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• W4289532713 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." @default.
• W4289532713 created "2022-08-03" @default.
• W4289532713 creator A5021344058 @default.
• W4289532713 creator A5058541397 @default.
• W4289532713 date "2022-06-22" @default.
• W4289532713 modified "2023-09-27" @default.
• W4289532713 title "Using an Adaptive Neuro Fuzzy Inference System to Improve the Calibration Accuracy of Modeless Robots" @default.
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• W4289532713 doi "https://doi.org/10.1109/speedam53979.2022.9841979" @default.
• W4289532713 hasPublicationYear "2022" @default.
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