Modelling and simulation of 3DOF parallel manipulator using artificial neural network

Author:

Youssef Abdelrahman,Bayoumy Amgad M,Rostom Mostafa,Tolbah Farid A

Abstract

Abstract Parallel Robot (PR) has shown its ability to be precise in its movement. Actuators move simultaneously to achieve the required target, on top of that its payload is much greater than what a serial robot can withstand. To determine workspace of the robot with known angles Forward kinematics has to be introduced which, bring a lot of difficulty as it requires the solution of multiple coupled nonlinear algebraic equations. Those equations bring multiple valid solutions. Those solutions could lead to different locations. As it is not going to make the pick and place for PR will be easier. This paper will discuss a numerical method that calculates the Forward Kinematics for PR. This method uses Artificial Neural Network which relay on training with a certain number of iterations. The set of data to be used in the training can be obtained from PR simulation. This method will serve to know workspace around PR as it will help it to pick the target object.

Publisher

IOP Publishing

Subject

General Medicine

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1. On an Alternative form of the Constraint Equations for the Delta Robot and Ways to Take them into Account in Modeling;2022 4th International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA);2022-11-09

2. Forward Kinematics of Delta Manipulator by Novel Hybrid Neural Network;International Journal of Mathematical, Engineering and Management Sciences;2021-12-01

3. Artificial Neural Networks to Solve Forward Kinematics of a Wearable Parallel Robot with Semi-rigid Links;2021 IEEE International Conference on Robotics and Automation (ICRA);2021-05-30

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