Abstract
This paper describes a vision control algorithm for flying wing wildfire tracking. The aircraft, equipped with a camera attached to a gimbal, is dropped at a given altitude by a high-altitude balloon, and then performs a gliding descent while surveying the region of interest.
The control methodology chosen was the image-based visual servoing (IBVS). An algorithm was developed to control the gliding descent trajectory, keeping the camera fixed. The results obtained for the simulations with the camera fixed validated the algorithm, although with a deviation between the position of the target in the image and its center. The stationary error was suppressed by controlling the camera rotation. The gimbal and camera were modeled, and respective Proportional-Integral controllers were designed. The algorithm was tested in a realistic simulation environment, demonstrating to effectively control the flying wing trajectory in order to guarantee wildfire monitoring.
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Acknowledgements
This work was supported by FCT - Fundação para a Ciência e a Tecnologia, I.P., through IDMEC, under project Eye in the Sky, PCIF/SSI/0103/2018, and under LAETA, project UIDB/50022/2020.
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Nunes, A.P., Moutinho, A., Azinheira, J.R. (2023). Flying Wing Wildfire Tracking Using Visual Servoing and Gimbal Control. In: Rousseau, JJ., Kapralos, B. (eds) Pattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges. ICPR 2022. Lecture Notes in Computer Science, vol 13644. Springer, Cham. https://doi.org/10.1007/978-3-031-37742-6_13
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