| Naslov: | Human intention recognition by deep LSTM and transformer networks for real-time human-robot collaboration |
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| Avtorji: | ID Mavsar, Matija, Institut "Jožef Stefan" (Avtor)
ID Simonič, Mihael, Institut "Jožef Stefan" (Avtor)
ID Ude, Aleš, Institut "Jožef Stefan" (Avtor) |
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| Datoteke: |  URL - Izvorni URL, za dostop obiščite https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2025.1708987/full
 PDF - Predstavitvena datoteka, prenos (5,71 MB)
MD5: CAEAFF9578940192BCCB617D386F9090
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| Jezik: | Angleški jezik |
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| Tipologija: | 1.01 - Izvirni znanstveni članek |
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| Organizacija: |  IJS - Institut Jožef Stefan
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| Povzetek: | Collaboration between humans and robots is essential for optimizing the performance of complex tasks in industrial environments, reducing worker strain, and improving safety. This paper presents an integrated human-robot collaboration (HRC) system that leverages advanced intention recognition for real-time task sharing and interaction. By utilizing state-of-the-art human pose estimation combined with deep learning models, we developed a robust framework for detecting and predicting worker intentions. Specifically, we employed LSTM-based and transformer-based neural networks with convolutional and pooling layers to classify human hand trajectories, achieving higher accuracy compared to previous approaches. Additionally, our system integrates dynamic movement primitives (DMPs) for smooth robot motion transitions, collision prevention, and automatic motion onset/cessation detection. We validated the system in a real-world industrial assembly task, demonstrating its effectiveness in enhancing the fluency, safety, and efficiency of human-robot collaboration. The proposed method shows promise in improving real-time decision-making in collaborative environments, offering a safer and more intuitive interaction between humans and robots. |
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| Ključne besede: | human-robot collaboration, deep neural networks, LSTM, transformer, intention recognition |
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| Status publikacije: | Objavljeno |
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| Verzija publikacije: | Objavljena publikacija |
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| Poslano v recenzijo: | 19.09.2025 |
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| Datum sprejetja članka: | 26.11.2025 |
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| Datum objave: | 19.12.2025 |
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| Založnik: | Frontiers |
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| Leto izida: | 2025 |
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| Št. strani: | str. 1-15 |
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| Številčenje: | Vol. 12 |
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| Izvor: | Švica |
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| PID: | 20.500.12556/DiRROS-25143  |
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| UDK: | 004.5 |
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| ISSN pri članku: | 2296-9144 |
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| DOI: | doi.org/10.3389/frobt.2025.1708987 |
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| COBISS.SI-ID: | 263645187 |
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| Avtorske pravice: | © 2025 Mavsar, Simonič and Ude. |
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| Opomba: | Nasl. z nasl. zaslona;
Opis vira z dne 6. 1. 2026;
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| Datum objave v DiRROS: | 12.01.2026 |
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| Število ogledov: | 100 |
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| Število prenosov: | 47 |
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| Metapodatki: |    |
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