Inverse kinematics solution of a five joint robot using Feed forward and Elman network

Robotics is one of the emerging fields in today´s industries and the motion of a manipulator can be expressed based on the kinematical approach. Generally the process of computing the inverse kinematics solution is a tough assignment. By this method the joint angles of the end effector can be retrieved corresponding to the position and orientation which is provided as input. Here the Neural Network approach is adopted and the algorithms employed are Feed forward and Elman Back propagation Neural Network. Since these algorithms are put to use, the inverse kinematics of a five DOF robot can solved and the fetched result will be more precise and less complex, thus finally it can analyzed and compared.