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Repetitive Motion Planning of Redundant Robots Based on LVI-Based Primal-Dual Neural Network and PUMA560 Example

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Life System Modeling and Simulation (LSMS 2007)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 4689))

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Abstract

A primal-dual neural network based on linear variational inequalities (LVI) is presented in this paper, which is used to solve the repetitive motion planning of redundant robots. To do so, a drift-free criterion is exploited. In addition, the physical constraints such as joint limits and joint velocity limits are incorporated into the problem formulation of such a scheme. The scheme is finally reformulated as a quadratic programming (QP) problem and resolved at the velocity-level. Compared to other computational strategies on inverse kinematics, the LVI-based primal-dual neural network is designed based on the QP-LVI conversion and Karush-Kuhn-Tucker (KKT) conditions. With simple piecewise-linear dynamics and global (exponential) convergence to optimal solutions, it can handle general QP and linear programming (LP) problems in the same inverse-free manner. The repetitive motion planning scheme and the LVI-based primal-dual neural network are simulated based on PUMA560 robot manipulator with effectiveness demonstrated.

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Kang Li Xin Li George William Irwin Gusen He

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© 2007 Springer-Verlag Berlin Heidelberg

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Zhang, Y., Lv, X., Li, Z., Yang, Z. (2007). Repetitive Motion Planning of Redundant Robots Based on LVI-Based Primal-Dual Neural Network and PUMA560 Example. In: Li, K., Li, X., Irwin, G.W., He, G. (eds) Life System Modeling and Simulation. LSMS 2007. Lecture Notes in Computer Science(), vol 4689. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74771-0_61

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  • DOI: https://doi.org/10.1007/978-3-540-74771-0_61

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74770-3

  • Online ISBN: 978-3-540-74771-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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