Using an Adaptive Neuro Fuzzy Inference System to Improve the Calibration Accuracy of Modeless Robots

Abstract

This paper is our extended research described a technique used for position error compensations of the robot and manipulator calibration process based on an Adaptive Neuro Fuzzy Inference System (ANFIS) method. Traditional robots calibration implements either model or modeless method. The compensation of position error in modeless method is to move the robot’s end-effector to a target position in the robot workspace, and to find the target position error based on the measured neighboring 4-point errors around the target position. A camera or other measurement device is attached on the robot’s end-effector to find and measure the neighboring position errors, and compensate the target position with the error interpolation results. By using the ANFIS technique provided in this paper, the accuracy of the position error compensation can be greatly improved, which has been confirmed by the simulation results given in this paper. Compared with some other popular traditional interpolation methods, this ANFIS technique is a better choice. The simulation results show that more accurate compensation result can be achieved using this technique compared with the interval type-2 fuzzy interpolation method.