Operational Validation of Search and Rescue Robots

Cubber, Geert De; Doroftei, Daniela; Balta, Haris; Matos, Aníbal; Silva, Eduardo; Serrano, Daniel; Govindaraj, Shashank; Roda, Rui; Lobo, Victor; Marques, Mario Monteiro; Wagemans, Rene

doi:10.5772/intechopen.69497

Cited by 9 publications

(11 citation statements)

References 8 publications

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“…An example of a mixed qualitative-qualitative evaluation methodology in the field of robotics is the framework proposed in [20], where the performance was assessed of a series of search and rescue robots that work in close collaboration with human search and rescue workers. In this study, the human operators were non-experts and were quite reluctant to accept these new tools in the beginning but were only convinced of the use of the system following the outcome of the mixed qualitative-quantitative evaluation [21].…”

Section: Previous Work and A Discussion On Quantitative And Qualitatimentioning

confidence: 94%

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Using a qualitative and quantitative validation methodology to evaluate a drone detection system

Doroftei

Cubber

2019

ACTA IMEKO

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Now that the use of drones is becoming more common, the need to regulate the access to airspace for these systems is becoming more pressing. A necessary tool in order to do this is a means of detecting drones. Numerous parties have started the development of such drone detection systems. A big problem with these systems is that the evaluation of the performance of drone detection systems is a difficult operation that requires the careful consideration of all technical and non-technical aspects of the system under test. Indeed, weather conditions and small variations in the appearance of the targets can have a huge difference on the performance of the systems. In order to provide a fair evaluation, it is therefore paramount that a validation procedure that finds a compromise between the requirements of end users (who want tests to be performed in operational conditions) and platform developers (who want statistically relevant tests) is followed. Therefore, we propose in this article a qualitative and quantitative validation methodology for drone detection systems. The proposed validation methodology seeks to find this compromise between operationally relevant benchmarking (by providing qualitative benchmarking under varying environmental conditions) and statistically relevant evaluation (by providing quantitative score sheets under strictly described conditions).

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Section: Previous Work and A Discussion On Quantitative And Qualitatimentioning

confidence: 94%

“…The proposed methodology is a derivative of the work performed in [21] but ported to the domain of maritime threat agent detection [22]. A first step in the development of the validation framework was the requirements analysis, for which we followed a step-wise approach:…”

Section: Methodology For Gathering User Requirementsmentioning

confidence: 99%

Using a qualitative and quantitative validation methodology to evaluate a drone detection system

Doroftei

Cubber

2019

ACTA IMEKO

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“…ICARUS (De Cubber et al, ) focused on developing integrated tools for SAR, utilizing teams of air, ground, and marine vehicles with ad hoc communication networks. This team included two UGVs with tracked locomotion, one large and one small, with complementary capabilities based on their size and sensing/actuation suites (De Cubber et al, ). TRADR (de Greeff, Hindriks, Neerincx, & Kruijff‐Korbayova, ) developed human–robot teams to permit persistent operation in disaster response scenarios and also included a tracked platform in the team.…”

Section: State Of the Artmentioning

confidence: 99%

The current state and future outlook of rescue robotics

Delmerico

Mintchev

Giusti

et al. 2019

Journal of Field Robotics

263

124

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Robotic technologies, whether they are remotely operated vehicles, autonomous agents, assistive devices, or novel control interfaces, offer many promising capabilities for deployment in real-world environments. Postdisaster scenarios are a particularly relevant target for applying such technologies, due to the challenging conditions faced by rescue workers and the possibility to increase their efficacy while decreasing the risks they face. However, field-deployable technologies for rescue work have requirements for robustness, speed, versatility, and ease of use that may not be matched by the state of the art in robotics research. This paper aims to survey How to cite this article: Delmerico J, Mintchev S, Giusti A, et al. The current state and future outlook of rescue robotics.

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“…A major endeavor involving institutions from ten European countries and funded by the European Community’s Seventh Framework Program (FP7/2007-2013), called Integrated Components for Assisted Rescue and Unmanned Search (ICARUS) (The ICARUS project budget was in the order of 17.5 million Euros [19]. ), is focused on large-scale maritime assistive robotic tools for SAR operations [199,200,201]. The ICARUS initiative designed and tested several USVs for SAR: among them, two small Unmanned life-raft robotized CAPsules (UCAPs) [202,203,204].…”

Section: Usv Applications For Preventive Maintenance and Disaster mentioning

confidence: 99%

“…The ICARUS project stands out as the leading initiative focusing on SAR in marine environments [205]. Notwithstanding, ICARUS’ resources encompass robust unmanned systems designed for air, land, and water SAR operations, and training exercises tested its operational validation, involving different scenarios such as shipwrecks, where a team of robots presented effective results while detecting and helping people on the water [201]. The primary goal of the project is to enable first-responders with a team of unmanned systems, along with management tools to enable faster and more effective SAR operations [21].…”

Section: Usv Applications For Preventive Maintenance and Disaster mentioning

confidence: 99%

A Survey on Unmanned Surface Vehicles for Disaster Robotics: Main Challenges and Directions

Jorge

Granada

Maidana

et al. 2019

Sensors

142

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Disaster robotics has become a research area in its own right, with several reported cases of successful robot deployment in actual disaster scenarios. Most of these disaster deployments use aerial, ground, or underwater robotic platforms. However, the research involving autonomous boats or Unmanned Surface Vehicles (USVs) for Disaster Management (DM) is currently spread across several publications, with varying degrees of depth, and focusing on more than one unmanned vehicle—usually under the umbrella of Unmanned Marine Vessels (UMV). Therefore, the current importance of USVs for the DM process in its different phases is not clear. This paper presents the first comprehensive survey about the applications and roles of USVs for DM, as far as we know. This work demonstrates that there are few current deployments in disaster scenarios, with most of the research in the area focusing on the technological aspects of USV hardware and software, such as Guidance Navigation and Control, and not focusing on their actual importance for DM. Finally, to guide future research, this paper also summarizes our own contributions, the lessons learned, guidelines, and research gaps.

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Operational Validation of Search and Rescue Robots

Cited by 9 publications

References 8 publications

Using a qualitative and quantitative validation methodology to evaluate a drone detection system

Using a qualitative and quantitative validation methodology to evaluate a drone detection system

The current state and future outlook of rescue robotics

A Survey on Unmanned Surface Vehicles for Disaster Robotics: Main Challenges and Directions

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