Motor Control and Learning by the State Space Model

Title: en_US Motor Control and Learning by the State Space Model
Creator: en_US Raibert, Marc H.
Date: 2004-10-20T20:08:02Z
Date Available: 2004-10-20T20:08:02Z
Date Issued: en_US 1977-09-01
Identifier: en_US AITR-439
uri: http://hdl.handle.net/1721.1/6927
Abstract: en_US A model is presented that deals with problems of motor control, motor learning, and sensorimotor integration. The equations of motion for a limb are parameterized and used in conjunction with a quantized, multi-dimensional memory organized by state variables. Descriptions of desired trajectories are translated into motor commands which will replicate the specified motions. The initial specification of a movement is free of information regarding the mechanics of the effector system. Learning occurs without the use of error correction when practice data are collected and analyzed.
Extent: 13850748 bytes; 10963405 bytes
Format: application/postscript; application/pdf
Language: en_US
Relation: en_US AITR-439