Neural networks with their inherent learning ability have been widely applied to solve the
robot manipulator inverse kinematics problems. However, there are still two open
problems:(1) without knowing inverse kinematic expressions, these solutions have the
difficulty of how to collect training sets, and (2) the gradient-based learning algorithms can
cause a very slow training process, especially for a complex configuration, or a large set of
training data. Unlike these traditional implementations, the proposed metho trains neural …