Search

Autonomous robotic teams have been proposed for a variety of lost-person searches in wilderness and urban settings. In the latter scenarios, for missing persons, the application of such teams, however, is more challenging than it would be in the wilderness. This paper, specifically, examines the application of an autonomous team of unmanned aerial vehicles (UAVs) to perform a sparse, mobile-target search in an urban setting. A novel multi-UAV search-trajectory planning method, which relies on the prediction of the missing-person's motion, given a known map of the search environment, is the primary focus. The proposed method incorporates periodic updates of the estimates of where the lost/missing person may be, allowing for intelligent re-coverage of previously searched areas. Additional significant contributions of this work include a behavior-based motion-prediction method for missing persons and a novel non-parametric estimator for iso-probability-based (missing-person-location) curves. Simulated experiments are presented to illustrate the effectiveness of the proposed search-planning method, demonstrating higher rates of missing-person detection and in shorter times compared to other methods. [ABSTRACT FROM AUTHOR]

Abstract Background Rescue operations are in Norway defined as situations where patients are difficult to access or that more resources are needed than the health services alone possess and can put in operation (Bull A, Redningshåndboken er endelig her! [Internet]. Hovedredningssentralen. 2018 [cited 2023 May 15]. Available from: https://www.hovedredningssentralen.no/redningshandboken-er-endelig-her/ ). Rescue operations after large incidents may include civil protection, military forces, non-governmental organizations and other resources, but the initial rescue effort must be performed by the emergency services as time often is of essence. The central area of an accident where special training and personal protection equipment is necessary or mandatory is called the Hot Zone. This study examines Urban Search And Rescue (USAR) firefighters and police officers reported experiences from ambulance personnel’s contribution in the Hot Zone. Methods We conducted five focus group interviews with USAR-trained firefighters and police officers. The interviewees were those on duty on the agreed dates. The interviews were taped, transcribed, and analysed using thematic analysis as described by Braun & Clarke. Results Three themes were identified; Feeling safe during missions, Building USAR capacity, and Trust-building within USAR-teams. The firefighters and police officers reported their and the patients’ safety are best managed by EMS-personnel, whose presence strongly contributes to their own feeling of safety in a dangerous area. When EMS handles victims and injured emergency workers, firefighters and police officers can focus on their own primary tasks. Indeed, interviewees reported that building a USAR capacity depends on having USAR-trained EMS-personnel in the Hot Zone. The interviewees have clear and consistent opinions on how to establish an interagency USAR capacity effectively. Trust is paramount to the interviewees, and they express a high degree of trust within USAR Oslo. Conclusions Firefighters and police officers regard USAR-trained EMS-personnel as a natural and integrated part in urban search and rescue teams. EMS-personnel in the dangerous area deliver safety and medical professional assistance to both rescue workers and patients. Informants in this study had clear opinions on how to establish and maintain such a service.

Background: Rescue operations are in Norway defined as situations where patients are difficult to access or that more resources are needed than the health services alone possess and can put in operation (Bull A, Redningshåndboken er endelig her! [Internet]. Hovedredningssentralen. 2018 [cited 2023 May 15]. Available from: https://www.hovedredningssentralen.no/redningshandboken-er-endelig-her/). Rescue operations after large incidents may include civil protection, military forces, non-governmental organizations and other resources, but the initial rescue effort must be performed by the emergency services as time often is of essence. The central area of an accident where special training and personal protection equipment is necessary or mandatory is called the Hot Zone. This study examines Urban Search And Rescue (USAR) firefighters and police officers reported experiences from ambulance personnel's contribution in the Hot Zone. Methods: We conducted five focus group interviews with USAR-trained firefighters and police officers. The interviewees were those on duty on the agreed dates. The interviews were taped, transcribed, and analysed using thematic analysis as described by Braun & Clarke. Results: Three themes were identified; Feeling safe during missions, Building USAR capacity, and Trust-building within USAR-teams. The firefighters and police officers reported their and the patients' safety are best managed by EMS-personnel, whose presence strongly contributes to their own feeling of safety in a dangerous area. When EMS handles victims and injured emergency workers, firefighters and police officers can focus on their own primary tasks. Indeed, interviewees reported that building a USAR capacity depends on having USAR-trained EMS-personnel in the Hot Zone. The interviewees have clear and consistent opinions on how to establish an interagency USAR capacity effectively. Trust is paramount to the interviewees, and they express a high degree of trust within USAR Oslo. Conclusions: Firefighters and police officers regard USAR-trained EMS-personnel as a natural and integrated part in urban search and rescue teams. EMS-personnel in the dangerous area deliver safety and medical professional assistance to both rescue workers and patients. Informants in this study had clear opinions on how to establish and maintain such a service. [ABSTRACT FROM AUTHOR]

