What Is It?
Inventory is the “process of checking all the items on a library's shelves against a list of holdings to identify for replacement or deselection those missing and not checked out” (Reitz, 2013). Conducting inventory through shelf reading on a regular basis is essential for maintaining collection integrity and accessibility, reducing patron’s frustration, and minimizing needs for staff to search for missing or misplaced items. Shelf-reading is traditionally performed by library staff and is a tedious, labor-intensive, and time-consuming activity. Due to its monotonous and repetitive nature, shelf reading is an ideal task that can be performed by a robot.
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
Use Case - Robotic Library System
At the National Institute of Advanced industrial Science and Technology in Japan, researchers built an information structured environment, called u-RT space, in which physical objects are tagged and connected with RFID tags. Equipped with a gripper and four RFID tag readers, a librarian robot is designed to navigate within this physical space, pick up books on the table, bring it to the bookshelf, and place it in the proper order on the shelf. The testing results showed feasibility of the prototype (Kim, Ohara, et al., 2008; Kim, Sugawara, et al., 2008).
Left: The librarian robot system, the intelligent floor, and the intelligent bookshelf
Below: Book handling
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).
References
411ninja (January 10, 2021). Robots can put away books, but they can’t do a reference interview: The future of robotics in the library. INF506 Online Journal. https://thinkspace.csu.edu.au/triciainf506/2021/01/10/olj-18-robots-can-put-away-books-but-they-cant-do-a-reference-interview/
Axelsson, M. (July 25, 2019). The little robot that lived at the library: How we built an emotive social robot to guide library customers to books. Medium. https://towardsdatascience.com/the-little-robot-that-lived-at-the-library-90431f34ae2c
Black, M. (August 16, 2018). High-tech robot couriers set efficiency in motion at the National Library of Australia. https://www.abc.net.au/news/2018-08-17/robot-couriers-set-efficiency-in-motion-at-national-library/10118356
Blakemore, E. (2016). SINGAPORE’S LIBRARY ROBOT. Library journal (1976). 2016;141(15):13-13.
Ehrenberg, I, Floerkemeier C, Sarma S. (2007). Inventory management with an RFID-equipped mobile robot. In: 2007 IEEE International Conference on Automation Science and Engineering. IEEE; 2007:1020-1026. doi:10.1109/COASE.2007.4341838
Fan, H., & Shao, B. (2018). Reflection and innovative practice of book inventory with intelligent robot: A case study of Nanjing University Library. Library, 2018(9), 96-100. doi:10.3969/j.issn.1002-1558.2018.09.017
Harada, T. (2019). Robotics and artificial intelligence technology in Japanese libraries. IFLA WLIC, 2019. http://library.ifla.org/id/eprint/2695/1/s08-2019-harada-en.pdf
Helsingin Kulttuuri ja vapaa-aika. (2019 February 6). Helsingin kaupunginkirjaston logistiikka. https://youtu.be/kXUkNyqXjYw
Kim, B. K., Ohara, K., Kitagaki, K., Ohba, K., & Sugawara, T. (2008). Design of ubiquitous space for the robotic library system and its application. In: IFAC Proceedings Volumes (IFAC-PapersOnline). Vol 17.; 2008. doi:10.3182/20080706-5-KR-1001.3212. https://na03.primo.exlibrisgroup.com/permalink/01USC_INST/273cgt/cdi_scopus_primary_355322422
Kim, B. K., Sugawara, T., Ohara, K., Kitagaki, K., & Ohba, K. (2008). Design and control of the librarian robot system in the ubiquitous robot technology space. RO-MAN 2008 - The 17th IEEE International Symposium on Robot and Human Interactive Communication, 616–621. https://doi.org/10.1109/ROMAN.2008.4600735
Li, G. S., Pang, Y. X., Luo, W., & Zhang, L. (2012). Design of RFID Based Robot System for Automatic Search of Books in Libraries. In Advanced Materials Research (Vols. 433–440, pp. 6856–6860). Trans Tech Publications, Ltd. https://doi.org/10.4028/www.scientific.net/amr.433-440.6856
Li, R., Huang, Z., Kurniawan E, & Ho, C. K. (2015). AuRoSS: An Autonomous robotic shelf scanning system. In: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Vol 2015-. IEEE; 2015:6100-6105. doi:10.1109/IROS.2015.7354246
Liau, Y. C. (2019). Transforming library operation with robotics. 2019 IFLA WLIC. http://library.ifla.org/id/eprint/2701/1/s08-2019-liau-en.pdf
Nolan, S. (January 27, 2022). Immersion and robots: The next chapter for Singapore’s libraries. GovInsider. https://govinsider.asia/smart-gov/immersion-and-robots-the-next-chapter-for-singapores-libraries/
Reitz, J. (2013). Online dictionary for library and information science. ABC-CLIO. http://products.abc-clio.com/ODLIS/odlis_about.
Scott, T. (October 14, 2019). Why Helsinki's Library robots aren't important. https://youtu.be/dPb9o3uDF_Q
Seow, J. (2019 August 13). Not enough service staff? Why not ‘hire’ a robot. The Strait Times. https://www.straitstimes.com/business/not-enough-service-staff-why-not-hire-a-robot
Shen, K., Shao, B., Chen, L., & Shan, G. (2016). The Design and implementation of book inventory robot based on ultra high frequency RFID. Library Research, 2016(7), 24-28. Doi:10.15941/j.cnki.issn1001-0424.2016.07.005
South China Morning Post. (2022 May 31). Singapore employs robots to fill labour gaps. https://youtu.be/Lu--njUBOFA
Tang L, Li L, Su H. Fixed-Point Target Control of Library Management Robot: A Linear Decomposition Approach. IOP conference series Materials Science and Engineering. 2018;466(1):12092-. doi:10.1088/1757-899X/466/1/012092
Thirumurugan, J, Kartheeswaran G, Vinoth M, Vishwanathan M. (2010). Line following robot for library inventory management system. In: INTERACT-2010. IEEE; 2010:1-3. doi:10.1109/INTERACT.2010.5706151
Xia, Z., Li, Q., Duan, W., & Fu, P. (2019) A Post-implementation review analysis for an autonomous RFID inventory project: A qualitative study. 2019 IFLA.
Yu, Fan, Z., Wan, H., He, Y., Du, J., Li, N., Yuan, Z., & Xiao, G. (2019). Positioning, navigation, and book accessing/returning in an autonomous library robot using integrated binocular vision and QR code identification systems. Sensors (Basel, Switzerland), 19(4), 783–. https://doi.org/10.3390/s19040783
Zhang, Ling, B., Luo, W., Liu, X., & Pang, Y. (2012). Obstacle avoidance scheme for RFID based mobile robot in libraries. Advanced Materials Research, 433-440, 6802–6806. https://doi.org/10.4028/www.scientific.net/AMR.433-440.6802