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Neural network approach to trajectory synthesis for robotic manipulators

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Abstract

The paper deals with the collision free trajectory synthesis for industrial robotic manipulators. A new efficient method is proposed that is based on a neural network collision model. The developed iterative transformation procedure provides small computing times for the C-space synthesis and yields sufficiently precise configuration space map for the manipulators with many degrees of freedom. A topologically ordered neural network model is proposed to find the path in the configuration space. The stability of this model is proved using the Lyapunov function technique. To generate the collision model, a modification of the Radial Basis Function Network (RBFN) is used. The developed technique is illustrated by an application example of designing a robotic manufacturing cell for the automotive industry.

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References

  • Althoefer, K., Fraser, D. A., Bugmann, G. and Plumbley, M. D. (1995) Asymmetric B-splines for the fast calculation of C-space patterns of robot arms, in Proceedings of the 5th International Conference on Artificial Neural Networks, Paris, France, pp. 387–382

  • Althoefer, K. (1996) Neuro-Fuzzy Motion Planning for Robotic Manipulators, Ph.D. Thesis, Department of Electronic and Electrical Engineering, King’s College, London

  • N. M. Amato O. B. Bayazit L. K. Dale C. Jones D. Vallejo (2000) ArticleTitleChoosing good distance metrics and local planners for probabilistic roadmaps methods IEEE Transaction on Robotic and Automation 16 IssueID4 442–447

    Google Scholar 

  • Arik, S. and Tavsanoglu, V. (1996) Absolute stability of nonsymmetric neural networks, in Proceedings of the 1996 IEEE International Symposium on Circuits Systems, Atlanta, Georgia, USA, pp. 441–444

  • Arik, S. (1998) Global stability of a large class of dynamic neural network, in Proceedings of the 1998 IEEE International Symposium on Circuits Systems, Monterey, USA, pp.187–190

  • E. Blanzieri (1998) Learning Algorithms for Radial Basis Function Networks: Synthesis, Experiments and Cognitive Modeling Center of Cognitive Science, University and Polytechnic Turin

    Google Scholar 

  • Bohlin, R. and Kavraky, L. (2001) A randomized algorithm for robot path planning based on lazy evaluation, in Handbook on Randomized Computation, S. Rajasekarn, P. Pardalos and J. Rolim (eds.), Kluwer Academic Publishers, , pp. 221--249.

  • N. K. Bose P. Liang (1996) Neural Networks Fundamentals: Graphs, Algorithms McGraw-Hill Book Company New York

    Google Scholar 

  • G. Bugmann J. G. Tylor M. J. Denham (1995) Route finding by neural nets J. G. Tylor (Eds) Neural Networks Alfred Waller Ltd Henley-on-Thames, UK 217–230

    Google Scholar 

  • Branicky, M., LaValle, S. M., Olsen, K. and Yang, L. (2001) Quasi-randomized path planning, in Proceedings of IEEE International Conference on Robotic and Automation, Seoul, Korea, pp. 1481–1487

  • W. Brown C. Harris (1994) Neurofuzzy Adaptive Modeling and Control Prentice Hall International Ltd. UK

    Google Scholar 

  • C. I. Connolly J. B. Burnas (1993) ArticleTitleA model for the functioning of the striatum Biological Cybernetics 68 IssueID6 535–544

    Google Scholar 

  • Y. Fang T. G. Kincaid (1996) ArticleTitleStability analysis of dynamical neural networks IEEE Transactions on Neural Networks 7 IssueID4 1996–1006

    Google Scholar 

  • Geraerts, R. and Overmars, M. H. (2002) A comparative study of probabilistic roadmap planners, in Proceedings of Workshop on Algorithmic Foundations of Robotics, Nice, France, pp. 43–57

  • Glasius, R., Komoda, A. and Gielen, S. (1993) Biologically inspired neural network for trajectory formation and obstacle avoidance, in Proceedings of the International Conference on Artificial Neural Networks, S. Gielen and B. Kappen (eds.), Springer-Verlag, , pp. 281--284.

  • R. Glasius A. Komoda S. Gielen (1995) ArticleTitleNeural network dynamics for path planning and obstacle avoidance Neural Networks 8 IssueID1 125–133

    Google Scholar 

  • Z. Guan G. Chen Y. Qin (2000) ArticleTitleOn equilibria, stability, and instability of Hopfield neural networks IEEE Transactions on Neural Networks 11 IssueID2 534–540

    Google Scholar 

  • K. K. Gupta Z. Guo (1995) ArticleTitleMotion planning for many degrees of freedom: sequential search with backtracking IEEE Transactions on Robotics and Automation 11 IssueID6 897–906

    Google Scholar 

  • L. Kavraky P. Svestka J. C. Latombe M. Overmars (1996) ArticleTitleProbabilistic roadmaps for path planning in high dimensional configuration space IEEE Transactions Robotics and Automation 12 IssueID4 566–580

    Google Scholar 

  • J. C. Latombe (1991) Robot Motion Planning Kluwer Academic Publishers Boston, MA

    Google Scholar 

  • S. M. LaValle J. J. Kuffner (2001) Rapidly-exploring random trees: progress and prospects B. R. Donald K. M. Lynch D. Rus (Eds) Algorithmic and Computational Robotics: New Directions AK Peters Wesley 293–308

    Google Scholar 

  • T. Lozano-Perez (1987) ArticleTitleA simple motion-planning algorithm for general robot manipulators IEEE Journal of Robotic and Automation 3 IssueID3 224–238

    Google Scholar 

  • W. S. Newman M. S. Branicky (1991) ArticleTitleReal-time configuration space transforms for obstacle avoidance International Journal of Robotic Research 10 IssueID6 650–667

    Google Scholar 

  • Orr, M. J. (1996) Introduction to Radial Basis Function Networks, Technical report, : Center of Cognitive Science, University of Edinburgh.

  • A. P. Pashkevich (1996) Computer-Aided Design of Industrial Robots and Robotic Cells for Assembling and Welding Belarusian State University of Informatics and Radioelectronics Minsk, Belarus

    Google Scholar 

  • Rosell, J. and Iniguez, P. (2002) Hierarchical and dynamic method to compute harmonic functions for constrained motion planning, in Proceedings of the 15th IEEE/RSJ International Conference on Intelligent Robots and Systems, Lausanne, Switzerland, pp. 2334–2340

  • K. Sato (1993) ArticleTitleDeadlock-free motion planning using the Laplace potential field Advanced Robotics 7 IssueID5 449–461

    Google Scholar 

  • Y. Zhang P. A. Heng W. C. Ada (1999) ArticleTitleEstimate of exponential convergence rate and exponential stability for neural networks IEEE Transactions on Neural Networks 10 IssueID6 1487–1493

    Google Scholar 

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Authors and Affiliations

  1. Department of Automatic Control, Belarusian State University of Informatics and Radioelectronics, 6 P. Brovka St., Minsk, 220027, Republic of Belarus

    A. Pashkevich & M. Kazheunikau

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  1. A. Pashkevich
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  2. M. Kazheunikau
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Correspondence to A. Pashkevich.

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Pashkevich, A., Kazheunikau, M. Neural network approach to trajectory synthesis for robotic manipulators. J Intell Manuf 16, 173–187 (2005). https://doi.org/10.1007/s10845-004-5887-5

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