Autonomous robotic teams have been proposed for a variety of lost-person searches in wilderness and urban settings. In the latter scenarios, for missing persons, the application of such teams, however, is more challenging than it would be in the wilderness. This paper, specifically, examines the application of an autonomous team of unmanned aerial vehicles (UAVs) to perform a sparse, mobile-target search in an urban setting. A novel multi-UAV search-trajectory planning method, which relies on the prediction of the missing-person’s motion, given a known map of the search environment, is the primary focus. The proposed method incorporates periodic updates of the estimates of where the lost/missing person may be, allowing for intelligent re-coverage of previously searched areas. Additional significant contributions of this work include a behavior-based motion-prediction method for missing persons and a novel non-parametric estimator for iso-probability-based (missing-person-location) curves. Simulated experiments are presented to illustrate the effectiveness of the proposed search-planning method, demonstrating higher rates of missing-person detection and in shorter times compared to other methods.

First responders often lack information and visual clues regarding interior spaces in disaster rubble, preventing efficient, effective, and safe search and rescue for victims trapped in collapsed structures. Rapidly detecting and acquiring information about the voids in collapsed structures that could contain surviving victims is critical for urban search and rescue. However, reconstructing the buried voids in three dimensions (3D) and communicating the relevant information such as buried depth and void size to first responders remain significant challenges. In response, this study proposes a see-through technique by integrating ground-penetrating radar (GPR) with interactive augmented reality (AR). The contribution of this study is twofold. First, a new method is developed to process collected GPR data to reconstruct potential voids in disaster rubble in 3D and extract the buried depth and void size from the GPR data. The coordinates of void boundaries are extracted from multiple GPR scans to generate sparse point clouds. An improved alpha-shape method is exploited to reconstruct the 3D space beneath disaster rubble from the point clouds. Second, an interactive augmented reality interface is developed to enable first responders to visualize the voids in collapsed structures in 3D together with relevant information to assist urban search and rescue. The results from simulations and pilot experiments demonstrate the feasibility and potential of the proposed methods. [ABSTRACT FROM AUTHOR]

Accurate flood forecasting and efficient emergency response operations are vital, especially in the case of urban flash floods. The dense distribution of power lines in urban areas significantly impacts search and rescue operations during extreme flood events. However, no existing emergency response frameworks have incorporated the impacts of overhead power lines on lifeboat rescue operations. This study aims to determine the necessity and feasibility of incorporating overhead power line information into an emergency response framework using Manville, New Jersey during Hurricane Ida as a test bed. We propose an integrated framework, which includes a building-scale flood model, urban point cloud data, a human vulnerability model, and network analysis, to simulate rescue operation feasibility during Hurricane Ida. Results reveal that during the most severe point of the flood event, 46% of impacted buildings became nonrescuable due to complete isolation from the road network, and a significant 67.7% of the municipality's areas that became dangerous for pedestrians also became inaccessible to rescue boats due to overhead power line obstruction. Additionally, we identify a continuous 10-hour period during which an average of 43.4% of the 991 impacted buildings faced complete isolation. For these structures, early evacuation emerges as the sole means to prevent isolation. This research highlights the pressing need to consider overhead power lines in emergency response planning to ensure more effective and targeted flood resilience measures for urban areas facing increasingly frequent extreme precipitation events. [ABSTRACT FROM AUTHOR]

