增强现实
坐标系
计算机视觉
工作区
计算机科学
笛卡尔坐标系
机器人
直角坐标机器人
人工智能
接口(物质)
转化(遗传学)
机器人运动学
移动机器人
数学
最大气泡压力法
生物化学
化学
几何学
气泡
并行计算
基因
作者
Vinh Nguyen,Xiaofeng Liu,Jeremy A. Marvel
出处
期刊:Journal of Computing and Information Science in Engineering
[ASME International]
日期:2023-10-10
卷期号:24 (3)
摘要
Abstract Accurate registration of Cartesian coordinate systems is necessary to facilitate metrology-based solutions for industrial robots in production environments. Conducting coordinate registration between industrial robots and their metrological systems requires measuring multiple points in the robot’s and sensor system’s coordinate frames. However, operators lack intuitive tools to interface, visualize, and characterize the quality of the selected points in the robot workspace for robot–sensor coordinate registration. This article proposes an augmented reality system for human-in-the-loop, robot–sensor coordinate registration to efficiently record and visualize the pose-dependent quality of computing the robot–sensor transformation. Furthermore, this work establishes metrics to define the relative quality of measurement points used in robot–sensor coordinate registration, which is shown by the augmented reality application. Experiments were conducted demonstrating the augmented reality environment in addition to investigating the pose dependency of the measurement point quality. The results indicate that the proposed metrics highlight the dependency of the poses on both robot and sensor placement and that the augmented reality system can provide a human-in-the-loop interface for robot–sensor coordinate registration.
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