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• W4285117968 abstract "In this letter, we tackle the problem of flying a quadrotor using time-optimal control policies that can be replanned online when the environment changes or when encountering unknown disturbances. This problem is challenging as the time-optimal trajectories that consider the full quadrotor dynamics are computationally expensive to generate, on the order of minutes or even hours. We introduce a sampling-based method for efficient generation of time-optimal paths of a point-mass model. These paths are then tracked using a Model Predictive Contouring Control approach that considers the full quadrotor dynamics and the single rotor thrust limits. Our combined approach is able to run in real-time, being the first time-optimal method that is able to adapt to changes <italic xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>on-the-fly</i> . We showcase our approach’s adaption capabilities by flying a quadrotor at more than 60 km/h in a racing track where gates are moving. Additionally, we show that our online replanning approach can cope with strong disturbances caused by winds of up to 68 km/h." @default.
• W4285117968 created "2022-07-14" @default.
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• W4285117968 date "2022-07-01" @default.
• W4285117968 modified "2023-10-16" @default.
• W4285117968 title "Time-Optimal Online Replanning for Agile Quadrotor Flight" @default.
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• W4285117968 doi "https://doi.org/10.1109/lra.2022.3185772" @default.
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