A low-cost monocular vision system for robot calibration

IF 0.2 Q4 ENGINEERING, MULTIDISCIPLINARY
Jesús Abraham Rojas Úrzulo, José-Joel González-Barbosa, Xochitl Yamile Sandoval Castro, Maximiano Francisco Ruiz Torres, Erick-Alejandro González-Barbosa
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引用次数: 0

Abstract

The inverse kinematic model uses robot design parameters: ideal link lengths and mounting angles. In practice, these values hardly coincide with the design values due to manufacturing and assembly processes or continuous use of the robot. In order to reduce this geometric error, it is necessary to calibrate the robot to update the geometric model and reduce the resulting error of the robot end-effector. In this work, we propose a methodology based on a vision system to calibrate the robot's geometric parameters and minimize the error between the robot’s end-effector theoretical and real trajectory. This way, variations are introduced to the geometric parameters that generate errors between the robot's desired position and the position developed. The results show up a reduction of the average position error of 54.6%.
一种用于机器人标定的低成本单目视觉系统
运动学逆模型采用机器人的设计参数:理想连杆长度和安装角度。在实践中,由于制造和装配过程或机器人的连续使用,这些值很难与设计值一致。为了减小这种几何误差,有必要对机器人进行标定,以更新机器人的几何模型,减小机器人末端执行器的误差。在这项工作中,我们提出了一种基于视觉系统的方法来校准机器人的几何参数,并最大限度地减少机器人末端执行器理论轨迹与实际轨迹之间的误差。这样,就引入了几何参数的变化,从而在机器人的期望位置和开发的位置之间产生误差。结果表明,平均位置误差降低了54.6%。
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来源期刊
Nexo Revista Cientifica
Nexo Revista Cientifica ENGINEERING, MULTIDISCIPLINARY-
自引率
0.00%
发文量
74
审稿时长
30 weeks
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