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Use Cases | 3D Volumetric Measurement for Warehouses |仓储3D体积量方...

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Author: Livox Pioneer | Time: 2022-11-7 17:42:24 | Smart city|
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Posted on 2022-11-7 17:42:24| All floors |Read mode
In the logistics and warehousing industries, determining the volumes and quantities of materials and their inbound and outbound status is vital for the management of production inventory.

Traditionally, this is done manually. For example, in coal warehousing and production, the volume of coal is typically measured with a total station held manually by a human operator. However, such conventional solution comes with constant challenges, such as a lack of technical means, significant margins of error, low efficiency, and monitoring difficulties.

Inside a typical coal warehouse

In static scenarios such as those involving coal, rapid scanning is less of a priority. Therefore, users can maximize non-repetitive scanning by prolonging the scan duration of a Livox LiDAR, which delivers greater point cloud density and thus more granular data for clients.

It is this feature that has enabled our partners SF Technology and Wuyi Yuntong to address pain points in the coal industry, by developing intelligent measurement systems that generate accurate data and real-time updates.

Intelligent Inventory System | SF Technology

The accurate measurement of large bulk volumes has been a thorny issue in the coal industry for years. A coal pile usually weighs at least 10,000 tonnes, which means that a 1% margin of error in its measurement can lead to losses in the tens of millions of yuan. Evidently, improving the accuracy of bulk measurement is crucial to inventory management and the calculation of material consumption.

The traditional method of measuring large coal heaps involves the use of a total station and RTK spot measurement, along with manual extraction of features. In these instances, tall coal piles are usually difficult for human workers to climb up, thus making feature extraction incredibly challenging. Meanwhile, such operations are inefficient due to the low data density generated by spot measurement, which reduces the accuracy of coal volume measurements.

In response to this pain point, SF Technology developed an intelligent inventory system using multiple sensors such as Livox LiDARs and cameras. The system makes full use of LiDARs to accurately collect distance data for 3D modeling of targets, as well as AI algorithms to automatically calculate coal volumes and update them in real time. This enables users to control warehouse conditions easily and directly through the web interface.

The system can perform a range of functions such as completing a designated inventory plan, periodic data collection, automatic 3D point cloud generation, auto-splicing to create whole volume data, auto-calculation of bulk volumes in defined areas, and auto-generation of computation reports. As a result, it brings greater efficiency and accuracy to the automation of inventory management.

3D warehouse view

Real-time point cloud image of coal heaps

Warehouse Inventory Management | Wuyi Yuntong

Traditional measurement methods usually involve manual and regular stocktaking. Due to their limited detection range and measurement angles, data cannot be updated in real time effectively.

The solution adopted by Wuyi Yuntong utilizes LiDARs and gimbals, which assist operators in selecting the optimal roof equipment with a wider and more flexible and comprehensive coverage of a warehouse. By splicing multi-point cloud files, the entire inventory of a warehouse can be displayed in 3D, which enables dynamic and real-time exchange of information on its items. At the same time, the volumes of materials can be measured and computed intelligently and in real time by segmenting their point clouds through positioning and virtual fencing technology. With these features, users can gather and integrate comprehensive and dynamic data, to manage safety control as well as entry and exit of goods flexibly and precisely.

3D modeling of a coal warehouse

The above two solutions utilize point clouds from LiDARs to upgrade non-structured image data to structured 3D data. On top of delivering cost-efficient, rigorous, and precise volumetric measurements, they provide an effective monitoring function for avoiding risks of theft, and expand the scope of surveillance by increasing data dimensions. As a result, the solutions greatly enhance the real-time nature and deterrent effect of data monitoring, therefore marking a significant step forward in resolving the pain points of the coal industry.





在煤炭或类似的静态场景中,由于场景本身对响应时间要求不高,通过使用Livox 激光雷达并延长激光雷达的扫描时间,利用时间换取空间充分发挥非重复扫描的优势,即可获得稠密点云密度,为客户需求提供更精细化的数据。


智能盘库系统 | 顺丰科技
堆体测量,尤其是大型堆体体积测量如何提高准确性,是困扰煤炭行业多年的难题。正常的大型堆体一般有万吨以上,即使测量误差可控制在1% 以内,其价值损失也高达千万元以上。可见提高大型堆体体积测量的准确性,对企业加强物资管理、核算物料消耗具有重要现实意义。


针对这一行业痛点,顺丰科技利用Livox 激光雷达、摄像头等多传感器开发了一套智能盘库系统。该系统充分利用激光雷达对距离信息的精准采集实现对目标物体的3D建模,利用AI算法自动测算煤炭体积并实时更新,在WEB端即可直观地管控仓库情况。




仓库库存管理 | 物易云通




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