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An S-SOM method based on binocular vision for configuration detection of concentric cable-driven manipulators

Published online by Cambridge University Press:  27 February 2026

Zhonghui Wei ,
Weitao Li ,
Jie Li ,
Naijun Zhang ,
Yuxia Li  and
Zonggao Mu Open the ORCID record for Zonggao Mu [Opens in a new window]
Zhonghui Wei
Affiliation:
School of Mechanical Engineering, Shandong University of Technology, Zibo, China
Weitao Li
Affiliation:
School of Mechanical Engineering, Shandong University of Technology, Zibo, China
Jie Li
Affiliation:
School of Artificial Intelligence, Shenzhen Polytechnic University, Shenzhen, China
Naijun Zhang
Affiliation:
Shandong Jite Industrial Technology Company Limited, China
Yuxia Li
Affiliation:
School of Artificial Intelligence, Shenzhen Polytechnic University, Shenzhen, China
Zonggao Mu*
Affiliation:
School of Mechanical Engineering, Shandong University of Technology, Zibo, China Institute of Modern Agricultural Equipment, Shandong University of Technology, China Zibo Key Laboratory of Collaborative Robots, AUBO(Shandong) Intelligent Robot Co, China
*
Corresponding author: Zonggao Mu; Email: muzonggaook@163.com
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Abstract

The concentric cable-driven manipulator (CCDM) is slender enough to work in narrow oral environments. However, the configuration detection of the CCDM with two segments is the key issue to realize the servo control and force sensing. In this paper, a Segmented Self-Organizing Map (S-SOM) method is presented for configuration detection of the CCDM without preset markers. Firstly, two-dimensional point cloud of the CCDM is acquired by the binocular vision. Secondly, the dimension reduction of point cloud is realized by principal component analysis to avoid noises and eliminate redundant information. Then, the threshold is set to distinguish the segment with different diameters that need to be trained independently. Thirdly, quantization errors and topological errors are designed to select different training parameters of the CCDM with two segments. Finally, the experimental results show that the average point-to-point distance error is less than 2.57 mm. The effectiveness of the proposed S-SOM method for configuration detection of the CCDM is verified.

Keywords

concentric cable-driven manipulatorsthe binocular visionthe S-SOM methodPCA

Information

Type
Research Article
Information
Robotica , Volume 44 , Issue 2 , February 2026 , pp. 684 - 697
Copyright
© The Author(s) 2026. Published by Cambridge University Press

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