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A Performance Comparison of Different Back Propagation Neural Networks in Inverse Kinematics

عنوان مقاله: A Performance Comparison of Different Back Propagation Neural Networks in Inverse Kinematics
شناسه ملی مقاله: ACCSI12_279
منتشر شده در دوازدهمین کنفرانس سالانه انجمن کامپیوتر ایران در سال 1385
مشخصات نویسندگان مقاله:

Mahdi Hosseini - Computer Engineering Department of Sharif University of Technology, Tehran, Iran
Leila Sharif - Computer Science Department Shahid Beheshti University, Tehran, Iran

خلاصه مقاله:
Error Back Propagation, a class of neural networks, is proposed to solve the inverse kinematics problem in robotic manipulator. In this approach a network has been trained to learn a desired set of joint angles positions from a given set of end effectors positions. This paper demonstrates some methods of Back Propagation neural network which can be used to solve inverse kinematics. Next the performance of these methods has been compared for inverse kinematics problems. The used Error Back Propagation techniques are the Standard, Momentum and Delta Bar- Delta.

کلمات کلیدی:
Neural networks; Robotic; Inverse kinematics; Back propagation

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/44665/