Human-robot cooperative assembly key information extraction based on GCN

Lei Meng; Weiping Fu

doi:10.1117/12.3045268

16 January 2025 Human-robot cooperative assembly key information extraction based on GCN

Lei Meng, Weiping Fu

Author Affiliations +

Proceedings Volume 13447, International Conference on Mechatronics and Intelligent Control (ICMIC 2024); 134470W (2025) https://doi.org/10.1117/12.3045268
Event: International Conference on Mechatronics and Intelligent Control (ICMIC 2024), 2024, Wuhan, China

Abstract

In order to tackle the challenge of inadequate comprehension by cooperative robots during assembly tasks, we present an innovative algorithm that leverages Graph Convolutional Neural Networks. The primary objective of this algorithm is to extract essential information relevant to assembly tasks from assembly process cards. To achieve this, we also implement an Optical Character Recognition algorithm, which effectively identifies textual information contained within the cards cells. By incorporating the Graph Convolutional Neural Network, we can then capture the underlying topological relationships among the key information elements. This comprehensive approach not only facilitates the prediction of key cell locations but also help robots to autonomously comprehend assembly tasks through an automated data mining process.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Lei Meng and Weiping Fu "Human-robot cooperative assembly key information extraction based on GCN", Proc. SPIE 13447, International Conference on Mechatronics and Intelligent Control (ICMIC 2024), 134470W (16 January 2025); https://doi.org/10.1117/12.3045268

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