Trajectory control based on On/Off, Fuzzy Logic and Convolutional Neural Networks for an Industrial Robot Arm: an experimental comparison

IF 1.3 4区工程技术 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

IEEE Latin America Transactions Pub Date : 2024-06-18 DOI:10.1109/TLA.2024.10562261

José Raúl Castro;David Rosales;Carlos Calderon-Cordova

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引用次数: 0

Abstract

The objective of the present study is to compare three control approaches: ON/OFF control, fuzzy logic, and convolutional neural networks (CNN) implemented in Python for controlling the real-time trajectory tracking of a six-axis industrial robotic arm. This analysis has significant applications in fields that require a high level of precision, such as automated welding and surgical interventions in the medical domain. To evaluate the performance and adaptability of the control models, we will analyze the results using metrics such as Mean Squared Error (MSE), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), as well as metrics including Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), Jaccard Index, and Pearson's correlation coefficient. The results obtained reveal valuable information about the advantages and limitations of each control approach, highlighting the effectiveness of CNNs in visual perception and trajectory tracking. The ability of CNNs to interpret visual complexities is presented as a key factor for their success in industrial robotics and automation applications, suggesting a promising future for these technologies in dynamic environments.

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基于开/关、模糊逻辑和卷积神经网络的工业机械臂轨迹控制：实验比较

本研究旨在比较三种控制方法：开/关控制、模糊逻辑和用 Python 实现的卷积神经网络 (CNN)，以控制六轴工业机械臂的实时轨迹跟踪。这项分析在要求高精度的领域有着重要的应用，如医疗领域的自动焊接和外科干预。为了评估控制模型的性能和适应性，我们将使用平均平方误差 (MSE)、平均绝对误差 (MAE)、均方根误差 (RMSE) 等指标，以及峰值信噪比 (PSNR)、结构相似性指数 (SSIM)、Jaccard 指数和皮尔逊相关系数等指标来分析结果。所获得的结果揭示了每种控制方法的优势和局限性，凸显了 CNN 在视觉感知和轨迹跟踪方面的有效性。CNN 解释视觉复杂性的能力是其在工业机器人和自动化应用中取得成功的关键因素，这表明这些技术在动态环境中大有可为。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Latin America Transactions COMPUTER SCIENCE, INFORMATION SYSTEMS-ENGINEERING, ELECTRICAL & ELECTRONIC

CiteScore

3.50

自引率

7.70%

发文量

192

审稿时长

3-8 weeks

期刊介绍： IEEE Latin America Transactions (IEEE LATAM) is an interdisciplinary journal focused on the dissemination of original and quality research papers / review articles in Spanish and Portuguese of emerging topics in three main areas: Computing, Electric Energy and Electronics. Some of the sub-areas of the journal are, but not limited to: Automatic control, communications, instrumentation, artificial intelligence, power and industrial electronics, fault diagnosis and detection, transportation electrification, internet of things, electrical machines, circuits and systems, biomedicine and biomedical / haptic applications, secure communications, robotics, sensors and actuators, computer networks, smart grids, among others.