Achim Schade, Vu Nguyen, Cansu Gencoglu, Giang T. Nguyen, F. Fitzek
{"title":"Intuitive Robot Control with Data Gloves for Industrial Use Cases","authors":"Achim Schade, Vu Nguyen, Cansu Gencoglu, Giang T. Nguyen, F. Fitzek","doi":"10.1109/CCNC51664.2024.10454653","DOIUrl":null,"url":null,"abstract":"Human-robot interaction is crucial in various industries and domains, such as manufacturing, healthcare, and entertainment. Natural and intuitive interactions between humans and robots are crucial. Legacy controllers were designed for two-dimensional visual display and, therefore, suboptimal for interaction in three-dimensional space. Hand gesture recognition with camera-based systems is often hindered by visual obstruction. We demonstrate a hand gesture system leveraging data gloves with inertial measurement units (IMU). This demonstration focuses on gesture recognition quality, enhancing robustness and responsiveness. Audiences can observe and directly participate using the data glove to maneuver a robotic dog remotely in real-time.","PeriodicalId":518411,"journal":{"name":"2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)","volume":"95 11","pages":"1114-1115"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCNC51664.2024.10454653","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Human-robot interaction is crucial in various industries and domains, such as manufacturing, healthcare, and entertainment. Natural and intuitive interactions between humans and robots are crucial. Legacy controllers were designed for two-dimensional visual display and, therefore, suboptimal for interaction in three-dimensional space. Hand gesture recognition with camera-based systems is often hindered by visual obstruction. We demonstrate a hand gesture system leveraging data gloves with inertial measurement units (IMU). This demonstration focuses on gesture recognition quality, enhancing robustness and responsiveness. Audiences can observe and directly participate using the data glove to maneuver a robotic dog remotely in real-time.