Human-Robot Teaming in Urban Search and Rescue

Author(s):  
Cade E. Bartlett ◽  
Nancy J. Cooke
Author(s):  
Ruben Martin Garcia ◽  
Daniel Hernandez de la Iglesia ◽  
Juan F. de Paz ◽  
Valderi R. Q. Leithardt ◽  
Gabriel Villarrubia

2012 ◽  
Vol 19 (3) ◽  
pp. 46-56 ◽  
Author(s):  
Teodor Tomic ◽  
Korbinian Schmid ◽  
Philipp Lutz ◽  
Andreas Domel ◽  
Michael Kassecker ◽  
...  

2008 ◽  
Vol 41 (2) ◽  
pp. 3098-3103 ◽  
Author(s):  
Gurvinder S. Virk ◽  
Yiannis Gatsoulis ◽  
Mudassir Parack ◽  
Afsha Kherada

2021 ◽  
Vol 19 (1) ◽  
pp. 33-38
Author(s):  
Ariel Braverman, BSc, RN, EMT-P

This paper’s purpose is to establish a methodological basis for using unmanned aerial vehicles (UAV) in urban search and rescue (USAR). Modern USAR operations involve the location, rescue (extrication), and initial medical stabilization of individuals trapped in confined spaces or places with complicated access, eg, high structures. As a part of the ongoing modernization process, this paper explores possible options for UAV utilization in USAR operations. Today, UAV are already taking part in support emergency operations all over the world, and possible forms of operation for UAV in USAR environment can be in two primary modes: on-site and logistic chain. The on-site mode includes various capabilities of multilayer UAV array, mostly based on enhanced visual capabilities to create situational awareness and to speed-up search and rescue (SAR) process including using nanodrones for entering into confined places, ventilation ducts, and underground sewer channels can give to rescue teams’ opportunities to have eyes within ruins even before initial clearing process. Cargo drones will be able to bring equipment directly to high floors or roadless areas in comparison to wheeled transportation. The advantages of cargo drones operation are the ability of autonomous flight based on GPS or homing beacon and ability to provide logistics supports without involving additional personnel and vehicles and with no dependence on road conditions.


Author(s):  
D. Duarte ◽  
F. Nex ◽  
N. Kerle ◽  
G. Vosselman

Urban search and rescue (USaR) teams require a fast and thorough building damage assessment, to focus their rescue efforts accordingly. Unmanned aerial vehicles (UAV) are able to capture relevant data in a short time frame and survey otherwise inaccessible areas after a disaster, and have thus been identified as useful when coupled with RGB cameras for façade damage detection. Existing literature focuses on the extraction of 3D and/or image features as cues for damage. However, little attention has been given to the efficiency of the proposed methods which hinders its use in an urban search and rescue context. The framework proposed in this paper aims at a more efficient façade damage detection using UAV multi-view imagery. This was achieved directing all damage classification computations only to the image regions containing the façades, hence discarding the irrelevant areas of the acquired images and consequently reducing the time needed for such task. To accomplish this, a three-step approach is proposed: i) building extraction from the sparse point cloud computed from the nadir images collected in an initial flight; ii) use of the latter as proxy for façade location in the oblique images captured in subsequent flights, and iii) selection of the façade image regions to be fed to a damage classification routine. The results show that the proposed framework successfully reduces the extracted façade image regions to be assessed for damage 6 fold, hence increasing the efficiency of subsequent damage detection routines. The framework was tested on a set of UAV multi-view images over a neighborhood of the city of L’Aquila, Italy, affected in 2009 by an earthquake.


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