Suppr超能文献

用于农产品分拣加工生产线的堆积农产品深度成像的主动双激光扫描技术

Active Dual Line-Laser Scanning for Depth Imaging of Piled Agricultural Commodities for Itemized Processing Lines.

作者信息

Ali Mohamed Amr, Wang Dongyi, Tao Yang

机构信息

Fischell Department of Bioengineering, University of Maryland, College Park, MD 20742, USA.

Department of Biological and Agricultural Engineering, University of Arkansas, Fayetteville, AR 72701, USA.

出版信息

Sensors (Basel). 2024 Apr 9;24(8):2385. doi: 10.3390/s24082385.

Abstract

The accurate depth imaging of piled products provides essential perception for the automated selection of individual objects that require itemized food processing, such as fish, crabs, or fruit. Traditional depth imaging techniques, such as Time-of-Flight and stereoscopy, lack the necessary depth resolution for imaging small items, such as food commodities. Although structured light methods such as laser triangulation have high depth resolution, they depend on conveyor motion for depth scanning. This manuscript introduces an active dual line-laser scanning system for depth imaging static piled items, such as a pile of crabs on a table, eliminating the need for conveyor motion to generate high-resolution 3D images. This advancement benefits robotic perception for loading individual items from a pile for itemized food processing. Leveraging a unique geometrical configuration and laser redundancy, the dual-laser strategy overcomes occlusions while reconstructing a large field of view (FOV) from a long working distance. We achieved a depth reconstruction MSE of 0.3 mm and an STD of 0.5 mm on a symmetrical pyramid stage. The proposed system demonstrates that laser scanners can produce depth maps of complex items, such as piled Chesapeake Blue Crab and White Button mushrooms. This technology enables 3D perception for automated processing lines and offers broad applicability for quality inspection, sorting, and handling of piled products.

摘要

对堆积产品进行精确的深度成像,可为需要逐件进行食品加工的单个物体(如鱼、螃蟹或水果)的自动挑选提供重要的感知信息。传统的深度成像技术,如飞行时间法和立体视觉,缺乏对诸如食品等小物体成像所需的深度分辨率。尽管激光三角测量等结构光方法具有较高的深度分辨率,但它们依赖传送带运动进行深度扫描。本文介绍了一种用于对静态堆积物品(如桌上一堆螃蟹)进行深度成像的主动式双线激光扫描系统,无需传送带运动即可生成高分辨率的三维图像。这一进展有利于机器人从一堆物品中挑选单个物品进行逐件食品加工的感知。利用独特的几何配置和激光冗余,双激光策略在从远距离重建大视场(FOV)时克服了遮挡问题。在对称金字塔平台上,我们实现了深度重建均方误差为0.3毫米,标准差为0.5毫米。所提出的系统表明,激光扫描仪可以生成复杂物品(如堆积的切萨皮克蓝蟹和白蘑菇)的深度图。这项技术可为自动化生产线提供三维感知,并在堆积产品的质量检测、分拣和处理方面具有广泛的适用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/08cc/11054668/9e0253494728/sensors-24-02385-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