Multimodal Learning‐Based Proactive Human Handover Intention Prediction Using Wearable Data Gloves and Augmented Reality

Multimodal Learning‐Based Proactive Human Handover Intention Prediction Using Wearable Data Gloves and Augmented Reality

Efficient object handover between humans and robots holds significant importance within collaborative manufacturing environments. Enhancing the efficacy of human–robot handovers involves enabling robots to comprehend and foresee human handover intentions. This article introduces human‐teaching–robot...

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Bibliographic Details
Main Authors: Rui Zou, Yubin Liu, Jie Zhao, Hegao Cai
Format: Article
Language:English
Published: Wiley 2024-04-01
Series:Advanced Intelligent Systems
Subjects:
human intention predictions
human–robot handovers
multimodal learning
robot controls
Online Access:https://doi.org/10.1002/aisy.202300545

Internet

https://doi.org/10.1002/aisy.202300545

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