Title :
A network for learning kinematics with application to human reaching models
Author_Institution :
Dept. of Cognitive & Neural Syst., Boston Univ., MA, USA
fDate :
27 Jun-2 Jul 1994
Abstract :
A model for self-organization of the coordinate transformations required for spatial reaching is presented. During a motor babbling phase, a mapping from spatial coordinate directions to joint motion directions is learned. After learning, the model is able to produce straight-line spatial trajectories with characteristic bell-shaped spatial velocity profiles, as observed in human reaches. Simulation results are presented for transverse plane reaching using a two degree-of-freedom arm
Keywords :
biomechanics; learning (artificial intelligence); manipulator kinematics; manipulators; neural nets; physiological models; bell-shaped spatial velocity profiles; coordinate transformations; human reaching models; joint motion directions; kinematics; motor babbling phase; self-organization; spatial reaching; straight-line spatial trajectories; transverse plane reaching; wo degree-of-freedom arm; Ear; Equations; Humans; Orbital robotics; Robot kinematics; Robot sensing systems; Vectors;
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
DOI :
10.1109/ICNN.1994.374667
