期刊
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
卷 26, 期 4, 页码 282-290出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.rcim.2009.10.001
关键词
Noise; Robot manipulator; Neural network; Robust neural noise analyzer
资金
- Erciyes University and State Planning Organization
- [DPT-05-06]
Due to a lot of robot manipulators application in industry, low noise degree is very important criteria for robot manipulator's joints. In this paper, joint noise problem of a robot manipulator with five joints is investigated both theoretically and experimentally. The investigation is consisted of two steps. First step is to analyze the noise of joints using a hardware and software. The hardware is a part of noise sensors. The second step; according to experimental results, some neural networks are employed for finding robust neural noise analyzer. Five types of neural networks are used to compare each other. From the results, it is noted that the proposed RBFNN gives the best results for analyzing joint noise of the robot manipulator. (C) 2009 Elsevier Ltd. All rights reserved.
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