{"title":"Digital twins for hand gesture-guided human-robot collaboration systems","authors":"Ao Liu, Yifan Zhang, Yuan Yao","doi":"10.1177/09544054231223783","DOIUrl":null,"url":null,"abstract":"Gesture control is one of the effective and flexible communication method between humans and robots. However, it always depends on complex hardware and configurations in human-robot collaboration systems. Simplifying the design of gesture-interaction systems and avoiding miscommunication are challenging problems. In this paper, we proposed a method that utilizes an RGB sensor to realize spatial human-robot collaboration. A random forest based depth estimator is presented to supplement the additional spatial information for hand gesture recognition. Additionally, we demonstrate the construction of secure human-robot collaboration scenarios in Unity and validate our approach in real-world settings, based on which a digital twin system oriented to human-machine collaboration is constructed to realize rapid human-machine task simulation, safety specification testing, and real-scene applications development.","PeriodicalId":20663,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1177/09544054231223783","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
引用次数: 0
Abstract
Gesture control is one of the effective and flexible communication method between humans and robots. However, it always depends on complex hardware and configurations in human-robot collaboration systems. Simplifying the design of gesture-interaction systems and avoiding miscommunication are challenging problems. In this paper, we proposed a method that utilizes an RGB sensor to realize spatial human-robot collaboration. A random forest based depth estimator is presented to supplement the additional spatial information for hand gesture recognition. Additionally, we demonstrate the construction of secure human-robot collaboration scenarios in Unity and validate our approach in real-world settings, based on which a digital twin system oriented to human-machine collaboration is constructed to realize rapid human-machine task simulation, safety specification testing, and real-scene applications development.
期刊介绍:
Manufacturing industries throughout the world are changing very rapidly. New concepts and methods are being developed and exploited to enable efficient and effective manufacturing. Existing manufacturing processes are being improved to meet the requirements of lean and agile manufacturing. The aim of the Journal of Engineering Manufacture is to provide a focus for these developments in engineering manufacture by publishing original papers and review papers covering technological and scientific research, developments and management implementation in manufacturing. This journal is also peer reviewed.
Contributions are welcomed in the broad areas of manufacturing processes, manufacturing technology and factory automation, digital manufacturing, design and manufacturing systems including management relevant to engineering manufacture. Of particular interest at the present time would be papers concerned with digital manufacturing, metrology enabled manufacturing, smart factory, additive manufacturing and composites as well as specialist manufacturing fields like nanotechnology, sustainable & clean manufacturing and bio-manufacturing.
Articles may be Research Papers, Reviews, Technical Notes, or Short Communications.