用于机器人传感器坐标配准的增强现实接口

IF 2.6 3区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Vinh Nguyen, Xiaofeng Liu, J. Marvel
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引用次数: 0

摘要

笛卡尔坐标系的精确配准对于促进生产环境中工业机器人基于计量的解决方案是必要的。在工业机器人及其计量系统之间进行坐标配准需要测量机器人和传感器系统坐标系中的多个点。然而,操作员缺乏直观的工具来接口、可视化和表征机器人工作空间中用于机器人传感器坐标配准的选定点的质量。本文提出了一种用于人在环的增强现实系统,机器人传感器坐标配准,以有效地记录和可视化计算机器人传感器变换的姿态相关质量。此外,这项工作建立了度量标准,以定义机器人传感器坐标配准中使用的测量点的相对质量,增强现实应用程序显示了这一点。除了研究测量点质量的姿态依赖性外,还进行了实验来演示增强现实环境。结果表明,所提出的度量突出了姿态对机器人和传感器位置的依赖性,并且增强现实系统可以为机器人传感器坐标配准提供人在环界面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Augmented Reality Interface for Robot-Sensor Coordinate Registration
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 paper 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 are 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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来源期刊
CiteScore
6.30
自引率
12.90%
发文量
100
审稿时长
6 months
期刊介绍: The ASME Journal of Computing and Information Science in Engineering (JCISE) publishes articles related to Algorithms, Computational Methods, Computing Infrastructure, Computer-Interpretable Representations, Human-Computer Interfaces, Information Science, and/or System Architectures that aim to improve some aspect of product and system lifecycle (e.g., design, manufacturing, operation, maintenance, disposal, recycling etc.). Applications considered in JCISE manuscripts should be relevant to the mechanical engineering discipline. Papers can be focused on fundamental research leading to new methods, or adaptation of existing methods for new applications. Scope: Advanced Computing Infrastructure; Artificial Intelligence; Big Data and Analytics; Collaborative Design; Computer Aided Design; Computer Aided Engineering; Computer Aided Manufacturing; Computational Foundations for Additive Manufacturing; Computational Foundations for Engineering Optimization; Computational Geometry; Computational Metrology; Computational Synthesis; Conceptual Design; Cybermanufacturing; Cyber Physical Security for Factories; Cyber Physical System Design and Operation; Data-Driven Engineering Applications; Engineering Informatics; Geometric Reasoning; GPU Computing for Design and Manufacturing; Human Computer Interfaces/Interactions; Industrial Internet of Things; Knowledge Engineering; Information Management; Inverse Methods for Engineering Applications; Machine Learning for Engineering Applications; Manufacturing Planning; Manufacturing Automation; Model-based Systems Engineering; Multiphysics Modeling and Simulation; Multiscale Modeling and Simulation; Multidisciplinary Optimization; Physics-Based Simulations; Process Modeling for Engineering Applications; Qualification, Verification and Validation of Computational Models; Symbolic Computing for Engineering Applications; Tolerance Modeling; Topology and Shape Optimization; Virtual and Augmented Reality Environments; Virtual Prototyping
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