Search results

The duration of an urban search and rescue (USAR) operation directly depends on the number of rescue teams involved. The purpose of this paper is to simplify the earthquake environment and determine the initial number of rescuers in earthquake emergencies in USAR operation.

In the proposed methodology, four primary steps were considered: evaluation of buildings damage and the number of injured people by exerting geospatial information system (GIS) analyses; determining service time by means of task allocation; designing the simulation model (queuing theory); and calculation of survival rate and comparison with the time of rescue operations.

The calculation of buildings damage for an earthquake with 6.6 Richter in Tehran’s District One indicated that 18% of buildings are subjected to the high damage risk. The number of injured people calculated was 28,856. According to the calculated survival rate, rescue operations in the region must be completed within 22.33 h to save 75% of the casualties. Finally, the design of the queue model indicated that at least 2,300 rescue teams were required to provide the calculated survival rate.

The originality of this paper is an innovative approach for determining an appropriate number of rescue teams by considering the queuing theory. The results showed that the integration of GIS and the simulation of queuing theory could be a helpful tool in natural disaster management, especially in terms of rapid vulnerability assessment in urban districts, the adequacy and appropriateness of the emergency services.

This study aims to investigate locomotion mechanisms of different urban search and rescue (USAR) robots currently being researched or commercially available on the market.

USAR robots are categorized by the type of their mobility. Detailed illustration and analysis have been given for each USAR robot in the paper.

The paper finds that none of current USAR robots can practically and autonomously carry out rescue work in a complex and unstructured environment. Hence, responding to the practical requirements of highly challenging USAR tasks, a team of USAR robots based on different locomotion mechanisms may be a good solution to undertake rescue activities.

The paper provides guidance in the design of future USAR robots.

The paper investigates locomotion mechanisms of different USAR robots in detail.

The paper aims to describe the design and manufacturing process of a tele‐operative urban search and rescue tracked robot and discuss the advantages of a proposed novel track arrangement and other additional mechanisms, which help the robot to gain high manoeuverability on rough terrains.

Using a simplified static model, required torques are calculated and appropriate mechanisms and geometric dimensions are chosen. Next, stress distribution is analyzed in the parts, deploying both classic and numerical methods and to complete the procedure parts are fabricated and assembled together. The architecture of control system and the user interface is introduced. Finally, the robot is tested on a standard test arena and the results are compared with another similar search robot.

A tele‐operated rescue robot with considerable capabilities is designed and manufactured. The novel track arrangement and new rear arm's mechanism are tested and compared with a robot in the same class and higher performance is achieved on the evaluation.

Although the implemented locomotion mechanism is the common tracked type, adding the center tracks and arrangement of arms are original ideas which help the robot to gain high manoeuverability. The proposed rear arm's linkage mechanism generates a limited rotational path and has an acceptable strength for a robot working in rescue missions.

The purpose of this paper is to provide background information on a rarely studied response capability of communities across the USA, local, mostly volunteer search and rescue (SAR) teams.

Information on local teams was collected from January 2005 until February 2006 through internet searches, online SAR organization lists, and by e‐mailing a survey to local teams. A smaller, previously used database was used to verify the final list of teams and 57 new teams were added in this manner. An SPSS database was created using all the fields collated from the survey.

It was found that there are 1,150 teams in the USA, which range from one team per State to 79 teams in California. Local SAR teams had a quicker response time than federal teams, while maintaining better equipment and training than emergent volunteers. These teams, unlike the federally funded US&R teams, rely mostly on donations and community fundraisers to continue operating.

Missing data were the most consistent problem faced. Web sites, web links and e‐mail addresses often had expired or did not contain the right information, some teams existed without having a web site (and therefore were not included in the database); also response to the e‐mail survey was low.

Integrating interested local SAR teams into official multi‐organizational disaster and emergency responses could provide valuable additional resources to emergency and incident managers, would allow for better funding for local SAR, and could facilitate recognition to these often overlooked teams.

This paper provides preliminary information on local SAR teams in the USA.

This paper aims to provide an insight into the future for disaster relief (DR) and search and rescue (SAR) robots by considering research activities which seek to address real-world applications and by identifying key user requirements and development priorities.

Following a short introduction, this first provides a brief overview of the use of robots in DR and SAR and gives examples of organisations promoting their use. This is followed by details of development programmes aimed at meeting users’ requirements. Specific needs are identified and considered in detail and were derived from both the literature and through discussions with users. This paper concludes with a tabulated summary of key development priorities.

This study shows that several collaborative research programmes aim to address real DR and SAR applications, with robots being tested in simulated disaster scenarios. A number of key user requirements and development priorities are identified for aerial, ground and marine robots.

