Inventory

Case Study

Singapore public libraries have deployed a mobile robot, AuRoSS (Autonomous Robotic Shelf Scanning System) to automate self-reading process. AuRoSS is a creation by A*STAR (Agency for Science, Technology and Research) under the commission of the Singapore National Library Board. Equipped with a RFID scanner, AuRoSS roves around library stacks, scan shelves, and generates reports of missing or misplaced books (Li et al., 2015). The implementation of robotic technology at Singapore public libraries achieves much success. AuRoSS attains 99 percent detection accuracy (Blackmore, 2016). It saves each library 3,500 staff hours per year (Nolan, 2022). Consequently, libraries enjoy a saving of operating costs and staff time, fill the labor gaps, streamline workflows, reduce human errors, and receive fewer patron complaints (Liau, 2019; South China Morning Post, 2022). AuRoSS is also deployed at Temasek Polytechnic, a post-secondary institution in Singapore, to perform inventory tasks. The robot, nicknamed Robbie, is part of the institution’s Smart Campus Initiative and saves library 16 staff-hours a day (Seow, 2019). With its four arms equipped with RFID scanner, Robbie moves swiftly along the bookshelves[1]. Students can see the “guts" and "skeleton” through its transparent casing and observe how its mechanism works.

Use Case - Nanjing University

Several academic libraries in China are early adapters of robotic technology in aiding inventory operation. Nanjing University Library, in collaboration with the Department of Computer Science, developed an RFID-based inventory robot (Shen et al., 2016). Now in its third generation, the robot can scan 10,000 books in an hour, with less than 1% missing rate[2]. It can update item location in real time and significantly improves the successful rate of locating an item. The robot also aids book shelving by offering most efficient route. It further generates missing or misplaced reports for library staff to act on. The benefits of this inventory robot include cost reduction, efficiency, accuracy, standardized operation, and service improvement (Fan & Shao, 2018).

Wuhan University Library is another site to implement the RFID-based robot system developed by Nanjing University. The post-implementation review showed that the robot achieved 98% of scanning accuracy rate, almost 2% better than the rate by staff members. The robot completed the task more than five time faster than the average time spent by staff members (Xia et al., 2019).

Use Case - Ocean University of China

In another case, developers at the Ocean University of China created an RFID-based mobile robot for locating specific books and transmitting search results via wireless network (Li et al., 2012). The experiment shows that the robot effectively located desired books and avoided obstacles in the library (Zhang et al., 2012). Also, at the same institution, Tang et al. (2018) designed a mobile robot capable of calculating the best paths between current and target locations using RFID technology and maneuvering narrow aisle across ranges and rows of bookshelves (Tang et al., 2018).

Left: RFID-equipped mobile robot system model (Zhang et al., 2012)

Use Case - LibBot at MIT

Ehrenberg et al. (2007) at Massachusetts Institute of Technology created, LibBot, an RFIP-equipped mobile robot with an RFID reader, to automate shelf-reading task. In a single-shelf experiment, LibBot accurately determined the shelf order of books over 2 cm thick and detected misplaced books using RFID tags embedded in books. However, LibBot is less successful in a two-shelves experiment.

Left: LibBot with mounted RFID antenna in front of a book shelf (Ehrenberg et al., 2007)

Case Study - Library Inventory Management Robot

At the Sri Ramakrishna Institute of Technology in India, researchers designed a prototype line following robot that follows a predetermined path and searches for misplaced books by barcode. The experiment shows that the robot can locate the current position of a book and track the proper shelf order of books on a shelf (Thirumurugan, 2010).

Left: Book search and arrangement operation of a line following robot

Case Study - Autonomous Library Robot using QR Code

In another project, researchers at the Northwestern Polytechnical University in China developed a mobile robot integrated with the binocular vision and QR code identification techniques. The binocular vision is used to enhance robot’s capability in positioning and navigation, obstacle avoidance, and pulling books from or returning them to the shelf with robotic arms. The QR code is used to guide robot in searching of target books and determining its location. The results from simulations and experiments in a control environment show the combination of these two technologies is effective and robust (Yu et al., 2019).