Reach-Avoid Control Synthesis for a Quadrotor UAV with Formal Safety Guarantees
<|reference_start|>Reach-Avoid Control Synthesis for a Quadrotor UAV with Formal Safety Guarantees: Reach-avoid specifications are one of the most common tasks in autonomous aerial vehicle (UAV) applications. Despite the intensive research and development associated with control of aerial vehicles, generating feasible trajectories though complex environments and tracking them with formal safety guarantees remain challenging. In this paper, we propose a control framework for a quadrotor UAV that enables accomplishing reach-avoid tasks with formal safety guarantees. In this proposed framework, we integrate geometric control theory for tracking and polynomial trajectory generation using Bezier curves, where tracking errors are accounted for in the trajectory synthesis process. To estimate the tracking errors, we revisit the stability analysis of the closed-loop quadrotor system, when geometric control is implemented. We show that the tracking error dynamics exhibit local exponential stability when geometric control is implemented with any positive control gains, and we derive tight uniform bounds of the tracking error. We also introduce sufficient conditions to be imposed on the desired trajectory utilizing the derived uniform bounds to ensure the well-definedness of the closed-loop system. For the trajectory synthesis, we present an efficient algorithm that enables constructing a safe tube by means of sampling-based planning and safe hyper-rectangular set computations. Then, we compute the trajectory, given as a piecewise continuous Bezier curve, through the safe tube, where a heuristic efficient approach that utilizes iterative linear programming is employed. We present extensive numerical simulations with a cluttered environment to illustrate the effectiveness of the proposed framework in reach-avoid planning scenarios.<|reference_end|>
@article{serry2024reach-avoid,
    title={Reach-Avoid Control Synthesis for a Quadrotor UAV with Formal Safety
  Guarantees},
    author={Mohamed Serry, Haocheng Chang, Jun Liu},
    journal={arXiv preprint arXiv:2405.20502},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.20502},
    primaryClass={eess.SY cs.SY math.DS math.OC}
}