Aim: The aim of the article is to present the obstacles which constitute the so-called “barrier effect” while exploring the area of urban search and rescue operations on the first day after an earthquake. It also includes preliminary results of research conducted under the implementation project “EASeR”, aimed at developing procedures and outlines for fire-fighters from Italy, helping them minimise the “barrier effect”. They may also prove useful for other countries. Introduction: In the introduction, the authors outline the circumstances of the establishing of the INSARAG International Search and Rescue Advisory Group at the UN and its European counterpart with a broader spectrum of responsibilities (the EU Civil Protection Mechanism), along with the legal basis for the organisation, as well as recall the international guidelines defining standards and methodologies for the Search and Rescue Groups (GPR). The mechanism is responsible not only for USAR but also for almost 20 types of different civil protection assets. The authors also recall the whole cycle of the GPR mission, along with examples of natural disasters and circumstances that have led to the launching of the EASeR project. Finally, the assumptions of the project and its partners are presented. Methodology: The initial research material related to the subject matter in question included international UN and EU normative documents establishing the organisational and operational standards for the conduction of actions, and the operation of search and rescue groups (USAR), as well as exemplary EU implementation projects. The identification of the initial “obstacles limiting the conduction of initial assessments (ASR 1–3) at the scene of action, defined by Italian fire-fighters from Pisa as a “barrier effect”, was the starting point for a wider analysis of the facts, and the development of a questionnaire and international surveys, using a diagnostic survey in over a dozen countries around the world. Conclusions: The quantitative data and opinions on the main obstacles encountered during the disaster reconnaissance allowed the project experts to confirm or reject the pre-assumptions for the projected content of the final project documents, and during further meetings, it was possible to develop the final versions of operational procedures indexes for emergency services in Italy, as well as the index of guidelines for international USAR in the field of reconnaissance in the initial phase (the so-called ASR 1–3). After the consultation of the final project documents (procedures and guidelines), as a result of the collected opinions and further expert work, the second phase of the project was to take place.

This paper presents the map evaluation methodology developed for the Virtual Robots Rescue competition held as part of RoboCup. The procedure aims to evaluate the quality of maps produced by multi-robot systems with respect to a number of factors, including usability, exploration, annotation and other aspects relevant to robots and first responders. In addition to the design choices, we illustrate practical examples of maps and scores coming from the latest RoboCup contest, outlining strengths and weaknesses of our modus operandi. We also show how a benchmarking methodology developed for a simulation testbed effortlessly and faithfully transfers to maps built by a real robot. A number of conclusions may be derived from the experience reported in this paper and a thorough discussion is offered.

Teams of semi-autonomous robots can provide valuable assistance in Urban Search and Rescue (USAR) by efficiently exploring cluttered environments and searching for potential victims. Their advantage over solely teleoperated robots is that they can address the task handling and situation awareness limitations of human operators by providing some level of autonomy to the multi-robot team. Our research focuses on developing learning-based semi-autonomous controllers for rescue robot teams. In this paper, we specifically investigate the influence of the operator-to-robot ratio on the performance of our proposed MAXQ hierarchical reinforcement learning based semi-autonomous controller for USAR missions. In particular, we propose a unique learning-based system architecture that allows operator control of larger numbers of rescue robots in a team as well as effective sharing of information between these robots. A rigorous comparative study of our learning-based semi-autonomous controller versus a fully teleoperation-based approach was conducted in a 3D simulation environment. The results, as expected, show that, for both semi-autonomous and teleoperation modes, the total scene exploration time increases as the number of robots utilized increases. However, when using the proposed learning-based semi-autonomous controller, the rate of exploration-time increase and operator-interaction effort are significantly lower, while task performance is significantly higher. Furthermore, an additional case study showed that our learning-based approach can provide more scene coverage during robot exploration when compared to a non-learning based method. [ABSTRACT FROM AUTHOR]

People's safety is threatened by the repetition of critical events. Many people lose their lives due to unprofessional rescue operation as well as time pressure of the rescue operation. A key problem in urban search and rescue teams, considering the severe turbulence and complexity of the environments which are hit by a crisis, is the coordination between the team members. In order to solve this problem, an effective plan would be the provision of measures where human works with intelligent assistant agents to assign the tasks in any way. Dynamic tasks are identified by the human agent of the rescue team in the crisis environment and are characterized by spatial-temporal characteristics assigned to the appropriate rescue team by the intelligent assistant agents who apply intelligent decision-making techniques. The objective of this study is to propose a new approach for allocating spatial-temporal tasks in multi-agent systems through cellular learning automata as the decision-making technique. Results obtained here indicate that this proposed model can significantly improve the rescue time and space. Rescue teams could cover all critical areas by going through the minimum distance to make maximum use of time. [ABSTRACT FROM AUTHOR]

