volume
ISSN
Citations 
3
1662-5218
7
PageRank 
References 
Authors
0.56
12
3
Name
Order
Citations
PageRank
Alexandre Pitti1317.34
Max Lungarella247942.16
Yasuo Kuniyoshi32481362.58