On the improvement of calibration accuracy of parallel robots – modeling and optimization

• Autorzy: Bentaleb Toufik , Iqbal Jamshed

Identyfikatory

DOI

10.15632/jtam-pl/115863

• Języki publikacji: EN

Abstrakty

EN

This paper proposes kinematic based calibration methods for Delta parallel robots. The boundary of the robot workspace is computed using a forward kinematic model. Influence of errors in kinematic parameters on the workspace boundaries is investigated. The novelty of the proposed approach lies in Jacobian-based computation of kinematic models. Also, the present work extends and applies the existing calibration methods traditionally meant for serial robots on the Delta robot. These methods include the forward method and the inverse method. Simulation results confirm the efficacy of the proposed calibration strategies.

Słowa kluczowe

EN

robot calibration; error analysis; parallel robots; kinematic; modelling

• Wydawca: Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
• Czasopismo: Journal of Theoretical and Applied Mechanics
• Rocznik: 2020
• Tom: Vol. 58 nr 1
• Strony: 261--272
• Opis fizyczny: Bibliogr. 23 poz., rys.

Twórcy

autor

Bentaleb Toufik

• Control Department, LAMIH UMR CNRS 8201 (Laboratory of Industrial and Human Automation Control, Mechanical Engineering and Computer Science), University of Valenciennes, Valenciennes, France

autor

Iqbal Jamshed

• University of Jeddah, College of Engineering, Department of Electrical and Electronic Engineering, Jeddah, Saudi Arabia
• Department of Electrical Engineering, FAST National University, Islamabad, Pakistan

Bibliografia

• 1. Ajwad S.A., Iqbal J., Islam R.U., Alsheikhy A., Almeshal A., Mehmood A., 2018, Optimal and robust control of multi DOF robotic manipulator: Design and hardware realization, Cybernetics and Systems, 49, 1, 77-93.
• 2. Alam W., Mehmood A., Ali K., Javaid U., Alharbi S., Iqbal, J., 2018, Nonlinear control of a flexible joint robotic manipulator with experimental validation, Strojniski vestnik - Journal of Mechanical Engineering, 64, 1, 47-55.
• 3. Axehill J.W., Dressler I., Gunnarsson S., Robertsson A., Norrlöf M., 2014, Estimation-based (ILC) applied to a parallel kinematic robot, Control Engineering Practice, 33, 1-9.
• 4. Bai P., Jiangping Mei J., Tian Huang T., Chetwynd D.G., 2015, Kinematic calibration of Delta robot using distance measurements, Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 230, 3, 414-424.
• 5. Bentaleb T., Shahin L., 2015, Humanoid robots imitation of human motion using offline and real-time adaptation techniques, International Journal of Mechanisms and Robotic Systems, 2, 3/4, 295-313.
• 6. Bentaleb T., Zennadi K., Belouchrani M.E.A., 2007, A new method for self-calibration of the parallel robot “DELTA” using a constrained link, 18th French Congress of French Mechanics, Grenoble, France, 1-6.
• 7. Besnard S., Khalil W., 2001, Identifiable parameters for parallel robots kinematic calibration, IEEE International Conference on Robotics and Automation, 3, 2859-2866.
• 8. Fan C., Zhao G., Zhao J., Zhang L., Sun L., 2015, Calibration of a parallel mechanism in a serial-parallel polishing machine tool based on genetic algorithm, International Journal of Advanced Manufacturing Technology, 81, 27-37.
• 9. Ibrahim O., Khalil W., 2010, Inverse and direct dynamic models of hybrid robots, Mechanism and Machine Theory. 45, 4, 627-640.
• 10. Iqbal J., Ajwad S.A., Abbas S.Z., Khan A.A., Islam R.U., 2016, Automating industrial tasks through mechatronic systems – A review of robotics in industrial perspective, Technicki Vjesnik –Technical Gazette, 23, 3, 917-924.
• 11. Kamali K., Joubair A., Bonev I.A., Bigras P., 2016, Elasto-geometrical calibration of an industrial robot under multidirectional external loads using a laser tracker, IEEE International Conference on Robotics and Automation, Stockholm, Sweden, 4320-4327.
• 12. Mei J., Ni Y., Li Y., Zhang L., Liu F., 2009, The error modeling and accuracy synthesis of a 3-DOF parallel robot delta-S, International Conference on Information and Automation, Zhuhai, Macau, 289-294.
• 13. Meng Y., Zhuang H., 2007, Autonomous robot calibration using vision technology, Robotics and Computer-Integrated Manufacturing, 23, 4, 436-446.
• 14. Merlet J.-P., 2006, Parallel robots, Solid Mechanics and Its Applications, Springer, 128, ISBN: 978-1-4020-4132-7.
• 15. Mo J.S., Qiu C., Zeng L., Zhang X.M., 2016, A new calibration method for a directly driven 3PRR positioning system, Journal of Intelligent & Robotic Systems, 85, 3-4, 613-631
• 16. Nguyen H.N., Zhou J., Kang H.K., 2015, A calibration method for enhancing robot accuracy through integration of an extended Kalman filter algorithm and an artificial neural network, Neurocomputing, 151, 996-1005.
• 17. Nubiola A., Bonev I.A., 2014, Absolute robot calibration with a single telescoping ballbar, Precision Engineering, 38, 472-480.
• 18. Pagis G., Bouton N., Briot S., Martinet P., 2015, Enlarging parallel robot workspace through Type-2 singularity crossing, Control Engineering Practice, 39, 1-11.
• 19. Rauf A., Ryu J., 2001, Fully autonomous calibration of parallel manipulators by imposing position constraint, IEEE International Conference on Robotics and Automation, Proceedings, 3, 2389-2394.
• 20. Viera P., Juraj U., Vladimr B., Peter S., 2011, Delta Robots – Robots for high speed manipulation, Technicki Vjesnik – Technical Gazette, 18, 3, 435-445.
• 21. Yu D.Y., 2008, Parallel robots pose accuracy compensation using artificial neural networks, IEEE International Conference on Mechatronics and Automation, Takamatsu, 750-754.
• 22. Yu D.Y., Cong D.C., Han J.W., 2005, Parallel robots pose accuracy compensation using artificial neural networks, International Conference on Machine Learning and Cybernetics, 5, 3194-3198.
• 23. Zhao L., Joubair A., Bigras P., Bonev I.A., 2015, Metrological evaluation of a novel medical robot and its kinematic calibration, International Journal of Advanced Robotic Systems, 12, 9, 1-13.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).