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Motor Control and Learning by the State Space Model

Author(s)
Raibert, Marc H.
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Abstract
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.
Date issued
1977-09-01
URI
http://hdl.handle.net/1721.1/6927
Other identifiers
AITR-439
Series/Report no.
AITR-439

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  • AI Technical Reports (1964 - 2004)

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