</sup>) ,提出一種映射網(wǎng)格矩陣檢測法,對三維點云數(shù)據(jù)進行垂直分析,采用最小二乘法對碼垛紙箱在垂直方向的平面形態(tài)數(shù)據(jù)進行擬合處理,將三維數(shù)據(jù)進行網(wǎng)格化處理,轉(zhuǎn)換為二維數(shù)據(jù),再進行平面擬合處理,得到一個擬合平面高度和平面面積的矩陣數(shù)據(jù),進而計算出紙箱的數(shù)量。-龍源期刊網(wǎng)" />

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基于點云數(shù)據(jù)的智能盤點技術(shù)研究

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中圖分類號:F253.9 文獻標(biāo)志碼:ADOI: 10.13714/j.cnki.1002-3100.2025.09.014

Abstract: In an automated stereoscopic warehouse, the inventory of cardboard box goods on pallets requires the use ofa stacker crane to transport the pallets from the vertical warehouse to the entry and exit platforms for manual inventory, and then transport the pallets back to the vertical warehouse. Onlythencantheinventoryofapalletbecompleted,and the entire calculation process will inevitably lead to time-consuming and labor-intensive work. In order to improve inventory efficiency andreduce energy consumption, and avoid the transportation of stacker cranes during inventory work, this articleadopts an intelligent inventory technology based on point cloud data to directly inventory the goods on pallets in the vertical warehouse,without the need to manually transport palletsto the entry and exit platforms for inventory. This technology mainly uses LiDAR to collect three-dimensional point cloud data (x,y,z) of cardboard boxes on pallets. A mapping grid matrix detection method is proposed to vertically analyze the three-dimensional point cloud data,and the least squares method is used to fit the plane shape data of stacked cardboard boxes in the vertical direction. The three-dimensional data is gridded and converted into two-dimensional data,and then subjected to plane fitting processing to obtain a matrix dataof fitting plane height and plane area,and then calculate thenumberofcardboard boxes.

Key words: point cloud data; stereoscopic warehouse; least squares method;planar detection; LiDAR

0引言

在全球化及電子商務(wù)的日益發(fā)展下,立體倉庫作為存儲效率及空間利用率的重要提升者,已在現(xiàn)代供應(yīng)鏈管理中扮演著不可或缺的角色。(剩余6366字)

目錄
monitor