Absolute Positioning Error Modeling and Compensation of a 6-DOF Industrial Robot

He, Zhenya; Zhang, Ruian; Zhang, Xianmin; Chen, Zhong; Huang, Guojian; Zhou, Antai

doi:10.1109/robio49542.2019.8961386

Cited by 3 publications

(2 citation statements)

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“…The second method is to implement an absolute position feedback control, usually relying on external sensors [3][4][5]. Most commonly, the tool is tracked by an exteroceptive sensor (for instance, a laser tracker [6], an encoder [7] or a 3D camera [8,9]), and the position feedback enables real-time compensation for the robot's inaccuracy. This method achieves up to a 70% accuracy improvement by using a laser tracker with heavy-duty robots [6].…”

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confidence: 99%

“…Most commonly, the tool is tracked by an exteroceptive sensor (for instance, a laser tracker [6], an encoder [7] or a 3D camera [8,9]), and the position feedback enables real-time compensation for the robot's inaccuracy. This method achieves up to a 70% accuracy improvement by using a laser tracker with heavy-duty robots [6]. Another use of position feedback is to perform deformation-tracking impedance control coupled with an Extended Kalman Filter [10].…”

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confidence: 99%

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Elasto-Geometrical Model-Based Control of Industrial Manipulators Using Force Feedback: Application to Incremental Sheet Forming

et al. 2022

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This paper aims to improve the positioning accuracy of serial industrial manipulators using force feedback in manufacturing processes by implementing an elasto-geometrical model-based control. Initially, the real-time position control strategy using a force feedback to elastically correct the Tool Center Point (TCP) pose of serial industrial manipulators is detailed. To continue, an efficient model structure identification and calibration is proposed to shorten the elasto-geometrical modeling process. The Virtual Joint Method (VJM) is chosen to iterate and complete the robot stiffness modeling. This method considers that the elastic deformations are only localized at the joints of the robot. An appropriate and original test-model approach allows a minimum of optimization iterations to find the best compromise between complexity and accuracy of the modeling. The proposed approach is illustrated in detail by the Stäubli TX200 robot modeling. Finally, the reliability and responsiveness of the developed control framework is then evaluated through experimental tests in an Incremental Sheet Forming (ISF) context. An average improvement of 70% in trajectory-tracking accuracy is achieved during these tests. Overall, the high accuracy and responsiveness of the developed system demonstrate a promising potential for deploying industrial manipulators to a cost-effective manufacturing processes in industry 4.0.

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