基于工艺建模的机器人缝纫方法研究

IF 2.1 Q3 ROBOTICS
Fengming Li, Dang Hou, Tianyu Fu, Jiexin Song, Wenbin He, Rui Song
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引用次数: 0

摘要

目前,服装缝制大多依靠人工,机器人缝制已成为一种趋势。然而,不同的服装款式有不同的缝纫要求。这给机器人缝纫带来了挑战,而解决这一挑战的关键在于机器人操作轨迹的规划。虽然缝纫部件的形状多种多样,但我们可以将其分解为最基本的直线和曲线。为了解决机器人缝纫过程中的轨迹规划问题,本文将缝纫任务分为直线和曲线两部分,并提出了一种基于任务过程分解的新型机器人缝纫方法。首先,将机器人复杂缝纫任务分为直线和曲线两部分。根据延展性预测缝纫张力,实现基于阻抗控制的机器人直线缝纫。同时,在对曲线边缘进行线形识别的基础上,进行轨迹规划,实现曲线缝纫。最后,在搭建的物理实验平台上实现了机器人在不同曲率下的复杂缝合。验证了基于过程建模的机器人缝纫方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Research on robot sewing method based on process modeling

Research on robot sewing method based on process modeling

At present, most clothing sewing relies on manual labor, and robot sewing has become a trend. However, different clothing styles have various sewing requirements. This poses a challenge for robot sewing, and the key to solving this challenge lies in the planning of robot operation trajectories. Although the shapes of sewing components are diverse, we can decompose them into the most basic straight lines and curved edges. In order to solve the trajectory planning problem in robot sewing process, this paper divides the sewing task into two parts: straight line and curve, and proposes a new robot sewing method based on task process decomposition. Firstly, The robot complex sewing task is divided into two parts: straight line and curve. Based on the extensibility, the sewing tension is predicted, and the robot linear sewing based on impedance control is realized. At the same time, the trajectory planning is carried out on the basis of the line identification of the curved edge to realize the curve sewing. Finally, the robot complex stitch sewing under different curvatures is realized on the built physical experiment platform. It is verified that the effectiveness of the robot sewing method based on process modeling.

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来源期刊
CiteScore
3.80
自引率
5.90%
发文量
50
期刊介绍: The International Journal of Intelligent Robotics and Applications (IJIRA) fosters the dissemination of new discoveries and novel technologies that advance developments in robotics and their broad applications. This journal provides a publication and communication platform for all robotics topics, from the theoretical fundamentals and technological advances to various applications including manufacturing, space vehicles, biomedical systems and automobiles, data-storage devices, healthcare systems, home appliances, and intelligent highways. IJIRA welcomes contributions from researchers, professionals and industrial practitioners. It publishes original, high-quality and previously unpublished research papers, brief reports, and critical reviews. Specific areas of interest include, but are not limited to:Advanced actuators and sensorsCollective and social robots Computing, communication and controlDesign, modeling and prototypingHuman and robot interactionMachine learning and intelligenceMobile robots and intelligent autonomous systemsMulti-sensor fusion and perceptionPlanning, navigation and localizationRobot intelligence, learning and linguisticsRobotic vision, recognition and reconstructionBio-mechatronics and roboticsCloud and Swarm roboticsCognitive and neuro roboticsExploration and security roboticsHealthcare, medical and assistive roboticsRobotics for intelligent manufacturingService, social and entertainment roboticsSpace and underwater robotsNovel and emerging applications
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