A Model for Motor Control and Learning
Abstract
The human motor system acquires control of each limb in the body, adapts to mechanical and sensory changes, performs coordinate transformations from visual space to motor space, and uses limbs Interchangeably in executing motor programs. It is supposed that any flexible motor control system, biological or otherwise, can be viewed in terms of high- and low-level processes which accomplish these tasks; High-level processes generate descriptions of desired trajectories without considering the mechanical properties of any one effector system, and low-level mechanisms, tailored to the kinematic and dynamic properties of a particular effector system, translate these descriptions into motor plans. I propose a controller which uses an 'internal inverse dynamic model' to perform these low-level translations for a mechanical arm [Raibert 1976].
Cite
Text
Raibert. "A Model for Motor Control and Learning." International Joint Conference on Artificial Intelligence, 1977.Markdown
[Raibert. "A Model for Motor Control and Learning." International Joint Conference on Artificial Intelligence, 1977.](https://mlanthology.org/ijcai/1977/raibert1977ijcai-model/)BibTeX
@inproceedings{raibert1977ijcai-model,
title = {{A Model for Motor Control and Learning}},
author = {Raibert, Marc H.},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {1977},
pages = {761},
url = {https://mlanthology.org/ijcai/1977/raibert1977ijcai-model/}
}