{"title":"Assistive Sensory Feedback for Trajectory Tracking in Augmented Reality","authors":"I-Jan Wang, Lifen Yeh, Chih-Hsing Chu, Yan-Ting Huang","doi":"10.1115/1.4062543","DOIUrl":null,"url":null,"abstract":"\n In recent years, Augmented Reality (AR) has been successfully applied in various fields to assist in the execution of manual tasks. However, there is still a lack of complete set of criteria for interface design for generating real-time interactive functions and effectively improving the task efficiency through AR. In this study, subjects performed two kinds of trajectory tracking tasks in AR, the simple trajectory and complex trajectory. Their task performance under five different sensory feedbacks, namely, central vision, peripheral vision, auditory sensation, tactile sensation and no feedback, were compared. The results show that in the trajectory tracking task in complex trajectories, the feedback information should not only provide prompts of error states, but also provide suggestions for correcting the actions to the subjects. In addition, compared with visual sensation and auditory sensation, the feedback information of tactile sensation has better adaptation. Furthermore, the subjects tend to rely on the real-time feedback of tactile sensation to complete difficult tasks. It was found that in the manual trajectory tracking task, determining whether the trajectory tracking task is within the acceptable trajectory range will be affected by the postures subjects use for the tasks, and will change the task performance. Therefore, it is suggested that when designing auxiliary functions, the limitations of the postures of the task should be considered. The experimental results and findings obtained in this study can provide a reference for the auxiliary interface design of manual tasks in AR.","PeriodicalId":54856,"journal":{"name":"Journal of Computing and Information Science in Engineering","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2023-05-16","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/10.1115/1.4062543","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
In recent years, Augmented Reality (AR) has been successfully applied in various fields to assist in the execution of manual tasks. However, there is still a lack of complete set of criteria for interface design for generating real-time interactive functions and effectively improving the task efficiency through AR. In this study, subjects performed two kinds of trajectory tracking tasks in AR, the simple trajectory and complex trajectory. Their task performance under five different sensory feedbacks, namely, central vision, peripheral vision, auditory sensation, tactile sensation and no feedback, were compared. The results show that in the trajectory tracking task in complex trajectories, the feedback information should not only provide prompts of error states, but also provide suggestions for correcting the actions to the subjects. In addition, compared with visual sensation and auditory sensation, the feedback information of tactile sensation has better adaptation. Furthermore, the subjects tend to rely on the real-time feedback of tactile sensation to complete difficult tasks. It was found that in the manual trajectory tracking task, determining whether the trajectory tracking task is within the acceptable trajectory range will be affected by the postures subjects use for the tasks, and will change the task performance. Therefore, it is suggested that when designing auxiliary functions, the limitations of the postures of the task should be considered. The experimental results and findings obtained in this study can provide a reference for the auxiliary interface design of manual tasks in AR.
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