补偿(心理学)
机器人
人工神经网络
计算机科学
经济短缺
工业机器人
补偿方式
人工智能
计算机视觉
数字营销
政府(语言学)
哲学
万维网
精神分析
语言学
营销投资回报率
心理学
作者
Bujin He Shanghai,Wanhe Du Shanghai,Tao Yu
标识
DOI:10.1109/ispds54097.2021.00033
摘要
Due to the existence of geometric error and non-geometric error factors, the positioning accuracy of industrial robots is greatly reduced, which can not meet the needs of industrial production, so we need to carry out positioning error compensation for industrial robots. The traditional compensation method of establishing geometric error model can only compensate geometric errors. Aiming at this shortage, this paper proposes a positioning error compensation method based on BP neural network, which takes into account both geometric error and non-geometric error factors. Experimental results show that the proposed method can greatly improve the positioning accuracy of industrial robots.
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