SLAM-Integrated Kinematic Calibration Using Checkerboard Patterns
SLAM-Integrated Kinematic Calibration Using Checkerboard Patterns
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DOI：
10.1109/sii46433.2020.9026264
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发表时间：
2020-01
期刊：
影响因子：
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通讯作者：
Akitoshi Ito;Jinghui Li;Y. Maeda
中科院分区：
文献类型：
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作者：
Akitoshi Ito;Jinghui Li;Y. Maeda
如今，工业机器人离线编程是可能的，但有两个问题需要考虑。首先，由于任何机器人都有运动误差，机器人的绝对精度不一定足够。因此，机器人的运动学标定是必不可少的。其次，准确测量机器人周围环境有助于机器人的运动规划。因此，我们开发了一种SKCLAM（同时运动学校准，定位和映射）方法，其中运动学校准和环境映射同时进行的机械手与RGB-D传感器连接到它的手。在本研究中，为了使SKCLAM方法更实用，我们引入了棋盘模式。我们在虚拟环境和真实的环境中验证了SKCLAM方法与棋盘图案。结果表明，我国目前实施的有效性和一些局限性。
Today it is possible to program industrial robots offline, but there are two problems to consider. First, since any robot has kinematic errors, the absolute accuracy of the robot is not necessarily sufficient. Therefore, kinematic calibration of the robot is indispensable. Secondly, it is useful to accurately measure the surrounding environment of the robot for its motion planning. Therefore, we developed a SKCLAM (Simultaneous Kinematic Calibration, Localization and Mapping) method, in which kinematic calibration and environmental mapping are performed simultaneously for a manipulator with an RGB-D sensor attached to its hand. In this study, in order to make the SKCLAM method more practical, we introduced checkerboard patterns. We verified the SKCLAM method with checkerboard patterns in both a virtual environment and a real environment. The results showed that the effectiveness and some limitations of our current implementation.