Modeling and Simulation of Robotic Arm Movement using Soft Computing

Authors: V. K. Banga, Jasjit Kaur, R. Kumar, Y. Singh

Abstract:

In this research paper we have presented control architecture for robotic arm movement and trajectory planning using Fuzzy Logic (FL) and Genetic Algorithms (GAs). This architecture is used to compensate the uncertainties like; movement, friction and settling time in robotic arm movement. The genetic algorithms and fuzzy logic is used to meet the objective of optimal control movement of robotic arm. This proposed technique represents a general model for redundant structures and may extend to other structures. Results show optimal angular movement of joints as result of evolutionary process. This technique has edge over the other techniques as minimum mathematics complexity used.

Keywords: Kinematics, Genetic algorithms (GAs), Fuzzy logic(FL), Optimal control.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1328582

References:

[1] C. F. Olson, Lab. JP, Technol. CIo, Pasadena, "Probabilistic selflocalization for mobile robots"; IEEE Transactions on Robotics and Automation 16,1, 55-66, 2000.
[2] R.B. Gillespie, J. E. Colgate, M. A. Peshkin, "A general framework for robot control"; IEEE Transactions on Robotics and Automation, 17,4, 391-401, 2001.
[3] Devendra P. Garg and Manish Kumar, "Optimization Techniques applied to multiple manipulators for path planning and torque minimization"; Engineering Applications of Artificial Intelligence 15, 3- 4, 241-252, 2002.
[4] J. C. Trinkle and R. James Milgram, "Complete Path Planning for Closed Kinematics Chains with Spherical Joints"; SAGE International Journal of Robotic Research 21, 9, 773-789, 2002.
[5] M. Gemeinder and M. Gerke, "GA-based Path Planning for Mobile Robot Systems employing an active Search Algorithm"; Journal of Applied Soft Computing 3, 2, 149-158, 2003.
[6] P. Th. Zacharia and N. A. Aspragathos, "Optimal Robot task scheduling based on Genetic Algorithms"; Elsevier Robotics and Computer- Integrated Manufacturing 21, 67-79, 2005.
[7] V. B. Nguyen and A. S. Morris, "Genetic Algorithm Tuned Fuzzy Logic Controller for a Robot Arm with Two-link Flexibility and Two-joint Elasticity"; Springer J Intell Robot Syst. 49, 3-18, 2007.
[8] M. Mucientes, D. L. Moreno, "A. Bugarín and S. Barro, Design of a fuzzy controller in mobile robotics using genetic algorithms"; Elsevier Applied Soft Computing 7, 2, 540-546, 2007.
[9] Momotaz Begum, George K. I. Mann, Raymond G. Gosai, "Integrated fuzzy logic and genetic algorithmic approach for simultaneous localization and mapping of mobile robots"; Elsevier Applied Soft Computing 8, 1, 50-165, 2008.
[10] L. Doitsidis, N. C. Tsourveloudis, S. Piperidis, "Evolution of Fuzzy Controllers for Robotic Vehicles: The Role of Fitness Function Selection"; Springer J. Intell. Robot Syst. 56, 469-484, 2009.