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Intelligent controll of the gripping force of an object by two computer-controlled cooperative robots

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Języki publikacji
EN
Abstrakty
EN
This paper presents a method based on Multiple Adaptive Neuro-Fuzzy Inference System (MANFIS) to regulate the handling force of a common object. The foundation of this method is the prediction of the inverse dynamics of a cooperative robotic system made up of two 3-DOF robotic manipulators. Considering the lack of slippage in the contact between the tool and the object, the object is moved. To create and feed the MANFIS database, the inverse kinematics and dynamic equations of motion for the closed chain of motion for both arms are established in Matlab. Results from a SimMechanic simulation are given to demonstrate how well the suggested MANFIS controller works. Several manipulated object movements covering the shared work¬space of the two manipulator arms are used to test the proposed control strategy. The simulation results indicate that the proposed control strategy is effective in regulating the handling force of a common object with varying desired forces, and does not require the use of force sensors on the object-tool contact.
Rocznik
Strony
133--151
Opis fizyczny
Bibliogr. 18 poz., fig., tab.
Twórcy
  • Department of Mechanical Engineering, ENSET Mohammedia, Hassan II University of Casablanca, Morocco
  • Department of Mechanical Engineering, ENSET Mohammedia, Hassan II University of Casablanca, Morocco
autor
  • Department of Mechanical Engineering, ENSET Mohammedia, Hassan II University of Casablanca, Morocco
  • Department of Mechanical Engineering, ENSET Mohammedia, Hassan II University of Casablanca, Morocco
  • Department of Mechanical Engineering, ENSET Mohammedia, Hassan II University of Casablanca, Morocco
Bibliografia
  • [1] Arian, A., Danaei, B., Abdi, H., & Nahavandi, S. (2017). Kinematic and dynamic analysis of the Gantry-Tau, a 3-DoF translational parallel manipulator. Applied Mathematical Modelling, 51, 217-231. https://doi.org/10.1016/j.apm.2017.06.012
  • [2] Azadi, M., Eghtesad, M., & Gharesifard, B. (2005). Inverse Dynamics Control of Two 5 DOF Cooperating Robot Manipulators. Proceedings of the ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 4a: ASME/IEEE Conference on Mechatronic and Embedded Systems and Applications (pp. 187-193). ASME. https://doi.org/10.1115/DETC2005-85634
  • [3] Azizian, K. (2001). Position control of two robots manipulating a rigid plate. Shiraz University.
  • [4] Bahani, A., Ech-Chhibat, E. H., Samri, H., & El Attar, H. A. (2022). Intelligent Modeling and Simulation of the inverse Kinematics Redundant 3-Dof Cooperative Using SolidWorks and MATLAB/Simmechanics. International Journal on Technical and Physical Problems of Engineering (IJTPE), 50(14), 78-88.
  • [5] Esen, H., Inalli, M., Sengur, A., Esen, M. (2008). Artificial neural networks and adaptive neuro-fuzzy assessments for ground-coupled heat pump system. Energy and Buildings, 40(6), 1074-1083. https://doi.org/10.1016/j.enbuild.2007.10.002
  • [6] Han, J., Wang, F., & Sun, C. (2023). Trajectory Tracking Control of a Manipulator Based on an Adaptive Neuro-Fuzzy Inference System. Applied Sciences, 13(2), 1046. http://dx.doi.org/10.3390/app13021046
  • [7] Hayati, S. (1986). Hybrid position-force control of multi arm cooperating robots. Proceedings. 1986 IEEE International Conference on Robotics and Automation (pp. 82-89). IEEE. https://doi.org/10.1109/ROBOT.1986.1087650
  • [8] Herrero, S., Pinto, C., Altuzarra, O., & Diez, M. (2018). Analysis of the 2PRU-1PRS 3DOF parallel manipulator: kinematics, singularities and dynamics. Robotics and Computer-Integrated Manufacturing, 51, 63-72. https://doi.org/10.1016/j.rcim.2017.11.018
  • [9] Hsu, P. (1989). Control of multi-manipulator system-trajectory tracing, load distribution, internal force control, and the decentralized architecture. Proceedings, 1989 International Conference on Robotics and Automation (pp. 1234-1239). IEEE. https://doi.org/10.1109/ROBOT.1989.100149
  • [10] Hu, Y. R., & Goldenberg, A. A. (1989). An adaptive approach to motion and force control of multiple coordinated robots arms. Proceedings, 1989 International Conference on Robotics and Automation (pp. 1091-1096). IEEE. https://doi.org/10.1109/ROBOT.1989.100126
  • [11] Ivanov, S., Meleshkova, Z., & Ivanovа, L. (2020). Calculation and Optimization of Industrial Robots Motion. 2020 26th Conference of Open Innovations Association (FRUCT) (pp. 115-123). IEEE. https://doi.org/10.23919/FRUCT48808.2020.9087376
  • [12] Jang, J. S. R. (1993). ANFIS: Adaptive-Network-Based Fuzzy Inference System. IEEE Transactions on Systems Man & Cybernetics, 23(3), 665-685. https://doi.org/10.1109/21.256541
  • [13] Jha, P., Biswal, B. B., & Sahu, O. P. (2015). Inverse Kinematic Solution of Robot Manipulator Using Hybrid Neural Network. International Journal of Materials Science and Engineering, 3(1), 31-38. https://doi.org/10.12720/ijmse.3.1.31-38
  • [14] Kawazaki, H., Ito, S., & Ramli, R. B. (2003). Adaptative desentralised coordinated control of multiple robot arms. IFAC robot control, 36(17), 387-392. https://doi.org/10.1016/S1474-6670(17)33425-0
  • [15] Klein, C. A., & Kittivatcharapong, S. (1990). Optimal force distribution for the legs of a walking machine with friction cone constraints. IEEE Trans. on Robotics and Automation, 6(1), 73–85. https://doi.org/10.1109/70.88119
  • [16] Liu, F., Gao, G., Shi, L., & Lv, Y. (2017). Kinematic analysis and simulation of a 3-DOF robotic manipulator. In 2017 3rd International Conference on Computational Intelligence & Communication Technology (pp. 1-5). IEEE. https://doi.org/10.1109/CIACT.2017.7977291
  • [17] Mahfoudi, C., Djouani, K., Rechak, S., & Bouaziz, M. (2003). Optimal force distribution forthe legs of an hexapod robot. Proceedings of 2003 IEEE Conference on Control Applications (vol.1, pp. 657-663). IEEE. https://doi.org/10.1109/CCA.2003.1223515
  • [18] Walker, M.W., Kim, D., & Dionise, J. (1989). Adaptive coordinated motion control of two manipulators arms. Proceedings, 1989 International Conference on Robotics and Automation (pp. 1084-1090). IEEE. https://doi.org/10.1109/ROBOT.1989.100125
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-341e6bf3-ee27-4b03-9ad4-186b5ac854a8
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