{"title":"Augmented Reality Interface for Robot-Sensor Coordinate Registration","authors":"Vinh Nguyen, Xiaofeng Liu, J. Marvel","doi":"10.1115/1.4063131","DOIUrl":null,"url":null,"abstract":"\n 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.","PeriodicalId":54856,"journal":{"name":"Journal of Computing and Information Science in Engineering","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2023-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computing and Information Science in Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1115/1.4063131","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
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 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.
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