Field Trial of a Queue-Managing Security Guard Robot

Author:

Edirisinghe Sachi1ORCID,Satake Satoru2ORCID,Liu Yuyi1ORCID,Kanda Takayuki1ORCID

Affiliation:

1. Kyoto University, Japan and ATR Deep Interaction Laboratories, Japan

2. ATR Deep Interaction Laboratories, Japan

Abstract

We developed a security guard robot that is specifically designed to manage queues of people and conducted a field trial at an actual public event to assess its effectiveness. However, the acceptance of robot instructions or admonishments poses challenges in real-world applications. Our primary objective was to achieve an effective and socially acceptable queue-management solution. To accomplish this, we took inspiration from human security guards whose role has already been well-received in society. Our robot, whose design embodied the image of a professional security guard, focused on three key aspects: duties, professional behavior, and appearance. To ensure its competence, we interviewed professional security guards to deepen our understanding of the responsibilities associated with queue management. Based on their insights, we incorporated features of ushering, admonishing, announcing, and question answering into the robot’s functionality. We also prioritized the modeling of professional ushering behavior. During a 10-day field trial at a children’s amusement event, we interviewed both the visitors who interacted with the robot and the event staff. The results revealed that visitors generally complied with its ushering and admonishments, indicating a positive reception. Both visitors and event staff expressed an overall favorable impression of the robot and its queue-management services. These findings suggest that our proposed security guard robot shows great promise as a solution for effective crowd handling in public spaces.

Publisher

Association for Computing Machinery (ACM)

Reference49 articles.

1. 2022. What Do Security Guards Wear? A detailed guide. https://prosecurityguardcalifornia.com/what-do-security-guards-wear/

2. Iina Aaltonen, Anne Arvola, Päivi Heikkilä, and Hanna Lammi. 2017. Hello Pepper, may I tickle you? Children’s and adults’ responses to an entertainment robot at a shopping mall. In Proceedings of the Companion of the 2017 ACM/IEEE International conference on human-robot interaction. 53–54.

3. Muneeb I Ahmad and Reem Refik. 2022. “No Chit Chat!” A Warning From a Physical Versus Virtual Robot Invigilator: Which Matters Most? Frontiers in Robotics and AI 9 (2022).

4. Stochastic Sampling Simulation for Pedestrian Trajectory Prediction

5. The Social Power of a Uniform1

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