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Smart navigation and dynamic path planning of a micro-jet in a post disaster scenario

Small sized unmanned aerial vehicles (UAV) play major roles in variety of applications for aerial explorations and surveillance, transport, videography/photography and other areas. However, some other real life applications of UAV have also been studied. One of them is as a 'Disaster Response' component. In a post disaster situation, the UAVs can be used for search and rescue, damage assessment, rapid response and other emergency operations. However, in a disaster response situation it is very challenging to predict whether the climatic conditions are suitable to fly the UAV. Also it is necessary for an efficient dynamic path planning technique for effective damage assessment. In this paper, such dynamic path planning algorithms have been proposed for micro-jet, a small sized fixed wing UAV for data collection and dissemination in a post disaster situation. The proposed algorithms have been implemented on paparazziUAV simulator considering different environment simulators (wind speed, wind direction etc.) and calibration parameters of UAV like battery level, flight duration etc. The results have been obtained and compared with baseline algorithm used in paparazziUAV simulator for navigation. It has been observed that, the proposed navigation techniques work well in terms of different calibration parameters (flight duration, battery level) and can be effective not only for shelter point detection but also to reserve battery level, flight time for micro-jet in a post disaster scenario. The proposed techniques take approximately 20% less time and consume approximately 19% less battery power than baseline navigation technique. From analysis of produced results, it has been observed that the proposed work can be helpful for estimating the feasibility of flying UAV in a disaster response situation. Finally, the proposed path planning techniques have been carried out during field test using a micro-jet. It has been observed that, our proposed dynamic path planning algorithms give proximate results compare to simulation in terms of flight duration and battery level consumption.