참고문헌
- 송기무, 이종신 외, '직접구동방식의 스카라 로봇 개발,'삼성종합기술원, pp 611-612, 1989
- 이현엽, 문경일, MATLAB을 이용한 퍼지-뉴로, 도서출판 아진, pp.209-370, 1999
- J. J. Craig, Introduction to Robotics, Addison-Wesley Publishing Company, pp. 247,1986
DOI QR Code
This paper presents the compensation of mechanical deflection error in SCARA robot. End of robot gripper is deflected by weight of arm and pay-load. If end of robot gripper is deflected constantly regardless of robot configuration, it is not necessary to consider above mechanical deflection error. However, deflection in end of gripper varies because that moment of each axis varies when robot moves, it affects the relative accuracy. I propose the compensation method of deflection error using neural network. FEM analysis to obtain the deflection of gripper end was carried out on various joint angle, the results is used in neural network teaming. The result by simulation showed that maximum relative accuracy reduced maximum 9.48% on a given working area.