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All Journal Jurnal Inotera
Raditya Fadhil Arva
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Computer Science & IT Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

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A YOLO-Based Machine Learning Framework for Detection of Soft Pneumatic Actuator Bending Angles Syahirul Alim Ritonga; Raditya Fadhil Arva; Sarah Iftin Atsani; Mohammad Ardyansah; Herianto
Jurnal Inotera Vol. 10 No. 1 (2025): January-June 2025
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol10.Iss1.2025.ID448

Abstract

The bending angle of soft pneumatic actuator (SPA) is a critical parameter influencing their reliability and effectiveness across various applications. Conventional measurement methods are often labour-intensive and impractical for experiments requiring multiple trials, creating a need for efficient, non-invasive techniques. This study proposes a machine learning framework leveraging YOLO (You Only Look Once) models to detect SPA bending angles from image data, eliminating the need for additional hardware. A comprehensive dataset of SPAs under varying actuation pressures, with meticulously labelled bending angles, was curated to train a YOLO-based regression model. The results highlight the model's strong performance, achieving a recall of 99.1%, precision of 70%, and mean average precision (mAP) scores of 86.42% (IoU 0.5) and 84.35% (IoU 0.5–0.95). Low training and validation losses indicate high accuracy in bounding box predictions, object-background differentiation, and object classification. Optimized learning rates ensured efficient parameter updates, achieving convergence without overfitting. The proposed framework demonstrates a robust balance between accuracy, robustness, and efficiency, making it a practical solution for reliable SPA bending angle detection in real-world applications. This study underscores the potential of machine learning-driven techniques to streamline SPA characterization, offering a scalable and non-invasive alternative to traditional methods.
Design and Development of a Low-Cost Programmable Air Regulator for Soft Pneumatic Actuators Ritonga, Syahirul Alim; Sarah Iftin Atsani; Mohammad Ardyansah; Raditya Fadhil Arva; Herianto; Adrian Axel Yohannes
Jurnal Inotera Vol. 10 No. 1 (2025): January-June 2025
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol10.Iss1.2025.ID488

Abstract

Soft Pneumatic Actuators (SPAs) are widely utilized due to their affordability, simplicity, and ability to produce diverse movements such as bending and twisting by regulating air pressure. However, precise air pressure control remains a significant challenge in achieving desired actuator motions and maintaining performance consistency. While commercial programmable air regulators exist, their high cost often limits accessibility for budget-conscious research and educational institutions. This study addresses this challenge by designing and developing a low-cost programmable air regulator tailored for SPAs. Utilizing widely available and inexpensive components, the system aims to provide precise and reliable pressure control, democratizing SPA technology for researchers, small industries, and educational institutions. The regulator employs a stepper motor with a 1.8-degree step resolution and a 1:4 gear ratio, offering fine granularity in pressure adjustments. Carefully selected speed (1000 steps/s) and acceleration (500 steps/s) parameters ensure consistent operation under repetitive use. The program code of Arduino UNO microcontroller developed in this study can be readily adopted by researchers and practitioners. The regulator consistently achieves desired pressures through precise control of motor revolutions, proving to be a viable, cost-effective alternative to expensive commercial options.
Co-Authors Adrian Axel Yohannes Herianto Mohammad Ardyansah Ritonga, Syahirul Alim Sarah Iftin Atsani Syahirul Alim Ritonga