Predicting the Motion of a Robot Manipulator with Unknown Trajectories Based on an Artificial Neural Network. (30th October 2014)

• Record Type: Journal Article
• Authors: Tang, Sai Hong; Ang, Chun Kit; Ariffin, Mohd Khairol Anuar Bin Mohd; Mashohor, Syamsiah Binti
• Is Part Of: International journal of advanced robotic systems. Volume 11:Number 10(2014)
• Publication Date: 2014-10-30
• Subjects: Artificial Neural Networks -- Robotic Manipulator -- Unknown Trajectory; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.5772/59278
• Languages: English
• ISSNs: 1729-8806

Abstract

Mathematically, the motion of a robot manipulator can be computed through the integration of kinematics, dynamics, and trajectories calculations. However, the calculations are complex and only can be applied if the configuration of the robot and the characteristics of the joint trajectories are known. This paper introduces the use of artificial neural networks (ANN) to overcome these shortcomings by solving nonlinear functions and adapting the characteristics of unknown trajectories. A virtual six-degree-of-freedom (DOF) robot manipulator is exploited as an example to show the robustness of the developed ANN topology.