Next Article in Journal
Sorting Objects from a Conveyor Belt Using POMDPs with Multiple-Object Observations and Information-Gain Rewards
Previous Article in Journal
An Overview of Signal Processing Techniques for Remote Health Monitoring Using Impulse Radio UWB Transceiver
 
 
Article

Personal Guides: Heterogeneous Robots Sharing Personal Tours in Multi-Floor Environments

1
Faculty of Informatics, University of Basque Country (UPV/EHU), 20018 Donostia, Spain
2
University Institute of Intelligent Systems and Numeric Applications in Engineering, Campus de Tafira, Las Palmas de Gran Canaria, University of Las Palmas de Gran Canaria, 35017 Las Palmas, Spain
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(9), 2480; https://doi.org/10.3390/s20092480
Received: 20 February 2020 / Revised: 31 March 2020 / Accepted: 23 April 2020 / Published: 27 April 2020
(This article belongs to the Section Physical Sensors)
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. View Full-Text
Keywords: social service robots; distributed robotic system; face re-identification; neural networks social service robots; distributed robotic system; face re-identification; neural networks
Show Figures

Figure 1

MDPI and ACS Style

Rodriguez, I.; Zabala, U.; Marín-Reyes, P.A.; Jauregi, E.; Lorenzo-Navarro, J.; Lazkano, E.; Castrillón-Santana, M. Personal Guides: Heterogeneous Robots Sharing Personal Tours in Multi-Floor Environments. Sensors 2020, 20, 2480. https://doi.org/10.3390/s20092480

AMA Style

Rodriguez I, Zabala U, Marín-Reyes PA, Jauregi E, Lorenzo-Navarro J, Lazkano E, Castrillón-Santana M. Personal Guides: Heterogeneous Robots Sharing Personal Tours in Multi-Floor Environments. Sensors. 2020; 20(9):2480. https://doi.org/10.3390/s20092480

Chicago/Turabian Style

Rodriguez, Igor, Unai Zabala, Pedro A. Marín-Reyes, Ekaitz Jauregi, Javier Lorenzo-Navarro, Elena Lazkano, and Modesto Castrillón-Santana. 2020. "Personal Guides: Heterogeneous Robots Sharing Personal Tours in Multi-Floor Environments" Sensors 20, no. 9: 2480. https://doi.org/10.3390/s20092480

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop