계층 구조의 신경회로망에 의한 로보트 PTP 궤적 계획

Robot PTP Trajectory Planning Using a Hierarchical Neural Network Structure

A hierarchical neural network structure is described for robot PTP trajectory planning. In the first level, the multi-layered Perceptron neural network is used for the inverse kinematics with the back-propagation learning procedure. In the second level, a saccade generation model based joint trajectory planning model in proposed and analyzed with several features. Various simulations are performed to investigate the characteristics of the proposed neural networks.