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https://scholarbank.nus.edu.sg/handle/10635/245661
DC Field | Value | |
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dc.title | AI-ENHANCED HUMAN-MACHINE INTERFACES USING INTEGRATED MULTI-MODAL SENSING AND HAPTIC-AUGMENTED FUNCTIONS FOR DIGITAL TWIN AND METAVERSE | |
dc.contributor.author | SUN ZHONGDA | |
dc.date.accessioned | 2023-10-31T18:00:36Z | |
dc.date.available | 2023-10-31T18:00:36Z | |
dc.date.issued | 2023-01-25 | |
dc.identifier.citation | SUN ZHONGDA (2023-01-25). AI-ENHANCED HUMAN-MACHINE INTERFACES USING INTEGRATED MULTI-MODAL SENSING AND HAPTIC-AUGMENTED FUNCTIONS FOR DIGITAL TWIN AND METAVERSE. ScholarBank@NUS Repository. | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/245661 | |
dc.description.abstract | This thesis reports the development of AI-enhanced human-machine interfaces using integrated multi-modal sensing and haptic-augmented functions for digital twin and metaverse. Firstly a smart soft gripper with a fully self-powered multifunctional perception system capable of monitoring self-deformation and pressure/temperature tactile stimuli simultaneously is developed based on triboelectric and pyroelectric sensors. With machine learning analytics, high-accuracy object recognition is achieved for the developed smart robot to implement automatic item management for digital-twin-based unmanned working space. To boost the perception capability, the ultrasonic sensor is further integrated to realize the auto-positioning function and enhance the performance/robustness of the robotic identification system via multimodal data fusion technologies. Besides, wearable manipulators with multimodal sensing and haptic-feedback functions are also essential for immersive experiences in human- machine/human-robot interactions under the digital-twin-based framework when integrated with metaverse technologies. Based on this, augmented rings integrated with self-powered tactile/temperature sensors and low-power vibro-/thermo-haptic feedback units are achieved. | |
dc.language.iso | en | |
dc.subject | Human-machine Interface; Haptic Feedback; Intelligent Robots; Wearable Sensor; Digital Twin; Metaverse | |
dc.type | Thesis | |
dc.contributor.department | ELECTRICAL & COMPUTER ENGINEERING | |
dc.contributor.supervisor | Chengkuo Lee | |
dc.description.degree | Ph.D | |
dc.description.degreeconferred | DOCTOR OF PHILOSOPHY (CDE-ENG) | |
dc.identifier.orcid | 0000-0001-7365-1945 | |
Appears in Collections: | Ph.D Theses (Open) |
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SunZD.pdf | 48.59 MB | Adobe PDF | OPEN | None | View/Download |
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