3 research outputs found

    UAS for Public Safety: Active Threat Recognition

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    The Center for Homeland Defense and Security identified an increase of active threat events, such as mass shootings, annually since 1999. Literature suggests that 90% of shootings were over before law enforcement arrived at the scene and the first responder response was limited to “surround and contain” until Special Weapons and Tactics Teams (SWAT) arrived on the scene. Using Unmanned Aircraft Systems (UAS) to detect which individual was the threat and type of weapon used can provide useful information to increase the speed of the response for first-on-scene rather than waiting for SWAT if the type of weapon was known. A UAS equipped with a full spectrum sensor compared traditional red-green-blue (RGB) images to near-infrared (NIR) images in a simulated active threat scenario. A true positive rate (TPR) metric was used to measure the percentage of correctly-detected weapons consisting of either a knife, pistol, rifle, shotgun, or shovel at slant range distances of 25-, 50-, 75-, and 100-feet respectively. A convenience sample of 102 survey participants, recruited from constituents of the Airborne Public Safety Association (APSA) and DRONERESPONDERS was conducted to observe 48 randomly-presented images to determine which type of weapon was detected. The results suggest that survey participants could correctly detect weapons at a 12% greater rate with the NIR sensor than the RGB sensor; however, the pistol had the largest difference in TPR between NIR and RGB sensors. The pistol had an increased probability of detection by 33% when using the NIR sensor compared to an RGB sensor. Additionally, differences were also observed between slant range distances. The closest distance of 25 feet showed a 42% increase in participants’ ability to correctly determine the weapon type compared to the 100-foot slant range distance. Therefore, using a NIR sensor-equipped UAS at flying a maximum slant range distance of 50 feet may help a first-responder determine the type of weapon before SWAT arrives on the scene

    Practical applications using multi-UAV systems and aerial robotic swarms

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    [EN] Nowadays, there are a large number of unmanned aircraft on the market that can be commanded with high-level orders to perform complex tasks almost automatically, such as mapping crop fields. We can ask ourselves if it would be possible to coordinate a group of these robots to perform those same tasks more quickly, flexibly and robustly. In this work, we summarize the tasks that have been studied to be solved with systems composed by groups of unmanned aircraft and the algorithms used, as well as the methods and strategies on which they are based. Although the future of these systems is promising, there are certain legislative and technical obstacles that stop their implementation in a generalized way.[ES] A día de hoy, existen en el mercado una gran cantidad de aeronaves sin piloto que pueden ser comandadas con ordenes de alto nivel para realizar tareas complejas de forma casi automatica, como por ejemplo el mapeo de explotaciones agrícolas. De forma natural, nos podemos preguntar si sería posible coordinar a un grupo de estos robots para realizar esas mismas tareas de forma más rápida, flexible y robusta. En este trabajo se repasan las tareas que se han planteado resolver con sistemas compuestos por grupos de aeronaves no tripuladas y los algoritmos empleados, así como los metodos y estrategias en los que están basados. Aunque el futuro de estos sistemas es prometedor, existen ciertos obstaculos legislativos y técnicos que frenan su implantación de forma generalizada.Las investigaciones que han dado como resultado este trabajo han sido financiadas por RoboCity2030-DIH-CM, 426 Madrid Robotics Digital Innovation Hub, S2018/NMT-4331, financiadas por los Programas de Actividades I+D en la Comunidad Madrid, y por el proyecto TASAR (Team of Advanced Search And Rescue Robots), PID2019-105808RB-I00, financiado por el Ministerio de Ciencia e Innovacion (Gobierno de España).García-Aunon, P.; Roldán, J.; De León, J.; Del Cerro, J.; Barrientos, A. (2021). Aplicaciones practicas de los sistemas multi-UAV y enjambres aéreos. Revista Iberoamericana de Automática e Informática industrial. 18(3):230-241. https://doi.org/10.4995/riai.2020.13560OJS230241183Acevedo, J. J., Arrue, B. C., Maza, I., Ollero, A., 2013. Cooperative large area surveillance with a team of aerial mobile robots for long endurance missions. 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