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Learning to estimate UAV created turbulence from scene structure observed by onboard cameras
[article]
2022
arXiv
pre-print
Controlling UAV flights precisely requires a realistic dynamic model and accurate state estimates from onboard sensors like UAV, GPS and visual observations. Obtaining a precise dynamic model is extremely difficult, as important aerodynamic effects are hard to model, in particular ground effect and other turbulences. While machine learning has been used in the past to estimate UAV created turbulence, this was restricted to flat grounds or diffuse in-flight air turbulences, both without taking
arXiv:2203.14726v1
fatcat:54kdt2cjjjd5ze7vtzwz773s7e