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Modeling of Multi-DOF Robotic Manipulators using Sim-Mechanics Software


  • Department of Mechanical Engineering, TheNorthCap University, Gurugram – 122017, Haryana, India


Objectives: This paper presents a simulation based software platform to model and design a multi-degree of freedom robotic manipulator. Methods: Traditional methods of modeling robotic manipulators are a very laborious, iterative and time consuming task. In the last few years, new approaches towards the study of complex architectures of robotic manipulators have developed rapidly. In this paper, a new method based on Sim-Mechanics software is presented to simulate and design a multi-DOF robotic manipulator. Findings: It can be seen that the new software based method provides a much easier and faster way of modeling the multi-DOF robotic manipulator as compared to mathematical modeling. Improvements: The model developed using Sim-Mechanics software will be further used for dynamic analysis.


DOF, Dynamics, Modeling, Robotic Manipulator, Sim-Mechanics.

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  • Denavit J, Hartenberg R. S. A kinematic notation for lower pair mechanisms based on matrices. Transactions of ASME Journal of Applied Mechanics. 1955; 23: 215-221.
  • R.K. Mittal, I.J. Nagrath, “Robotics and Control”, Tata Mc Graw Hill Publishing Company Limited, New Delhi, India, pp. 1-487, 2003.
  • S. K. Saha, “Introduction to Robotics”, Tata McGraw Hill, pp.1-425, 2008.
  • Manseur R. A software package for computer-aided robotics education. Proceedings of 26th Annual Conference on Frontiers in Education. 1996; 3: p. 1409-1412.
  • Koyuncu B, Guzel M. Software Development for the Kinematic Analysis of a Lynx 6 Robot Arm. International Journal of Engineering and Applied Sciences. 2008; 4(4): 230-235.
  • Silva A. J, Ramirez O. A, Vega V. P, Oliver J. P. O. Phantom omni haptic device: Kinematic and manipulability. IEEE Conference on Electronics, Robotics and Automotive Mechanics. 2009: p. 193-198.
  • Duka A.V. ANFIS Based Solution to the Inverse Kinematics of a 3DOF Planar Manipulator. Procedia Technology. 2015; 19: p. 526-533.
  • Nil M, Yuzgec U, Sonmez M, Cakir B. Fuzzy Neural Network based Intelligent Controller for 3-DOF Robot Manipulators. Proceedings of 5th International Symposium on Intelligent Manufacturing Systems. 2006: p.884-895.
  • Alavandar S, Nigam M. J. Neuro-fuzzy based approach for inverse kinematics solution of industrial robot manipulators. International Journal of Computers, Communications & Control. 2008; 3(3): 224-234.
  • Manjaree S, Nakra B. C, Agarwal V. Comparative Analysis for Kinematics of 5-DOF Industrial Robotic Manipulator. Acta Mechanica et Automatica. 2015; 9 (4): 229-240.
  • Das, L., 2012. Prediction of Inverse Kinematics Solution of a redundant manipulator using ANFIS (Doctoral dissertation).
  • Jain A, Jagotra D, Agarwal V. Implementation and Validation of Artificial Intelligence Techniques for Robotic Surgery. International Journal of Advanced Computer Research. 2014; 4(1): 39.
  • Choi, B.B. and Lawrence, C. Inverse kinematics problem in robotics using neural networks. 1992.
  • Manjaree S, Nakra B. C, Agarwal V. Inverse Kinematics of 3-DOF Robotic Manipulator using Analytical method, ANFIS method and experiments. Accepted by International Journal of Mechanisms and Robotic Systems, Inderscience and currently in Press.
  • Manjaree S, Agarwal V, Nakra B.C. Kinematic Analysis Using Neuro-Fuzzy Intelligent Technique for Robotic Manipulator. International Journal of Engineering Research and Technology. 2013; 6 (4): 557-562.
  • Manjaree S, Agarwal V, Nakra B. C. Inverse Kinematics Using Neuro-Fuzzy Intelligent Technique for Robotic Manipulator. International Journal of Advanced Computer Research. 2013; 3 (4), issue 13: 160-165.
  • Wang J, Li Y. Comparative analysis for the inverse kinematics of redundant manipulators based on repetitive tracking tasks. IEEE International Conference on Automation and Logistics. 2009: p. 164-169.
  • Li, S., 1996. Dynamic Optimization of An N Degree-of-Freedom Robot System (Doctoral dissertation, Ohio University).
  • Al-Dois H. A, Jha A. K, Mishra R. B. Investigations into the parameters influencing the dynamic performance of 3-RRR planar & articulated robot manipulators. Tamkang Journal of Science and Engineering. 2011; 14(4): 313-322.
  • Lin C T, Lee C S G. Neural-Network-based fuzzy logic control and decision system. IEEE Transaction on Computer. 1991; 40: 1320-1336.
  • Lin C T, Lee C S G. Real time supervised structure-parameter learning for fuzzy neural network. Proceeding of IEEE International Conference on Fuzzy Systems. 1992: p. 1283-1290.
  • Lin C T, Lee C S G. Reinforced structure-parameter learning for neural-network-based fuzzy logic control systems. Proceeding of IEEE International Conference on Fuzzy Systems. 1993: p. 88-93.
  • Lin C T, Lee C S G. A neural fuzzy control system with structure and parameter learning. Fuzzy Sets and Systems. 1995; 70: 183-212.
  • Luca A. D, Siciliano B. Closed-form dynamic model of planar multilink lightweight robots. IEEE Transactions on Systems, Man and Cybernetics. 1991; 21(4): 826-839.
  • Patel Y. D, George P. M. Performance Measurement and Dynamic Analysis of two dof robotic arm manipulator. International Journal of Research in Engineering and Technology. 2013; 2(9): 77-79.
  • Giles D. Wood. Simulating mechanical systems in simulink with simmechanics. Technical report, The MathWorks, Inc., 3 Apple Hill Drive, Natick, MA, USA, 2003.
  • Shaoqiang Y, Zhong L, Zhingshan L. Modeling and Simulation of Robot based on MATLAB/SimMechanics. Proceedings of 27th Chinese Control Conference. Kunming, Yunnan, China. 2008.
  • Dung L. T, Kang H. J, Ro Y. S, ‘Robot manipulator modeling in Matlab/Sim-Mechanics with PD control and online gravity compensation. Proceedings of International Forum on Strategic Technology. 2010.
  • Zheng-Wen L, Guo-liang Z, Wei-ping Z, Bin J. A simulation platform design of Humanoid robot based on SimMechanics and VRML. Procedia Engineering. 2011; 15: p. 215-219.
  • Fedák V, Ďurovský F, Üveges R. Analysis of Robotic System Motion in SimMechanics and MATLAB GUI Environment. MATLAB Applications for the Practical Engineer. 2014
  • Schlotter, M., 2003. Multibody System Simulation with SimMechanics. University of Canterbury.


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