An improved approach to the solution of inverse kinematics problems for robot manipulators

A structured artificial neural-network (ANN) approach has been proposed her e to control the motion of a robot manipulator. Many neural-network models use threshold units with sigmoid transfer functions and gradient descent-ty pe learning rules. The learning equations used are those of the backpropaga tion algorithm. In this work, the solution of the kinematics of a six-degre es-of-freedom robot manipulator is implemented by using ANN. Work has been undertaken to find the best ANN configurations for this problem. Both the p lacement and orientation angles of a robot manipulator are used to fin the inverse kinematics solutions. (C) 2000 Elsevier Science Ltd. All rights res erved.