Empirical study on a robotic manipulator concludes that training sets larger than 125 samples yield no further gains in accuracy or efficiency for feedforward neural network inverse kinematics solvers.
V.: Neural network based inverse kinematics solution for trajectory tracking of a robotic arm.Procedia Technology, 12, 20–27 (2014)
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How Many Training Samples Are Needed for the Inverse Kinematics Solutions by Artificial Neural Networks
Empirical study on a robotic manipulator concludes that training sets larger than 125 samples yield no further gains in accuracy or efficiency for feedforward neural network inverse kinematics solvers.