RFID技术实现标签包装的三维重建

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"通过RFID系统对标签包装进行三维重建" 在物流行业中，3D重建技术已经被引入来监控包裹的放置情况。现有的3D重建方法主要依赖计算机视觉或传感器为基础的方法，这些方法往往受限于视线条件或电池寿命。本文提出的"RF-3DScan"是一种新颖的基于被动RFID（无线频率识别）的3D重建技术，它通过在包裹表面附着多个参考标签来进行三维重建。 RF-3DScan的核心思想是，通过在一个约束的二维空间内沿直线移动天线，获取包裹上参考标签的RF信号。这些信号包含了关于标签位置的关键信息。通过提取信号的相位差，可以构建每个标签的角度剖面。这种方法使得RF-3DScan能够比较不同参考标签的角度剖面，从而推算出包裹的三维结构。在实际应用中，由于RFID技术无需直接视线接触，因此不受视线阻挡的影响，同时也不受电池寿命限制，因为RFID标签通常是无源的，仅需通过天线接收射频能量即可工作。这一特性使得RF-3DScan在物流仓库、自动化分拣中心等环境中具有显著优势，能准确地跟踪和定位被RFID标签标记的包裹，即使在视线不佳或环境复杂的情况下也能有效工作。此外，RF-3DScan还可能有助于提升物流效率，减少人为错误。例如，在自动化仓库中，系统可以通过实时重建包裹的三维位置，精确指导机器人执行拣选和存放任务。此外，通过对包裹的三维建模，还可以检测包裹的形状和体积，从而优化存储空间的利用。尽管RF-3DScan提出了一种创新的3D重建解决方案，但该技术也面临一些挑战。例如，RF信号的干扰可能导致相位测量的不准确性，而且在密集的RFID标签环境中，信号重叠可能会增加计算复杂性。未来的研究可能需要关注如何优化信号处理算法，提高定位精度，并解决大规模部署中的信道拥堵问题。 "通过RFID系统对标签包装进行三维重建"的研究论文揭示了一种利用RFID技术进行非视线、无电池依赖的3D重建新方法，为物流行业的自动化和智能化提供了新的可能。通过不断的技术迭代和优化，RF-3DScan有望成为物流领域的一个重要工具，提升整个供应链的效率和可靠性。

3-Dimensional Reconstruction on Tagged Packages

via RFID Systems

Yanling Bu, Lei Xie, Jia Liu, Bingbing He, Yinyin Gong and Sanglu Lu

State Key Laboratory for Novel Software Technology, Nanjing University, China

yanlingbu@foxmail.com, lxie@nju.edu.cn, jialiu.cs@gmail.com,

{hebb, yygong}@dislab.nju.edu.cn, sanglu@nju.edu.cn

Abstract—Nowadays, 3D reconstruction has been introduced

in monitoring the package placement in logistic industry-related

applications. Existing 3D reconstruction methods are mainly

based on computer vision or sensor-based approaches, which are

limited by the line-of-sight or battery life constraint. In this paper,

we propose RF-3DScan to perform 3D reconstruction on tagged

packages via passive RFID, by attaching multiple reference tags

onto the surface of the packages. The basic idea is that by

moving the antenna along straight lines within a constrained

2-dimensional space, the antenna obtains the RF-signals of the

reference tags attached on the packages. By extracting the phase

differences to build the angle proﬁle for each tag, RF-3DScan

can compare the angle proﬁles of the different reference tags and

derive their relative positions, then further determine the package

orientation and stacking for 3D reconstruction. We implement

RF-3DScan and evaluate its performance in real settings. The

experiment results show that the average identiﬁcation accuracy

of the bottom face is about 92.5%, and the average estimation

error of the rotation angle is about 4.08

◦

I. INTRODUCTION

Nowadays, the traditional logistic industry-related appli-

cations, such as warehouse management and logistic trans-

portation, are emerging with brand new requirements. For

example, during the process of warehouse management or

logistic transportation, the packages are usually required to be

placed according to some speciﬁed regulations. In particular,

in regard to a single package, if it contains orientation-sensitive

goods, such as chemical reagents or precision instruments,

then it is prohibited from being rollover or upside down;

in regard to multiple packages, they are also required to be

precisely arranged in some speciﬁed order, e.g., heavy objects

are placed on the bottom, whereas light objects are placed

on the top, to ensure safety in the transportation. To deal

with the above requirements, the technology of 3-dimensional

(3D) reconstruction has been introduced to tackle these issues

in monitoring the package placement. 3D reconstruction is a

process of capturing the shape and appearance of a single or

multiple real objects. In principle, there are two key aspects

to realize 3D reconstruction for packaged objects: 1) Package

orientation for a single object, it refers to determining the

relative orientation for each package, i.e., ﬁguring out the

bottom/top face, as well as the angles of the other vertical sides

for the speciﬁed object in the speciﬁed coordinate system. 2)

Package stacking for multiple objects, it refers to determining

the relative stacking situation for multiple packages, i.e.,

performing the relative localization of multiple objects.

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Fig. 1. 3D reconstruction on tagged packages via mobile scanning

Existing 3D reconstruction methods are mainly based on

computer vision or sensor-based approaches. Computer vision-

based approaches leverage the cameras to capture the appear-

ance and build the 3D proﬁles of objects [1, 2]. They are able

to reconstruct the shape of objects in a vivid approach. The

main disadvantage is the line-of-sight constraint in capturing

images, which leads to blind angles in 3D reconstruction

with only one ﬁxed camera. Sensor-based approaches usually

leverage inertial sensors attached to the items to detect the

orientation variation of the speciﬁed items [3, 4]. However,

they suffer from high hardware cost of the sensors, as well

as the limited battery life for the sensors. Fortunately, the

rising use of RFID technology in the logistic industry has

brought brand new opportunities to 3D reconstruction on

packaged objects. In current logistic industry, RFID tags have

been widely used to label the packages with exact logistics

information. In comparison to the above two approaches, the

passive RFID tag is battery-free and very cheap, and the

backscatter-based communication from RFID is not limited

by the line of sight requirement. Most importantly, for most

logistic applications, the RFID systems are already deployed

in the sites to scan and identify the tagged packages.

Therefore, in this paper, we propose RF-3DScan, which

aims to perform 3D reconstruction on packaged objects via

the RFID systems (in Fig. 1). Our idea is based on the

observation that by attaching multiple tags onto the surface

of the packages, we are able to derive the 3D orientation of

each single package and the 3D stacking situation of multiple

packages according to the backscattered RF-signals from these

reference tags. Our approach of RF-3DScan is as follows: We

attach a set of reference tags on the surface of the packages,

then we utilize a single RFID antenna to continuously scan

the tagged packages, while the antenna is moving along

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