首页 /研究 /The UJI Aerial Librarian Robot: A Quadcopter for Visual Library Inventory and Book Localisation
PERCEPTION

The UJI Aerial Librarian Robot: A Quadcopter for Visual Library Inventory and Book Localisation

Ester Martínez-Martín, Eric Ferrer, Ilia Vasilev, Ángel P. del Pobil

发表年份
2021
引用次数
18
访问权限
开放获取

摘要

Over time, the field of robotics has provided solutions to automate routine tasks in different scenarios. In particular, libraries are awakening great interest in automated tasks since they are semi-structured environments where machines coexist with humans and several repetitive operations could be automatically performed. In addition, multirotor aerial vehicles have become very popular in many applications over the past decade, however autonomous flight in confined spaces still presents a number of challenges and the use of small drones has not been reported as an automated inventory device within libraries. This paper presents the UJI aerial librarian robot that leverages computer vision techniques to autonomously self-localize and navigate in a library for automated inventory and book localization. A control strategy to navigate along the library bookcases is presented by using visual markers for self-localization during a visual inspection of bookshelves. An image-based book recognition technique is described that combines computer vision techniques to detect the tags on the book spines, followed by an optical character recognizer (OCR) to convert the book code on the tags into text. These data can be used for library inventory. Misplaced books can be automatically detected, and a particular book can be located within the library. Our quadrotor robot was tested in a real library with promising results. The problems encountered and limitation of the system are discussed, along with its relation to similar applications, such as automated inventory in warehouses.

关键词

RoboticsComputer scienceQuadcopterRobotArtificial intelligenceMultirotorRelation (database)Field (mathematics)DroneComputer vision

相关论文

查看 PERCEPTION 分类全部论文