Scheduled System Maintenance:
Some services will be unavailable Sunday, March 29th through Monday, March 30th. We apologize for the inconvenience.
By Topic

Hierarchical neural network model for voluntary movement with application to robotics

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Kawato, M. ; Dept. of Biophys. Eng., Osaka Univ., Japan ; Uno, Y. ; Isobe, M. ; Suzuki, R.

In order to control voluntary movements, the central nervous system must solve the following three computational problems at different levels: determination of a desired trajectory in the visual coordinates; transformation of the trajectory from visual coordinates to body coordinates; and generation of motor commands. Based on physiological information and previous models, computational theories are proposed for the first two problems, and a hierarchical neural network model is introduced to deal with motor commands. The application of this approach to robotics is outlined.<>

Published in:

Control Systems Magazine, IEEE  (Volume:8 ,  Issue: 2 )