Experimental Kinematic Modeling of 6-DOF Serial Manipulator Using Hybrid Deep Learning
| Autor: | Nada Ali Mohamed, Nada Elsayed Abbas, Hossam Hassan Ammar, Mamdouh Ahmed Ezzeldin, Ahmad Taher Azar |
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| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Forward kinematics Neuro-fuzzy business.industry Computer science Robotics 02 engineering and technology Serial manipulator 020901 industrial engineering & automation Simulated annealing 0202 electrical engineering electronic engineering information engineering Robot Six degrees of freedom 020201 artificial intelligence & image processing Artificial intelligence business Robotic arm Simulation |
| Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9783030442880 AICV |
| DOI: | 10.1007/978-3-030-44289-7_27 |
| Popis: | According to its significance, robotics is always an area of interest for research and further development. While robots have varying types, design and sizes, the six degrees of freedom (DOF) serial manipulator is a famous robotic arm that has a vast areas of applications, not only in industrial application, but also in other fields such as medical and exploration applications. Accordingly, control and optimization of such robotic arm is crucial and needed. In this paper, different analyses are done on the chosen design of robotic arm. Forward kinematics are calculated and validated, then simulation using MSC ADAMS is done, followed by experimentation and tracking using Microsoft Kinect. Two approaches are used in this study: adaprive neuro fuzzy (ANF) system optimized by simulated annealing (SA) algorithm and convolutional neural networks (CNNs) optimized by adaptive moment estimation (Adam). The same inputs are given to both models and their results are compared in order to determine the best fit algorithm for higher precision in the given robotic model. The findings have shown that the accuracy of CNNs is higher. Furthermore, this advantage has a higher cost for the time of computation than for NFs with SA. |
| Databáze: | OpenAIRE |
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