Abstract




 
   

IJE TRANSACTIONS C: Aspects Vol. 30, No. 9 (September 2017) 1319-1325   

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  KINEMATIC SYNTHESIS OF PARALLEL MANIPULATOR VIA NEURAL NETWORK APPROACH
 
J. Ghasemi, R. Moradinezhad and M. A. Hosseini
 
( Received: March 04, 2017 – Accepted in Revised Form: July 07, 2017 )
 
 

Abstract    In this research, Artificial Neural Networks (ANNs) have been used as a powerful tool to solve the inverse kinematic equations of a parallel robot. For this purpose, we have developed the kinematic equations of a Tricept parallel kinematic mechanism with two rotational and one translational degrees of freedom (DoF). Using the analytical method, the inverse kinematic equations are solved for specific trajectory, and used as inputs for the applied ANNs. The results of both applied networks (Multi-Layer Perceptron and Redial Basis Function) satisfied the required performance in solving complex inverse kinematics with proper accuracy and speed.

 

Keywords    Parallel Robot, Kinematics, Artificial Neural Network.

 

چکیده    در این تحقیق، شبکه های عصبی به عنوان یک ابزار قدرتمند برای حل معادلات سینماتیک معکوس یک ربات موازی به کار گرفته شده است. به این منظور معادلات سینماتیک یک مکانیزم Tricept با دو درجه آزادی چرخشی و یک درجه آزادی انتقالی توسعه داده شد. با استفاده از روش های آنالیز تحلیلی، معادلات سینماتیک معکوس برای یک فضای مشخص حل شد. پاسخ به دست آمده به عنوان ورودی شبکه عصبی به کار گرفته شده است. نتایج دو شبکه عصبی بکار گرفته شده (پرسپترون چند لایه و شبکه عصبی تابع شعاعی) با سرعت و دقت مناسبی توانست معادلات پیچیده سینماتیکی مکانیزم را مدل کرده و حل نماید.

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