By identifying a number of specific requirements, this paper will assist in focussing research and development activities towards real users’ needs.

This paper aims to discuss search and rescue (SAR) and disaster relief robot developments, trials and applications and to answer the question posed in the title.

Following a short introduction, this first describes Integrated Components for Assisted Rescue and Unmanned Search operations, a recent, collaborative, European research project, and euRathlon, a major robotics competition. It then highlights the role of the centre for robot-assisted search and rescue, and provides examples of the deployment of terrestrial, marine and airborne robots in real SAR and disaster relief situations. It concludes with a brief discussion.

This shows that SAR and disaster relief robots are the topic of an extensive development effort, and many have performed well in simulated disaster scenarios. Terrestrial, marine and airborne robots have been used in many real disaster relief situations since 2001, and the use of unmanned aerial vehicles has proliferated due to recent technological developments. Robots now play an important role in supporting SAR teams, and this will certainly increase as the technologies are developed further.

In an era characterized by extreme weather events and continuing military conflicts, robots play an increasingly important role in supporting human disaster response teams. This article provides details of developments, trials and real-world deployments of such robots.

The purpose of this paper is to analyse if the classification system introduced by International Search and Rescue Advisory Group (INSARAG), or INSARAG External Classification (IEC), contributes to effective international search and rescue (SAR) activities in the 2015 Nepal earthquake.

In addition to the data collected by Office for the Coordination of Humanitarian Affairs and the United Nations Disaster Assessment and Coordination (UNDAC) team, the data were collected by one of the authors who was deployed to Nepal as part of the UNDAC just after the earthquake. Interviews with the deployed international SAR teams and the INSARAG Secretariat were also conducted.

Although more than 50 teams have been classified in IEC, some IEC-classified teams could not utilise their full capabilities in the Nepal response. For example, they did not necessarily arrive in Nepal earlier than the non-classified teams, but it was because the affected country did not prioritise the IEC-classified teams. To save more lives by international teams, INSARAG will need to raise the awareness of IEC in receiving countries, consider the good regional balance of IEC-classified teams and facilitate strengthening local SAR capabilities through the IEC process.

The added value of this study is, by combining the evidence-based field reality and academic analysis, to find out the existing problems in the field and to provide tangible recommendations for further improvement of the IEC system, which will then lead to saving more lives.

After a building collapse, people buried alive have to be localized and rescued. This requires the damage site's inspection and surveillance. These tasks are dangerous and challenging due to the area's hard‐to‐reach and hazardous environment. The damage site cannot be actively entered but must be inspected from a safe distance. In this context, mobile robots gain in importance as they can be operated semi‐autonomously or remote‐controlled without exposing the first responders to the risk. The purpose of this paper is to introduce a novel robot.

The novel robot introduced in this paper has a snake‐like build‐up, uses tracks and active flippers for locomotion and negotiates completely structured as well as extremely unstructured and rough terrain. The system's slender, segmented and modular structure is actively articulated by the use of overall 30 degrees‐of‐freedom, which allow the robot's flexible adaptation to a given terrain. System‐terrain‐interaction is detected by the use of an innovative, RFID‐based sensory integrated in the system's tracks.

The paper presents the mobile robot's basic features, as well as first experimental results for semi‐autonomy and tele‐operation.

The introduced robot stands out due to its high locomotion and mobility capabilities.

The purpose of this paper is to demonstrate a real time 3D localization and mapping approach for the USAR (Urban Search and Rescue) robotic application, focusing on the performance and the accuracy of the General‐purpose computing on graphics processing units (GPGPU)‐based iterative closest point (ICP) 3D data registration implemented using modern GPGPU with FERMI architecture.

The authors put all the ICP computation into GPU, and performed the experiments with registration up to 106 data points. The main goal of the research was to provide a method for real‐time data registration performed by a mobile robot equipped with commercially available laser measurement system 3D. The main contribution of the paper is a new GPGPU based ICP implementation with regular grid decomposition. It guarantees high accuracy as equivalent CPU based ICP implementation with better performance.

The authors have shown an empirical analysis of the tuning of GPUICP parameters for obtaining much better performance (acceptable level of the variance of the computing time) with minimal lost of accuracy. Loop closing method is added and demonstrates satisfactory results of 3D localization and mapping in urban environments. This work can help in building the USAR mobile robotic applications that process 3D cloud of points in real time.

This work can help in developing real time mapping for USAR robotic applications.

The paper proposes a new method for nearest neighbor search that guarantees better performance with minimal loss of accuracy. The variance of computational time is much less than SoA.