Enhanced six-axis robotic arm intelligent scalpel sorting system based on YOLOv4-tiny

Tiehong Li; Jin Li; Junbang Jiang; Xinyu Liu

doi:10.1117/12.3035178

19 July 2024 Enhanced six-axis robotic arm intelligent scalpel sorting system based on YOLOv4-tiny

Tiehong Li, Jin Li, Junbang Jiang, Xinyu Liu

Proceedings Volume 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024); 132133G (2024) https://doi.org/10.1117/12.3035178
Event: International Conference on Image Processing and Artificial Intelligence (ICIPAl2024), 2024, Suzhou, China

Abstract

In order to reduce the workload of healthcare workers during surgery and free them from the task of recognising and delivering surgical tools, this project designs a vision-based robotic arm scalpel sorting system. To improve the accuracy and recognition speed, this design proposes an optimisation approach for YOLOv4-tiny recognition, which introduces a depth-separable convolutional lightweight backbone network in the feature extraction stage to reduce the computational volume of the model, which improves the FPS by 3.3%, the mAP by 4.3%, and the size of the model is reduced by41%compared to YOLOv4-tiny. In the experimental test, this design can automatically identify different scalpels, the success rate of surgical tool identification can be up to 95%, and the success rate of grasping can be up to 94%. This intelligent recognition system has the characteristics of higher growth nature, better reliability and application of medical devices, which can be used as a reference for research instead of complex medical and surgical environments.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Tiehong Li, Jin Li, Junbang Jiang, and Xinyu Liu "Enhanced six-axis robotic arm intelligent scalpel sorting system based on YOLOv4-tiny", Proc. SPIE 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024), 132133G (19 July 2024); https://doi.org/10.1117/12.3035178

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KEYWORDS

Equipment

Robotics

Intelligence systems

Data modeling

Education and training

Image processing

Convolution

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