{"title":"利用虚拟现实和基于机器人的触觉引导,在焊接运动技能学习的感知学习中增强运动体验。","authors":"Yang Ye, Pengxiang Xia, Fang Xu, Jing Du","doi":"10.1109/TOH.2024.3432835","DOIUrl":null,"url":null,"abstract":"<p><p>Welding is an important operation in many industries, including construction and manufacturing, which requires extensive training and practices. Although welding simulators have been used to accommodate welding training, it is still challenging to enable novice trainees to effectively understand the kinesthetic experience of the expert in an egocentric manner, such as the proper way of force exertion in complex welding operations. This study implements a robot-assisted perceptual learning system to transfer the expert welders' experience to trainees, including both the positional and force control actions. A human-subject experiment (N = 30) was performed to understand the motor skill acquisition process. Three conditions (control, robotic positional guidance with force visualization, and force perceptual learning with position visualization) were tested to evaluate the role of robotic guidance in welding motion control and force exertion. The results indicated various benefits related to task completion time and force control accuracy under the robotic guidance. The findings can inspire the design of future welding training systems enabled by external robotic systems.</p>","PeriodicalId":13215,"journal":{"name":"IEEE Transactions on Haptics","volume":"PP ","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhance Kinesthetic Experience in Perceptual Learning for Welding Motor Skill Acquisition with Virtual Reality and Robot-based Haptic Guidance.\",\"authors\":\"Yang Ye, Pengxiang Xia, Fang Xu, Jing Du\",\"doi\":\"10.1109/TOH.2024.3432835\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Welding is an important operation in many industries, including construction and manufacturing, which requires extensive training and practices. Although welding simulators have been used to accommodate welding training, it is still challenging to enable novice trainees to effectively understand the kinesthetic experience of the expert in an egocentric manner, such as the proper way of force exertion in complex welding operations. This study implements a robot-assisted perceptual learning system to transfer the expert welders' experience to trainees, including both the positional and force control actions. A human-subject experiment (N = 30) was performed to understand the motor skill acquisition process. Three conditions (control, robotic positional guidance with force visualization, and force perceptual learning with position visualization) were tested to evaluate the role of robotic guidance in welding motion control and force exertion. The results indicated various benefits related to task completion time and force control accuracy under the robotic guidance. The findings can inspire the design of future welding training systems enabled by external robotic systems.</p>\",\"PeriodicalId\":13215,\"journal\":{\"name\":\"IEEE Transactions on Haptics\",\"volume\":\"PP \",\"pages\":\"\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-07-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Haptics\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1109/TOH.2024.3432835\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, CYBERNETICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Haptics","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1109/TOH.2024.3432835","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}
Enhance Kinesthetic Experience in Perceptual Learning for Welding Motor Skill Acquisition with Virtual Reality and Robot-based Haptic Guidance.
Welding is an important operation in many industries, including construction and manufacturing, which requires extensive training and practices. Although welding simulators have been used to accommodate welding training, it is still challenging to enable novice trainees to effectively understand the kinesthetic experience of the expert in an egocentric manner, such as the proper way of force exertion in complex welding operations. This study implements a robot-assisted perceptual learning system to transfer the expert welders' experience to trainees, including both the positional and force control actions. A human-subject experiment (N = 30) was performed to understand the motor skill acquisition process. Three conditions (control, robotic positional guidance with force visualization, and force perceptual learning with position visualization) were tested to evaluate the role of robotic guidance in welding motion control and force exertion. The results indicated various benefits related to task completion time and force control accuracy under the robotic guidance. The findings can inspire the design of future welding training systems enabled by external robotic systems.
期刊介绍:
IEEE Transactions on Haptics (ToH) is a scholarly archival journal that addresses the science, technology, and applications associated with information acquisition and object manipulation through touch. Haptic interactions relevant to this journal include all aspects of manual exploration and manipulation of objects by humans, machines and interactions between the two, performed in real, virtual, teleoperated or networked environments. Research areas of relevance to this publication include, but are not limited to, the following topics: Human haptic and multi-sensory perception and action, Aspects of motor control that explicitly pertain to human haptics, Haptic interactions via passive or active tools and machines, Devices that sense, enable, or create haptic interactions locally or at a distance, Haptic rendering and its association with graphic and auditory rendering in virtual reality, Algorithms, controls, and dynamics of haptic devices, users, and interactions between the two, Human-machine performance and safety with haptic feedback, Haptics in the context of human-computer interactions, Systems and networks using haptic devices and interactions, including multi-modal feedback, Application of the above, for example in areas such as education, rehabilitation, medicine, computer-aided design, skills training, computer games, driver controls, simulation, and visualization.