Suppr超能文献

用于自动化肉类加工的传感器增强型智能夹具开发。

Sensor-Enhanced Smart Gripper Development for Automated Meat Processing.

机构信息

Antal Bejczy Center of Intelligent Robotics, Óbuda University, 1034 Budapest, Hungary.

John von Neumann Faculty of Informatics, Óbuda University, 1034 Budapest, Hungary.

出版信息

Sensors (Basel). 2024 Jul 17;24(14):4631. doi: 10.3390/s24144631.

Abstract

Grasping and object manipulation have been considered key domains of Cyber-Physical Systems (CPS) since the beginning of automation, as they are the most common interactions between systems, or a system and its environment. As the demand for automation is spreading to increasingly complex fields of industry, smart tools with sensors and internal decision-making become necessities. CPS, such as robots and smart autonomous machinery, have been introduced in the meat industry in recent decades; however, the natural diversity of animals, potential anatomical disorders and soft, slippery animal tissues require the use of a wide range of sensors, software and intelligent tools. This paper presents the development of a smart robotic gripper for deployment in the meat industry. A comprehensive review of the available robotic grippers employed in the sector is presented along with the relevant recent research projects. Based on the identified needs, a new mechatronic design and early development process of the smart gripper is described. The integrated force sensing method based on strain measurement and magnetic encoders is described, including the adjacent laboratory and on-site tests. Furthermore, a combined slip detection system is presented, which relies on an optical flow-based image processing algorithm using the video feed of a built-in endoscopic camera. Basic user tests and application assessments are presented.

摘要

抓取和物体操纵自自动化开始以来一直被认为是网络物理系统 (CPS) 的关键领域,因为它们是系统或系统与其环境之间最常见的交互方式。随着对自动化的需求扩展到越来越复杂的工业领域,带有传感器和内部决策功能的智能工具成为必需品。几十年来,CPS(如机器人和智能自主机械)已被引入肉类行业;然而,动物的自然多样性、潜在的解剖障碍和柔软、滑溜的动物组织需要使用各种传感器、软件和智能工具。本文介绍了一种用于肉类行业的智能机器手爪的开发。对该领域中使用的各种现有机器人夹具进行了全面回顾,并介绍了相关的最新研究项目。基于确定的需求,描述了新型机电设计和智能夹具的早期开发过程。描述了基于应变测量和磁编码器的集成力感测方法,包括相邻的实验室和现场测试。此外,还提出了一种组合的滑差检测系统,该系统依赖于使用内置内窥镜摄像机的视频馈送的基于光流的图像处理算法。介绍了基本的用户测试和应用评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f4a/11281046/435adaa9bd89/sensors-24-04631-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验