The intersection between control algorithms and the environment pose multiple issues regarding safe and reliable operations of remote-controlled and autonomous quadcopters for commercial and defense applications. This is particularly true in urban environments, which can pose significant problems to navigation and safety. We are developing a new platform for the development and testing of control schemes for quad-copters in urban environments, with emphasis on the intersection of drone and environmental physics, the uncertainty inherent in each, and control algorithms employed. As our basis, we are using Unreal Engine, which provides exibility for physics and controls used, in addition to state-of-the-art visualization, environmental interactions (e.g. collision simulation) and user interface tools. We incorporate the open-source, open-architecture PixHawk PX4 software platform, with the object of transitioning control algorithms to hardware in the future. Finally, we convert models of actual cities from MapBox and OpenStreetMap for use in Unreal Engine. We conclude with a demonstration of human-controlled drone ight in a section of Chicago, IL with light, uni-directional winds.
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