Real-time Planning of Minimum-time Trajectories for Agile UAV Flight
<|reference_start|>Real-time Planning of Minimum-time Trajectories for Agile UAV Flight: We address the challenge of real-time planning of minimum-time trajectories over multiple waypoints, onboard multirotor UAVs. Previous works demonstrated that achieving a truly time-optimal trajectory is computationally too demanding to enable frequent replanning during agile flight, especially on less powerful flight computers. Our approach overcomes this stumbling block by utilizing a point-mass model with a novel iterative thrust decomposition algorithm, enabling the UAV to use all of its collective thrust, something previous point-mass approaches could not achieve. The approach enables gravity and drag modeling integration, significantly reducing tracking errors in high-speed trajectories, which is proven through an ablation study. When combined with a new multi-waypoint optimization algorithm, which uses a gradient-based method to converge to optimal velocities in waypoints, the proposed method generates minimum-time multi-waypoint trajectories within milliseconds. The proposed approach, which we provide as open-source package, is validated both in simulation and in real-world, using Nonlinear Model Predictive Control. With accelerations of up to 3.5g and speeds over 100 km/h, trajectories generated by the proposed method yield similar or even smaller tracking errors than the trajectories generated for a full multirotor model.<|reference_end|>
@article{teissing2024real-time,
    title={Real-time Planning of Minimum-time Trajectories for Agile UAV Flight},
    author={Krystof Teissing, Matej Novosad, Robert Penicka, Martin Saska},
    journal={arXiv preprint arXiv:2409.16074},
    year={2024},
    doi={10.1109/LRA.2024.3471388},
    archivePrefix={arXiv},
    eprint={2409.16074},
    primaryClass={cs.RO}
}