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Real-time thermal error compensation method for robotic visual inspection system

机译:机器人视觉检测系统的实时热误差补偿方法

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摘要

The thermally induced error is a critical element in the total errors for the robotic visual inspection system during its long-term operation. This paper investigates the thermal behavior of the robotic visual inspection system and proposes a real-time thermal error compensation method. Based on the fixed-point constraint, an error calibration model is derived by associating the thermally induced parameter errors with the deviations in the measured coordinates of the fixed reference point during the robot warm up and cool down. A joint-by-joint test is performed to investigate the link parameters that change significantly with respect to temperature variations. Standard spheres are adopted as the calibration targets, and optimum projected angles for sphere center measurement by visual sensor are obtained based on theoretical analysis and experimental data. Contrary to most other works, the method needs no exact knowledge of the temperature sensors and is well suited for online dynamic thermal error compensation for the robotic visual inspection system. Verification experiment is carried out on a car-body assembly line, and results show that the max/mean residual error for the tested points has been reduced from 0.441/0.195 to 0.136/0.078 mm with the significant parameters calibrated.
机译:对于机器人视觉检查系统,在长期运行过程中,热引起的误差是总误差中的关键因素。本文研究了机器人视觉检测系统的热行为,并提出了一种实时热误差补偿方法。基于定点约束,通过将热感应参数误差与机器人预热和冷却期间固定参考点的测量坐标中的偏差相关联,得出误差校准模型。执行逐项测试以研究随温度变化而显着变化的链接参数。采用标准球体作为标定目标,并根据理论分析和实验数据,获得了通过视觉传感器进行球心测量的最佳投影角。与大多数其他工作相反,该方法不需要确切的温度​​传感器知识,非常适合于机器人视觉检查系统的在线动态热误差补偿。在车身装配线上进行了验证实验,结果表明,在校正了重要参数的情况下,测试点的最大/平均残余误差已从0.441 / 0.195降低至0.136 / 0.078 mm。

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