<p> </p> <p>A search and rescue (SAR) operation requires a rapid, accurate, and effective response to provide the missing person the best chance of being rescued. Personnel from the local area are likely to be closest to the location of the missing person, be familiar with the area, but they may not be adequately trained, experienced, or equipped with the best tools to effectively locate, identify, and retrieve the missing person. Thus, most SAR operations rely on a mix of trained personnel and volunteers. Among the trained personnel, there is a wide variance in proficiency, experience, and access to technology, leading to some emergency response agencies being better prepared than others. Volunteers, on the other hand, could be very helpful, but are largely untrained and inexperienced, reducing their inherent likelihood of success. The primary challenge to successful SAR operations is the lack of consistently trained, adequately equipped, and diversely experienced personnel. Despite the lack of desired resources, SAR operations must be completed rapidly and emergency responders often turn to volunteers. In response to this challenge, the use of unmanned aerial systems, UAS, in small volunteer teams was proposed. Available, off-the-shelf UAS technology can be used to simplify training with the help of affordable advanced technology, and thereby enable rapid, accurate, and effective SAR operations.  </p> <p>The following research was executed in the form of three independent, but related, studies. The first study focused on the efficiency of a UAS-equipped SAR operation; the second study focused on the accuracy of a UAS and image analysis software-enabled SAR operation; and the third study tested the ability of novice volunteers to learn and apply the new technologies (UAS plus image analysis) efficiently and effectively. The goal of these studies was to determine whether affordable commercial, off-the-shelf technologies could be used to enhance the efficiency and effectivity of SAR operations. The experimental methodology used specifically designed simulations of SAR operational scenarios. Two operational tactics were tested: (a) Equip the SAR team with UAS and (b) equip the SAR team with UAS and image analysis software. The specific scenarios selected were similar in complexity, but different enough to minimize the transfer of learning from the first study to the second study.  Finally, the reference times for manual SAR operations were compared against UAS and computerized image analysis software-assisted methods. The results of the proposed studies determined whether off-the-shelf UAS and image analysis technologies could be used to enable rapid, accurate, and effective SAR operations. </p>

No description available.

Thesis (M.A.)--University of North Carolina at Wilmington, 2006. / Includes bibliographical references (leaves: 66-66)

Urban Search and Rescue (USAR) is the emergency response function that deals with the collapse of man-made structures. USAR environments contain concrete rubble, dust and debris, and provide poor lighting conditions. Due to the dangers that USAR rescue workers and their canines face, robots have become of interest in aiding rescue workers in searching. Experiences with robots in USAR missions have shown that a compact 3D sensor for 3D mapping of the environment is beneficial in providing the robot and identified victims’ locations within the structurally unstable environment. This thesis presents the developments of a novel 3D sensory system that provides both 3D and 2D texture information for mapping of cluttered unknown USAR environments. The sensor has been integrated into a robot platform, and experiments conducted to validate its usability in such applications. The experimental results show the potential for using this sensor in USAR robot mission.

Urban Search and Rescue (USAR) is the emergency response function that deals with the collapse of man-made structures. USAR environments contain concrete rubble, dust and debris, and provide poor lighting conditions. Due to the dangers that USAR rescue workers and their canines face, robots have become of interest in aiding rescue workers in searching. Experiences with robots in USAR missions have shown that a compact 3D sensor for 3D mapping of the environment is beneficial in providing the robot and identified victims’ locations within the structurally unstable environment. This thesis presents the developments of a novel 3D sensory system that provides both 3D and 2D texture information for mapping of cluttered unknown USAR environments. The sensor has been integrated into a robot platform, and experiments conducted to validate its usability in such applications. The experimental results show the potential for using this sensor in USAR robot mission.

Thesis (M. Arch.)--University of Hong Kong, 1996. / Includes special report study entitled: Skin and skeleton of a hangar. Includes bibliographical references.

The purpose of this thesis is to create an indoor rescue scenario with multiple self-localizing robots that are able to collaborate for a victim search. Victims are represented by RFID tags and detecting them combined with an accurate enough location data is considered as a successful finding. This setup is created for use in a laboratory assignment at Linköping University. We consider the indoor localization problem by trying to use as few sensors as possible and implement three indoor localization methods - odometry based, passive RFID based, and our approach by fusing both sensor data with particle filter.The Results show that particle filter based localization performs the best in comparison to the two other implemented methods and satisfies the accuracy requirements stated for the scenario. The victim search problem is solved by an ant mobility (pheromone-based) approach which integrates our localization method and provides a collaborative navigation through the rescue area. The purpose of the pheromone mobility approach is to achieve a high coverage with an acceptable resource consumption.Experiments show that area is covered with approximately 30-40% overhead in traveled distance comparing to an optimal path.

Thesis (Ph.D.)--University of Delaware, 2008. / Principal faculty advisor: Benigno E. Aguirre, Dept. of Sociology & Criminal Justice. Includes bibliographical references.

Thesis (M.S. in Defense Analysis)--Naval Postgraduate School, Dec. 2004. / Thesis Advisor(s): Erik Jansen. Includes bibliographical references (p. 91-93). Also available online.

Thesis (M.Arch.)--University of Hong Kong, 1996. / Includes special report study entitled : Skin and skeleton of a hangar. Includes bibliographical references. Also available in print.