964 resultados para Search and rescue missions


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Multiple UAVs are deployed to carry out a search and destroy mission in a bounded region. The UAVs have limited sensor range and can carry limited resources which reduce with use. The UAVs perform a search task to detect targets. When a target is detected which requires different type and quantities of resources to completely destroy, then a team of UAVs called as a coalition is formed to attack the target. The coalition members have to modify their route to attack the target, in the process, the search task is affected, as search and destroy tasks are coupled. The performance of the mission is a function of the search and the task allocation strategies. Therefore, for a given task allocation strategy, we need to devise search strategies that are efficient. In this paper, we propose three different search strategies namely; random search strategy, lanes based search strategy and grid based search strategy and analyze their performance through Monte-Carlo simulations. The results show that the grid based search strategy performs the best but with high information overhead.

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Both genetic factors and life experiences appear to be important in shaping dogs' responses in a test situation. One potentially highly relevant life experience may be the dog's training history, however few studies have investigated this aspect so far. This paper briefly reviews studies focusing on the effects of training on dogs' performance in cognitive tasks, and presents new, preliminary evidence on trained and untrained pet dogs' performance in an 'unsolvable task'. Thirty-nine adult dogs: 13 trained for search and rescue activities (S&R group), 13 for agility competition (Agility group) and 13 untrained pets (Pet group) were tested. Three 'solvable' trials in which dogs could obtain the food by manipulating a plastic container were followed by an 'unsolvable' trial in which obtaining the food became impossible. The dogs' behaviours towards the apparatus and the people present (owner and researcher) were analysed. Both in the first 'solvable' and in the 'unsolvable' trial the groups were comparable on actions towards the apparatus, however differences emerged in their human-directed gazing behaviour. In fact, results in the 'solvable' trial, showed fewer S&R dogs looking back at a person compared to agility dogs, and the latter alternating their gaze between person and apparatus more frequently than pet dogs. In the unsolvable trial no difference between groups emerged in the latency to look at the person however agility dogs looked longer at the owner than both pet and S&R dogs; whereas S&R dogs exhibited significantly more barking (always occurring concurrently to looking at the person or the apparatus) than both other groups. Furthermore, S&R dogs alternated their gaze between person and apparatus more than untrained pet dogs, with agility dogs falling in between these two groups. Thus overall, it seems that the dogs' human-directed communicative behaviours are significantly influenced by their individual training experiences. © 2009 Elsevier B.V. All rights reserved.

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This paper describes the development and testing of a robotic capsule for search and rescue operations at sea. This capsule is able to operate autonomously or remotely controlled, is transported and deployed by a larger USV into a determined disaster area and is used to carry a life raft and inflate it close to survivors in large-scale maritime disasters. The ultimate goal of this development is to endow search and rescue teams with tools that extend their operational capability in scenarios with adverse atmospheric or maritime conditions.

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A continued increase in computing power, sensor capability, software functionality, immersive interfaces and hardware modularity has given robot designers seemingly endless potential in the area of mobile robotics.  While some mobile robotic system designers are focusing on expensive, full-featured platforms, developers are realising the advantages of emerging technology in providing small, low-cost mobile reconnaissance vehicles as expendable teleoperated robotic systems.  The OzBotTM mobile reconnaissance platform presents one such system.  The design objectives of the OzBotTM platform focus on the development of inexpensive, lightweight carry-case sized robots for search and rescue operations, law enforcement scenarios and hazardous environment inspection.  The incorporation of Haptic augmentation provides the teleoperator with improved task immersion for an outdoor search and rescue scenario.  Achieved in cooperation with law enforcement agencies within Australia, this paper discusses the performance of the first four revisions of the OzBotTM platform.

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In this paper we discuss the use of accelerometers and Bluetooth to monitor canine pose in the context of common poses observed in urban search and rescue dogs. We discuss the use of the canine pose system in a disaster environment, and propose techniques for determining canine pose. In addition we discuss the challenges with this approach in such environments. The paper presents the experimental results obtained from the heavy urban search and rescue disaster simulation, where experiments were conducted using multiple canines, which show that angles can be derived from acceleration readings. Our experiments show that similar angles were measured for each of the poses, even when measured on multiple USAR canines of varying size. We also found measurable and consistent differences between each of the poses, making them clearly distinguishable from one another, again even when comparing with different USAR canines.

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Informe de las reuniones subregionales sobre coordinacion de los servicios de busqueda y salvamento maritimo, convocadas por la Organizacion Maritima Internacional y CEPAL: 1) Reunion del Caribe Sur-Central (Kingston, Jamaica, 6-8 octubre de 1982); 2) Reunion del Caribe Oeste (Ciudad de Mexico, 13-15 octubre de 1982); y 3) Reunion del Caribe Sur (Puerto Espana, 8-11 noviembre de 1982).

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Presenta los acuerdos propuestos en la reunion, acerca de los limites desde la costa hasta la frontera con los paises vecinos, en lo que se refiere a responsabilidad en los servicios de busqueda y salvamento maritimo en America Central.

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Mode of access: Internet.

