Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
408487 | Neurocomputing | 2007 | 5 Pages |
Abstract
The present article proposes a novel computational approach to the motor planning. In this approach, each motor command is represented as a linear combination of prefixed basis patterns, and the command for a given task is designed by minimizing a two-termed criterion consisting of a task optimization term and a parameter preference (i.e., sparseness) term. The result of a computer simulation with a single-joint reaching task confirmed that our “representation-based” criterion for motor planning appropriately worked, together with showing that the resultant trajectory qualitatively replicated Fitts’ law.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Yutaka Sakaguchi, Shiro Ikeda,