Analysis of Inverse Dynamics of 6-DOF Stanford Robotic Arm by Adaptive Neuro-Fuzzy Inference System (ANFIS)

Abstract

Inverse dynamics is characterized as a specified robot’s inertial and geometrical constraints, together with its joint motions, getting the torques and forces of the joint. Stanford robotic arm is described by high flexibility, particularly in assembly and handling applications. The main significant problem in robot dynamics and control is, estimating the torques that should be useful to the levers specified that the last part of the levers is required to pass through various paths. As the difficulty of robot increases, determining the inverse dynamics is complicated. In this paper, Adaptive Neuro-Fuzzy Inference System (ANFIS) will be applied to explain the inverse dynamics of the 6-DOF Stanford Robotic Arm by training the system by applying data that was saved by the arm robot using rob analyzer software, and after that, the outcome will be analyzed to confirm the model.