Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/73849
Title: Personal guides: heterogeneous robots sharing personal tours in multi-floor environments
Authors: Rodriguez, Igor
Zabala, Unai
Marín Reyes, Pedro Antonio 
Jauregi, Ekaitz
Lorenzo Navarro, José Javier 
Lazkano, Elena
Castrillón Santana, Modesto Fernando 
UNESCO Clasification: 120304 Inteligencia artificial
Keywords: Distributed robotic system
Face re-identification
Neural networks
Social service robots
Issue Date: 2020
Journal: Sensors 
Abstract: GidaBot is an application designed to setup and run a heterogeneous team of robots to act as tour guides in multi-floor buildings. Although the tours can go through several floors, the robots can only service a single floor, and thus, a guiding task may require collaboration among several robots. The designed system makes use of a robust inter-robot communication strategy to share goals and paths during the guiding tasks. Such tours work as personal services carried out by one or more robots. In this paper, a face re-identification/verification module based on state-of-the-art techniques is developed, evaluated offline, and integrated into GidaBot’s real daily activities, to avoid new visitors interfering with those attended. It is a complex problem because, as users are casual visitors, no long-term information is stored, and consequently, faces are unknown in the training step. Initially, re-identification and verification are evaluated offline considering different face detectors and computing distances in a face embedding representation. To fulfil the goal online, several face detectors are fused in parallel to avoid face alignment bias produced by face detectors under certain circumstances, and the decision is made based on a minimum distance criterion. This fused approach outperforms any individual method and highly improves the real system’s reliability, as the tests carried out using real robots at the Faculty of Informatics in San Sebastian show.
URI: http://hdl.handle.net/10553/73849
ISSN: 1424-8220
DOI: 10.3390/s20092480
Source: Sensors [ISSN 1424-8220], v. 20 (9), 2480 (2020)
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