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Compensation Control of Mechanical Deflection Error on SCARA Robot with Constant Pay Load Using Neural Network

일정한 가반 하중이 작용하는 스카라 로봇에 대한 신경망을 이용한 기계적 처짐 오차 보상 제어

  • 이종신 (주성대학 컴퓨터응용기계과)
  • Published : 2009.07.01

Abstract

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.

References

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