Second Order Recurrent Neural Network for the Inverse Kinematics of Redundant Manipulators

Run Sheng Hao

doi:10.4028/www.scientific.net/AMM.391.114

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 391Second Order Recurrent Neural Network for the...

Second Order Recurrent Neural Network for the Inverse Kinematics of Redundant Manipulators

Abstract:

In this paper, the second order recurrent neural network is adopted to study the inverse kinematics problem of three degree-of-freedom planar redundant manipulators. The Simulation results show that the network can effectively solve the inverse kinematics problem of redundant manipulators, and it reaches to good precision of solution and solving speed.

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Periodical:

Applied Mechanics and Materials (Volume 391)

Pages:

114-117

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.391.114

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Online since:

September 2013

Authors:

Run Sheng Hao

Keywords:

Inverse Kinematics, Recurrent Neural Network, Redundant Manipulators

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References

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