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Force–vision fusion fuzzy control for robotic batch precision assembly of flexibly absorbed pegs
Robotics and Computer-Integrated Manufacturing ( IF 9.1 ) Pub Date : 2024-09-06 , DOI: 10.1016/j.rcim.2024.102861
Bin Wang , Jiwen Zhang , Dan Wu

This article focuses on improving the compliance, efficiency, and robustness of batch precision assembly of small-scale pegs flexibly absorbed by a suction cup. The main contribution is that a force–vision fusion fuzzy control method (FVFFC) is proposed to achieve precision assembly with unknown clearance or interference fit. Both visual and force features are designed to describe the state of the peg and hole with the deformation of the suction cup. Then, a force–vision fusion control framework is proposed, where the visual features dynamically modify the reference position of admittance control and guide compliant adjustment of the peg angles. Furthermore, based on theoretical analysis, two fuzzy logic inference modules are developed to estimate the contact state as well as either the clearance or interference amount between the peg and hole in order to adaptively tune the control parameters. Finally, sufficient experiments are conducted to demonstrate the superiority and robustness of the FVFFC method.

中文翻译:


力视觉融合模糊控制用于机器人批量精确装配柔性吸附钉



本文重点关注提高吸盘灵活吸附的小型钉子的批量精密组装的合规性、效率和稳健性。主要贡献是提出了一种力视觉融合模糊控制方法(FVFFC)来实现未知间隙或过盈配合的精密装配。视觉和力特征都旨在描述钉子和孔随着吸盘变形的状态。然后,提出了一种力-视觉融合控制框架,其中视觉特征动态修改导纳控制的参考位置并引导钉角度的顺从调整。此外,基于理论分析,开发了两个模糊逻辑推理模块来估计接触状态以及销钉和孔之间的间隙或干涉量,以便自适应地调整控制参数。最后,进行了足够的实验来证明FVFFC方法的优越性和鲁棒性。
更新日期:2024-09-06
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