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Oceans - San Diego, 2013

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Purpose – The purpose of this paper is to describe an innovative compliance control architecture for hybrid multi‐legged robots. The approach was verified on the hybrid legged‐wheeled robot ASGUARD, which was inspired by quadruped animals. The adaptive compliance controller allows the system to cope with a variety of stairs, very rough terrain, and is also able to move with high velocity on flat ground without changing the control parameters. Design/methodology/approach – The paper shows how this adaptivity results in a versatile controller for hybrid legged‐wheeled robots. For the locomotion control we use an adaptive model of motion pattern generators. The control approach takes into account the proprioceptive information of the torques, which are applied on the legs. The controller itself is embedded on a FPGA‐based, custom designed motor control board. An additional proprioceptive inclination feedback is used to make the same controller more robust in terms of stair‐climbing capabilities. Findings – The robot is well suited for disaster mitigation as well as for urban search and rescue missions, where it is often necessary to place sensors or cameras into dangerous or inaccessible areas to get a better situation awareness for the rescue personnel, before they enter a possibly dangerous area. A rugged, waterproof and dust‐proof corpus and the ability to swim are additional features of the robot. Originality/value – Contrary to existing approaches, a pre‐defined walking pattern for stair‐climbing was not used, but an adaptive approach based only on internal sensor information. In contrast to many other walking pattern based robots, the direct proprioceptive feedback was used in order to modify the internal control loop, thus adapting the compliance of each leg on‐line.

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In this paper we present a set of field tests for detection of human in the water with an unmanned surface vehicle using infrared and color cameras. These experiments aimed to contribute in the development of victim target tracking and obstacle avoidance for unmanned surface vehicles operating in marine search and rescue missions. This research is integrated in the work conducted in the European FP7 research project Icarus aiming to develop robotic tools for large scale rescue operations. The tests consisted in the use of the ROAZ unmanned surface vehicle equipped with a precision GPS system for localization and both visible spectrum and IR cameras to detect the target. In the experimental setup, the test human target was deployed in the water wearing a life vest and a diver suit (thus having lower temperature signature in the body except hands and head) and was equipped with a GPS logger. Multiple target approaches were performed in order to test the system with different sun incidence relative angles. The experimental setup, detection method and preliminary results from the field trials performed in the summer of 2013 in Sesimbra, Portugal and in La Spezia, Italy are also presented in this work.

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All-terrain robot locomotion is an active topic of research. Search and rescue maneuvers and exploratory missions could benefit from robots with the abilities of real animals. However, technological barriers exist to ultimately achieving the actuation system, which is able to meet the exigent requirements of these robots. This paper describes the locomotioncontrol of a leg prototype, designed and developed to make a quadruped walk dynamically while exhibiting compliant interaction with the environment. The actuation system of the leg is based on the hybrid use of series elasticity and magneto-rheological dampers, which provide variable compliance for natural-looking motion and improved interaction with the ground. The locomotioncontrol architecture has been proposed to exploit natural leg dynamics in order to improve energy efficiency. Results show that the controller achieves a significant reduction in energy consumption during the leg swing phase thanks to the exploitation of inherent leg dynamics. Added to this, experiments with the real leg prototype show that the combined use of series elasticity and magneto-rheologicaldamping at the knee provide a 20 % reduction in the energy wasted in braking the knee during its extension in the leg stance phase.

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Planning, navigation, and search are fundamental human cognitive abilities central to spatial problem solving in search and rescue, law enforcement, and military operations. Despite a wealth of literature concerning naturalistic spatial problem solving in animals, literature on naturalistic spatial problem solving in humans is comparatively lacking and generally conducted by separate camps among which there is little crosstalk. Addressing this deficiency will allow us to predict spatial decision making in operational environments, and understand the factors leading to those decisions. The present dissertation is comprised of two related efforts, (1) a set of empirical research studies intended to identify characteristics of planning, execution, and memory in naturalistic spatial problem solving tasks, and (2) a computational modeling effort to develop a model of naturalistic spatial problem solving. The results of the behavioral studies indicate that problem space hierarchical representations are linear in shape, and that human solutions are produced according to multiple optimization criteria. The Mixed Criteria Model presented in this dissertation accounts for global and local human performance in a traditional and naturalistic Traveling Salesman Problem. The results of the empirical and modeling efforts hold implications for basic and applied science in domains such as problem solving, operations research, human-computer interaction, and artificial intelligence.

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Consider a person searching electronic health records, a search for the term ‘cracked skull’ should return documents that contain the term ‘cranium fracture’. A information retrieval systems is required that matches concepts, not just keywords. Further more, determining relevance of a query to a document requires inference – its not simply matching concepts. For example a document containing ‘dialysis machine’ should align with a query for ‘kidney disease’. Collectively we describe this problem as the ‘semantic gap’ – the difference between the raw medical data and the way a human interprets it. This paper presents an approach to semantic search of health records by combining two previous approaches: an ontological approach using the SNOMED CT medical ontology; and a distributional approach using semantic space vector space models. Our approach will be applied to a specific problem in health informatics: the matching of electronic patient records to clinical trials.