A real-time approach using feed forward neural network for a 5 DOF robot manipulator

Abstract

This paper displays a procedure for solving the inverse kinematics problem utilizing neural networks in realtime application. The inverse kinematics problem for a robotic manipulator is acquired for the required manipulator joint values for a given desired end point position and orientation. The proposed strategy yields various and exact arrangements and it is suitable for real-time applications. The Conclusive simulation shows that, by utilizing this new calculating algorithm, it can give a precise inverse kinematics solution quick and has higher efficiency. Aside from these, when utilizing as a part of practice, it additionally mirrors a flawless execution.