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Trajectory Planning and Obstacle Avoidance Control of Redundant Robots Using Differential Evolution and Particle Swarm Optimization Algorithms

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Swarm, Evolutionary, and Memetic Computing (SEMCCO 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8947))

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Abstract

The problem of trajectory planning and obstacle avoidance in redundant robots is addressed in this paper. Four variants of Particle Swarm Optimization (PSO) and a Differential Evolution (DE) algorithm are proposed to solve this problem. Simulation experiments on a 5 degree-of-freedom (DOF) robot manipulator in an environment with static obstacles are conducted. The manipulator is required to move from a start position to a goal position with minimum error while avoiding collision with the obstacles in the workspace. The performance of the proposed algorithms is compared with the results reported in the literature and the comparative results are presented. It is observed that qPSO-C performs better in free space and PSO-C performs better in environment with obstacles in terms of minimizing error average convergence time. The performance of DE improves when the number of obstacles increases.

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References

  1. Kim, S.W., Lee, J.J.: Resolved motion rate control of redundant robots using an adaptive fuzzy logic. Second IEEE International Conference on Fuzzy Systems, pp. 333–338(1993)

    Google Scholar 

  2. Beheshti, M.T.H., Tehrani, A.K.: Obstacle avoidance for kinematically redundant robots using an adaptive fuzzy logic algorithm. In: Proceedings of the American Control Conference, vol. 2, pp. 1371–1375 (1999)

    Google Scholar 

  3. Nearchou, A.C.: Solving the inverse kinematics problem of redundant robots operating in complex environments via a modified genetic algorithm. Mech. Mach. Theory 33(3), 273–292 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  4. Secară, C., Vlădăreanu, L.: Iterative genetic algorithm based strategy for obstacles avoidance of a redundant manipulator. In: Proceedings of American Conference on Applied Mathematics, Stevens Point, pp. 361–366, USA (2010)

    Google Scholar 

  5. Zhang, Y., Wang, J.: Obstacle avoidance for kinematically redundant manipulators using a dual neural network. IEEE Trans. Syst. Man Cybern. Part B: Cybern. 34(1), 752–759 (2004)

    Article  Google Scholar 

  6. Price, K., Storn, R.: Differential evolution – a simple and efficient heuristic for global optimization over continuous spaces. J. Global Optim. II, 341–359 (1997)

    MathSciNet  Google Scholar 

  7. Liu, Yu., Ni, F.-l., Liu, H., Wen-fu, X.: Enhancing pose accuracy of space robot by improved differential evolution. J. Cent. South Univ. 19, 933–943 (2012)

    Article  Google Scholar 

  8. Saravanan, R., Ramabalan, S., Balamurugan, C.: Evolutionary collision-free optimal trajectory planning. Int. J. Adv. Manuf. Technol. 36, 1234–1251 (2008)

    Article  Google Scholar 

  9. Gang, H., Li, D., Yang, J.: A research on particle swarm optimization and its application in robot manipulators. In: Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA, vol. 2, pp. 377–381 (2008)

    Google Scholar 

  10. Eberhart, R.C., Kennedy, J.: A new optimizer using particle swarm theory. In: Proceedings of the Sixth International Symposium on Micro Machine and Human Science, vol. 1, pp. 39–43 (1995)

    Google Scholar 

  11. Wen, X., Sheng, D., Huang, J.: A Hybrid Particle Swarm Optimization for Manipulator Inverse Kinematics Control. In: Huang, D.-S., Wunsch II, D.C., Levine, D.S., Jo, K.-H. (eds.) ICIC 2008. LNCS, vol. 5226, pp. 784–791. Springer, Heidelberg (2008)

    Google Scholar 

  12. Donelan, P.S.: Singularities of robot manipulators. Singul. Theory, pp. 189–217 (2007)

    Google Scholar 

  13. Desa, S.M., Qussay, A.S.: Image subtraction for real time moving object extraction. In: International Conference on Computer Graphics, Imaging and Visualization, CGIV 2004. Proceedings, pp. 41–45 (2004)

    Google Scholar 

  14. Qidwai, U., Chi-hau, C.: Digital image processing: an algorithmic approach with MATLAB. Chapman & Hall/CRC, London (2009)

    Google Scholar 

  15. Chyan, G.S., Ponnambalam, S.G.: Obstacle avoidance control of redundant robots using variants of particle swarm optimization. Rob. Comput.-Integr. Manuf. 28(2), 147–153 (2012)

    Google Scholar 

  16. Hartenberg, R.S., Denavit, J.: A kinematic notation for lower-pair mechanisms based on matrices. ASME Journal of Applied Mechanics 22(77), 215–221 (1995)

    MathSciNet  Google Scholar 

  17. Eberhart, R.C., Kennedy, J.: A new optimizer using particle swarm theory. In: Proceedings of the sixth international symposium on micro machine and human science, vol. 1, pp. 39–43 (1995)

    Google Scholar 

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Author information

Authors and Affiliations

  1. MAS Unichela Pvt. Ltd., no. 124, Horana Road, Panadura, Srilanka

    Sujan Warnakulasooriya

  2. Advanced Engineering Platform and School of Engineering, Monash University Malaysia, 46150, Bandar Sunway, Malaysia

    S. G. Ponnambalam

Authors
  1. Sujan Warnakulasooriya
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  2. S. G. Ponnambalam
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Corresponding author

Correspondence to S. G. Ponnambalam .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, IIT, New Delhi, India

    Bijaya Ketan Panigrahi

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Ponnuthurai Nagaratnam Suganthan

  3. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, India

    Swagatam Das

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Warnakulasooriya, S., Ponnambalam, S.G. (2015). Trajectory Planning and Obstacle Avoidance Control of Redundant Robots Using Differential Evolution and Particle Swarm Optimization Algorithms. In: Panigrahi, B., Suganthan, P., Das, S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2014. Lecture Notes in Computer Science(), vol 8947. Springer, Cham. https://doi.org/10.1007/978-3-319-20294-5_51

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  • DOI: https://doi.org/10.1007/978-3-319-20294-5_51

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20293-8

  • Online ISBN: 978-3-319-20294-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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