Document Detail


Comparison of human and humanoid robot control of upright stance.
MedLine Citation:
PMID:  19665564     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
There is considerable recent interest in developing humanoid robots. An important substrate for many motor actions in both humans and biped robots is the ability to maintain a statically or dynamically stable posture. Given the success of the human design, one would expect there are lessons to be learned in formulating a postural control mechanism for robots. In this study we limit ourselves to considering the problem of maintaining upright stance. Human stance control is compared to a suggested method for robot stance control called zero moment point (ZMP) compensation. Results from experimental and modeling studies suggest there are two important subsystems that account for the low- and mid-frequency (DC to approximately 1Hz) dynamic characteristics of human stance control. These subsystems are (1) a "sensory integration" mechanism whereby orientation information from multiple sensory systems encoding body kinematics (i.e. position, velocity) is flexibly combined to provide an overall estimate of body orientation while allowing adjustments (sensory re-weighting) that compensate for changing environmental conditions and (2) an "effort control" mechanism that uses kinetic-related (i.e., force-related) sensory information to reduce the mean deviation of body orientation from upright. Functionally, ZMP compensation is directly analogous to how humans appear to use kinetic feedback to modify the main sensory integration feedback loop controlling body orientation. However, a flexible sensory integration mechanism is missing from robot control leaving the robot vulnerable to instability in conditions where humans are able to maintain stance. We suggest the addition of a simple form of sensory integration to improve robot stance control. We also investigate how the biological constraint of feedback time delay influences the human stance control design. The human system may serve as a guide for improved robot control, but should not be directly copied because the constraints on robot and human control are different.
Authors:
Robert J Peterka
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Publication Detail:
Type:  Comparative Study; Journal Article; Research Support, N.I.H., Extramural     Date:  2009-08-07
Journal Detail:
Title:  Journal of physiology, Paris     Volume:  103     ISSN:  1769-7115     ISO Abbreviation:  J. Physiol. Paris     Publication Date:    2009 Sep-Dec
Date Detail:
Created Date:  2009-10-13     Completed Date:  2010-01-06     Revised Date:  2013-07-10    
Medline Journal Info:
Nlm Unique ID:  9309351     Medline TA:  J Physiol Paris     Country:  France    
Other Details:
Languages:  eng     Pagination:  149-58     Citation Subset:  IM    
Affiliation:
Biomedical Engineering Division, Oregon Health & Science University, OHSU West Campus, 505 NW 185th Avenue, Beaverton, OR 97006, USA. peterkar@ohsu.edu
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MeSH Terms
Descriptor/Qualifier:
Adaptation, Physiological
Humans
Models, Biological
Models, Theoretical
Nonlinear Dynamics
Postural Balance / physiology*
Posture / physiology*
Proprioception / physiology*
Psychomotor Performance / physiology*
Robotics*
Grant Support
ID/Acronym/Agency:
AG-17960/AG/NIA NIH HHS; R01 AG017960/AG/NIA NIH HHS; R01 AG017960-08/AG/NIA NIH HHS
Comments/Corrections

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