https://scholars.lib.ntu.edu.tw/handle/123456789/580784
Title: | Zero-tuning grinding process methodology of cyber-physical robot system | Authors: | Yang H.-Y Shih C.-H Lo Y.-C Lian F.-L. FENG-LI LIAN |
Keywords: | Agricultural robots; Computer control systems; Construction industry; Cyber Physical System; Genetic algorithms; Grinding (machining); Intelligent robots; Complex Processes; Grinding process; Grinding quality; Neural network model; Precise positioning; Process parameters; Real environments; System calibration; Industrial robots | Issue Date: | 2020 | Start page/Pages: | 4270-4275 | Source: | IEEE International Conference on Intelligent Robots and Systems | Abstract: | Industrial robots play potential and important roles on labor-intensive and high-risk jobs. For example, typical industrial robots have been used in grinding process. However, the automatic grinding process by robots is a complex process because it still relies on skillful engineers to adaptively adjust several key parameters. Moreover, it might take a lot of time and effort to yield better grinding quality. Hence, this paper proposed a new framework of cyber-physical robot system with automatic zero-tuning optimization of the process parameters to achieve the desired quality. To overcome the unexpected difference between reality and simulation, proper system calibration can help in precise positioning in real environment, and the cloud database is constructed to record the relative data during the grinding process simultaneously. The proposed zero-tuning methodology combines both neural network (NN) model and genetic algorithm (GA) to generate the best combination of corresponding parameters to meet the desired quality. Experimental results showed that the average error of the output result was 8.93%. To compare the CNC machine, our solution shows more prominent role and potential in plumbing industry. ? 2020 IEEE. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102405415&doi=10.1109%2fIROS45743.2020.9341102&partnerID=40&md5=63f2e61e14a2fb9c5d098fe9ef5749b2 https://scholars.lib.ntu.edu.tw/handle/123456789/580784 |
ISSN: | 21530858 | DOI: | 10.1109/IROS45743.2020.9341102 |
Appears in Collections: | 電機工程學系 |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.