Monitoring of populated indoor environments is crucial for the surveillance of public spaces like airports or embassies, where the behavior of people may be relevant in order to determine abnormal situations. In this paper, a surveillance system based on an integration of interactive and non-interactive heterogeneous sensors is described. As a difference with respect to traditional, pure vision-based systems, the proposed approach relies on Radio Frequency Identification (RFID) tags carried by people, multiple mobile robots (each one equipped with a laser range finder and an RFID reader), and fixed RGBD cameras. The main task of the system is to assess the presence and the position of people in the environment. This is obtained by suitably integrating data coming from heterogeneous sensors, including those mounted on board of mobile robots that are in charge of patrolling the environment. The robots also adapt their behavior according to the current situation, on the basis of a Prey-Predator scheme. Experimental results carried out both on real and on simulated data show the effectiveness of the approach. © 2014 Published by Elsevier B.V.
Distributed Sensor Network for Multi-robot Surveillance
BLOISI, Domenico Daniele;
2014-01-01
Abstract
Monitoring of populated indoor environments is crucial for the surveillance of public spaces like airports or embassies, where the behavior of people may be relevant in order to determine abnormal situations. In this paper, a surveillance system based on an integration of interactive and non-interactive heterogeneous sensors is described. As a difference with respect to traditional, pure vision-based systems, the proposed approach relies on Radio Frequency Identification (RFID) tags carried by people, multiple mobile robots (each one equipped with a laser range finder and an RFID reader), and fixed RGBD cameras. The main task of the system is to assess the presence and the position of people in the environment. This is obtained by suitably integrating data coming from heterogeneous sensors, including those mounted on board of mobile robots that are in charge of patrolling the environment. The robots also adapt their behavior according to the current situation, on the basis of a Prey-Predator scheme. Experimental results carried out both on real and on simulated data show the effectiveness of the approach. © 2014 Published by Elsevier B.V.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