Copyright of Safety & Fire Technology (2657-8808) is the property of Centrum Naukowo-Badawcze Ochrony Przeciwpozarowej and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Highlights • Cases of three different scales are simulated and compared by FEM and AEM. • Blast and earthquake loading is considered. • Comparison of simulated debris heaps with real results. • Discusses strengths and weaknesses of methods in context of collapse. Abstract Numerical prediction of progressive collapse of buildings due to extreme loading is still a challenging task. However, increased computational power makes it nowadays possible to analyze not only small-scale connections and mid-size building elements, but also full buildings with considerable height and complexity. The present paper compares the results of Finite Element Method (FEM) and Applied Element Method (AEM) simulations to experimental results when performing blast or earthquake analysis on those three scales. The aim is to highlight which level of physical detail and complexity is required to predict progressive collapse numerically, and which level of accuracy can be expected. For the full scale level, the progressive collapse of the Pyne Gould Corporation Building in Christchurch, New Zealand, was simulated and compared to the final collapse shape. It is shown that the FEM is able to predict the structural response of small scale models well, but fails to achieve realistic collapsed shapes in case of the large structure, whereas the AEM shows convincing results in all cases. [ABSTRACT FROM AUTHOR]

A group of Urban Search and Rescue (USAR) Unmanned Ground Vehicles (UGVs) works in the city’s dangerous places that are caused by natural disasters or the decommissioning of nuclear facilities such as the nuclear power plant. Consider the multi sensor platform that the USAR UGV is equipped with, protecting the sensors from the danger that dwells in the working environments is highly related to the success of the USAR mission. The radioactive working environments due to the diffusion of the radioactive materials during the decommissioning of the nuclear facilities are proposed in this work. Radiation shielding boards are used to protect the sensors by installing them on the UGV. Generally, the more shielding boards installed on the UGV, the lower the probability of the sensor malfunctioning. With a large number of UGVs that are used in missions, a large number of shielding boards are needed. Considering the cost of the boards, a conflict between the finite budget and the best protection for the UGV swarm occurs. Due to differences in environments and working times, an asymmetric allocation of shielding boards might protect the UGV swarm better than that by allocating evenly. To minimize the absorption radiation doses, two methods including competitive equilibrium analysis and integer linear programming are proposed. The performances that result from the allocation of the shielding boards by two methods with different budgets are studied.

Working canines are often deployed to contaminated environments with unknown chemical and biological content. Little data exists supporting the effectiveness of current canine decontamination protocols. The objective of this study was to prospectively compare the effectiveness of a standard decontamination protocol utilized in real-world working scenarios by Federal Emergency Management Agency (FEMA) urban search and rescue teams (Protocol A) vs. a modified protocol (Protocol B) developed from technician feedback. Protocol A (n = 7) utilized stiff bristle brushes, generic pet shampoo, and a double rinse system. Protocol B (n = 7) utilized a soft rubber grooming brush, Johnson & Johnson’s ® Head-to-Toe Body Wash, and a grated floor in addition to the existing rinse system to facilitate drainage of gray water. An oil-based pseudo-contaminant (Glo-Germ) was topically applied to four anatomical sites on each canine: the throat latch; between the shoulder blades; the inner aspect of the hind leg; and the hind paw. Reduction in contamination was assessed after each canine underwent decontamination and scored using a previously validated scale. Categorical data were analyzed using a Chi Square test and PROC FREQ of SAS (version 9.4). Overall, Protocol B was associated with greater reduction in contamination compared to Protocol A ( P = 0.01), with the throat latch and inner hind leg more likely to retain contaminant than the hind paw or between the shoulder blades ( P < 0.01). Canines decontaminated using Protocol A were more likely to have residual contamination of the throat latch or inner hind leg compared to the hind paw ( P < 0.05). In contrast, those decontaminated using Protocol B were likely to have residual contamination of only the throat latch compared to other sites ( P < 0.05). Simple modifications in current FEMA protocols increased the overall effectiveness of working canine decontamination. [ABSTRACT FROM AUTHOR]

With increasing capabilities and reliability of autonomous mobile robots, inspection of remote industrial plants in challenging environments becomes feasible. With the ARGOS challenge, oil and gas company TOTAL S.A. initiated an international competition aimed at the development of the first autonomous mobile robot which can safely operate in complete or supervised autonomy over the entire onshore or offshore production site, potentially in hazardous explosive atmospheres and harsh conditions. In this work, the approach of joint Austrian-German Team ARGONAUTS towards solving this challenge is introduced, focussing on autonomous capabilities. These build on functional components developed during prior participation in the RoboCup Rescue Robot League. [ABSTRACT FROM AUTHOR]