Purpose

The purpose of this study is to design, program and implement an intelligent robot for shelf-reading. an essential task in library maintenance is shelf-reading, which refers to the process of checking the disciplines of books based on their call numbers to ensure that they are correctly shelved. Shelf-reading is a routine yet challenging task for librarians, as it involves controlling call numbers on the scale of thousands of books promptly.

Design/methodology/approach

Leveraging the strength of autonomous robots in handling repetitive tasks, this paper introduces a novel vision-based shelf-reader robot, called \emph{Pars} and demonstrate its effectiveness in accomplishing shelf-reading tasks. Also, this paper proposes a novel supervised approach to power the vision system of \emph{Pars}, allowing it to handle motion blur on images captured while it moves. An approach based on Faster R-CNN is also incorporated into the vision system, allowing the robot to efficiently detect the region of interest for retrieving a book’s information.

Findings

This paper evaluated the robot’s performance in a library with $120,000 books and discovered problems such as missing and misplaced books. Besides, this paper introduces a new challenging data set of blurred barcodes free publicly available for similar research studies.

Originality/value

The robot is equipped with six parallel cameras, which enable it to check books and decide moving paths. Through its vision-based system, it is also capable of routing and tracking paths between bookcases in a library and it can also turn around bends. Moreover, \emph{Pars} addresses the blurred barcodes, which may appear because of its motion.

中文翻译：

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使用更快的 R-CNN 的基于自主视觉的货架阅读器机器人

目的

本研究的目的是设计、编程和实现一种用于货架阅读的智能机器人。图书馆维护中的一项基本任务是书架阅读，这是指根据书号检查书籍的学科以确保它们正确上架的过程。书架阅读对图书馆员来说是一项例行但具有挑战性的任务，因为它涉及迅速控制数千本书的索书号。

设计/方法/方法

利用自主机器人在处理重复性任务方面的优势，本文介绍了一种新型的基于视觉的货架阅读机器人，名为 \emph{Pars}，并展示了其在完成货架阅读任务方面的有效性。此外，本文提出了一种新颖的监督方法来为 \emph {Pars} 的视觉系统提供动力，使其能够处理在移动时捕获的图像上的运动模糊。基于 Faster R-CNN 的方法也被纳入视觉系统，使机器人能够有效地检测感兴趣的区域以检索书籍信息。

发现

这篇论文评估了机器人在拥有 12 万美元图书的图书馆中的表现，发现了图书丢失和错位等问题。此外，本文介绍了一个新的具有挑战性的模糊条形码数据集，可免费用于类似的研究。

原创性/价值

该机器人配备了六个并行摄像头，可以检查书籍并决定移动路径。通过其基于视觉的系统，它还能够路由和跟踪图书馆书柜之间的路径，还可以转弯。此外，\emph{Pars} 解决了可能因其运动而出现的模糊条形码。