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Tytuł artykułu

Comparative analysis for kinematics of 5-DOF industrial robotic manipulator

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper gives the kinematic analysis of a 5-DOF industrial robotic manipulator while considering wrist in motion. Analytical solutions have been obtained for forward kinematics and inverse kinematics to accurately position the end-effector of robotic manipulator in three dimensional spaces. For the first time, a hybrid neuro-fuzzy intelligent technique with two different membership functions has been studied and their performances are comparatively evaluated with analytical solutions. An experiment has been performed for a desired trajectory. It is seen that the results for the intelligent technique are reasonably in agreement with experiment. Also, the results obtained highlight the importance of selection of a particular membership function for robotic manipulators of industrial use.
Rocznik
Strony
229--240
Opis fizyczny
Bibliogr. 32 poz., rys., tab., wykr.
Twórcy
autor
  • Department of Mechanical Engineering, The Northcap University (Formerly ITM University), Sector 23 A, Gurgaon, India
autor
  • Department of Mechanical Engineering, IIT Delhi, Hauz Khas, New Delhi, India
autor
  • Department of MPAE, NSIT, Sector 3, Dwarka, New Delhi, India
Bibliografia
  • 1. Aghajarian M., Kiani K. (2011), Inverse Kinematics Solution of PUMA 560 Robot Arm using ANFIS, 8th International Conference on Ubiquitous Robots and Ambient Intelligence, Songdo Conventia, Korea.
  • 2. Agarwal V., Mittal A.P., Nakra B.C. (2005), A Study of Fuzzy Logic Based Inverse Kinematics Solution, Proceedings of International Conference on Computer Applications in Electrical Engineering, IIT Roorkee, India.
  • 3. Alavander S., Nigam M.J. (2008), Inverse Kinematics Solution of 3- DOF Planar Robot using ANFIS, International Journal of Computers, Communication and Control, 3,150-155.
  • 4. Azadivar F. (1987), The Effect of Joint Position Errors of Industrial Robots on Their Performance in Manufacturing Operations, IEEE Journal of Robotics and Automation, RA-3 (2), 109-114.
  • 5. Bachir O., Zoubir A. (2012), Adaptive Neuro-fuzzy Inference System based Control of PUMA 600 Robot Manipulator, International Journal of Electrical and Computer Engineering, 2 (1), 90-97.
  • 6. Bingul Z, Karahan O. 2011, A Fuzzy Logic Controller tuned with PSO for 2 DOF robot trajectory control, Expert Systems with Applications, 38, 1017-1031.
  • 7. Chen C, Wu T, Peng C. 2010, Robust trajectories following control of a 2-link robot manipulator via coordinate transformation for manufacturing applications, Robotics and Computer-Integrated Manufacturing, 27, 569-580.
  • 8. Conkur E. (2003), Path following algorithm for highly redundant manipulators, Robotics and Autonomous Systems, 45, 1-22.
  • 9. Corke P.I. (2011), Robotics Toolbox for MATLAB (Release 9), http://petercorke.com/Robotics_Toolbox.html.
  • 10. Denavit J, Hartenberg R.S. (1955), A kinematic notation for lower pair mechanisms based on matrices, ASME Journal of Applied Mechanics, 77, 215-221.
  • 11. Efe M.O., Kaynak O. (2000), A comparative study of soft-computing methodologies in identification of robotic manipulators, Robotics and Autonomous Systems, Elsevier, 30, 221-230.
  • 12. Elgazzar S. (1985), Efficient Kinematic Transformations for the PUMA 560 Robot, IEEE Journal of Robotics and Automation, RA-1 (3),142-151.
  • 13. Er M.J., Yap S.M., Yeaw C.W., Luo F.L. (1997), A Review of NeuralFuzzy Controllers for Robotic Manipulators, Conference Record of the IEEE Industry Applications.
  • 14. Gasparetto A, Zanotto V. (2007), A new method for smooth trajectory planning of robotic manipulators, Mechanism and Machine Theory, 42, 455-471.
  • 15. Homaifar A, Sayyarrodsari B, Hogans J. (1994), Fuzzy Controller for Robot Arm Trajectory, Information Sciences, 2, 69-83.
  • 16. Jang J.S.R. (1993), ANFIS: Adaptive Network based Fuzzy Inference System. IEEE Transactions on Systems, Man and Cybernetics, 665-685.
  • 17. Karlik B, Aydin S. (2000), An improved approach to the solution of inverse kinematics problems for robot manipulators, Engineering Applications of Artificial Intelligence, 13, 159-164.
  • 18. Kim W.S., Tendick F., Stark L.W. (1987), Visual Enhancements in Pick-and-Place Tasks: Human Operators Controlling a Simulated Cylindrical Manipulator, IEEE Journal of Robotics and Automation, RA-3 (5), 418-425.
  • 19. Koyuncu B., Guzel M. (2007), Software development for the kinematic control of Lynx6 Robot Arm, World Academy of Science, Engineering and Technology, 252-257.
  • 20. Kuo C, Wang S. (1991), Robust Position Control of Robotic Manipulator in Cartesian Coordinates, IEEE Transactions on Robotics and Automation, 7, 653-659.
  • 21. Manjaree S., Shah J., Nakra B.C. (2010), Studies on Kinematics of Robotic Systems Using Artificial Intelligence Techniques, M Tech Thesis, Maharishi Dayanand University, Rohtak.
  • 22. Manjaree S. (2013), Inverse Kinematic Analysis of 3-degree-offreedom Robotic Manipulator using three different methods, International Journal of Advances in Science and Technology, 6(3), 71-80.
  • 23. Manjaree S., Agarwal V., Nakra B.C. (2013), Inverse Kinematics using Neuro-Fuzzy Intelligent Technique for Robotic Manipulator, International Journal of Advanced Computer Research, 3(4), 160-165.
  • 24. Manseur R. (1996), A software package for computer-aided robotics education, Proceedings of 26th Annual Conference on Frontiers in Education, Salt Lake City, UT.
  • 25. Mittal R.K., Nagrath I.J. (2003), Robotics and Control, Tata Mc Graw Hill Publishing Company Limited.
  • 26. Mohan S., Bhanot S. (2007), Comparative Study of Some Adaptive Fuzzy Algorithms for Manipulator Control, International Journal of Computational Intelligence, 3(4), 303-311.
  • 27. Niku S.B. (2009), Introduction to Robotics: Analysis, Systems, Applications, PHI Learning Private Limited, India.
  • 28. Pravak Manual (2008), Model 1055, Pravak Cybernetics, New Delhi.
  • 29. Saha S.K. (2008), Introduction to Robotics, Tata McGraw Hill Education Private Limited.
  • 30. Shah J., Rattan S.S., Nakra B.C. (2013), End-Effector Position Analysis Using Forward Kinematics For 5 Dof Pravak Robot Arm, IAES International Journal of Robotics and Automation, 2(3), 112-116.
  • 31. Tejomurtula S., Kak S. (1999), Inverse kinematics in robotics using neural networks, Information Sciences, Elsevier, 116 (2), 147-164.
  • 32. Yahya S., Moghavvemi M, Haider A.F. Mohamed (2011), Geometrical approach of planar hyper-redundant manipulators: Inverse kinematics, trajectory planning and workspace, Simulation Modeling Practice and Theory, 19, 406-422.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-dc61db67-0b60-4b15-93b0-4ed3beb1c5d4
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