Pattern recognition based movement control and gripping forces control system on arm robot model using LabVIEW

Nur Jamiludin Ramadhan, N. Lilansa, Afaf Fadhil Rifa’i, Hoe D. Nguyen
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引用次数: 4

Abstract

Most arm robot has an inefficient operating time because it requires operator to input destination coordinates. Besides, main problem of arm robot is object’s vulnerability when it is manipulated by the robot. This research goals is to develop an arm robot control system which has ability to automatically detect object using image processing in order to reduce operating time. It is also able to control gripping force for eliminating damage to objects caused by robot gripper. This research is implemented in LabVIEW 2011 software to control arm robot model which can represent industrial scale robot. The software is designed with informative visualization to help user learn and understand robotic control concept deeply. The system can automatically detect object position based on pattern recognition method which has four steps: pre-processing process to initialize picture taken by camera, segmentation process for separating object from the background, classification process to determine characteristics of object, and position estimation process to estimate object position in the picture. The object’s position data are then calculated by using kinematic equation to control the robot’s motion. The results show that the system is able to detect object and move the robot automatically with accuracy rate in x-axis is 95.578 % and in y-axis is 92.878 %. The system also implements modified PI control method with FSR as input to control gripping force with maximum overshoot value 10 %. Arm robot model control system developed is successfully meet the expectation. The system control can be implemented to industrial scale arm robot with several modification because of kinematic similarity between model and industrial scale robot.
基于模式识别的手臂机器人运动控制与夹持力控制系统
大多数手臂机器人由于需要操作者输入目标坐标而存在效率低下的问题。此外,手臂机器人的主要问题是机器人操纵物体时的脆弱性。本课题的研究目标是开发一种利用图像处理技术自动检测物体的手臂机器人控制系统,以减少操作时间。还可以控制夹持力,消除机器人夹持器对物体的损伤。本研究在LabVIEW 2011软件中实现了能够代表工业规模机器人的手臂机器人控制模型。软件采用信息可视化设计,帮助用户深入学习和理解机器人控制概念。该系统基于模式识别方法自动检测目标位置,该方法分为四个步骤:预处理过程初始化相机拍摄的图像,分割过程将目标从背景中分离出来,分类过程确定目标的特征,位置估计过程估计目标在图像中的位置。然后利用运动学方程计算物体的位置数据来控制机器人的运动。结果表明,该系统能够自动检测物体并实现机器人的自动移动,在x轴和y轴上的准确率分别为95.578%和92.878%。系统还实现了以FSR为输入的改进PI控制方法,以最大超调量10%控制夹持力。开发的手臂机器人模型控制系统成功地满足了期望。由于模型与工业规模机器人的运动相似,经过多次修改,该系统控制可以实现对工业规模手臂机器人的控制。
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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CiteScore
0.70
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10
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