基于滚动时域NMPC的密集固定翼蜂群控制
Dense Fixed-Wing Swarming using Receding-Horizon NMPC
AI总结：
针对敏捷固定翼飞行器近距离蜂群飞行的避障需求，提出基于滚动时域NMPC的控制方法，结合轨迹偏离概率统计界实现鲁棒避障，经仿真与硬件实验验证，为首次在实体特技固定翼上实现近距离蜂群飞行。
摘要：
本文提出了一种控制一组敏捷固定翼飞行器近距离编队飞行的方法。该方法依托滚动时域非线性模型预测控制（NMPC，Nonlinear Model Predictive Control），在扩展飞行包线内规划机动动作，以实现智能体间的避障。为实现鲁棒避障并量化智能体间碰撞的可能性，我们计算了系统偏离规划标称轨迹周围管形区域概率的统计界。最后，我们提出了一种评估高动态蜂群的指标，并以此评估所提方法。我们通过仿真和硬件实验均成功验证了该方法，据我们所知，这是首次在实体特技固定翼飞行器上实现近距离蜂群飞行。
英文摘要：
In this paper, we present an approach for controlling a team of agile fixed-wing aerial vehicles in close proximity to one another. Our approach relies on receding-horizon nonlinear model predictive control (NMPC) to plan maneuvers across an expanded flight envelope to enable inter-agent collision avoidance. To facilitate robust collision avoidance and characterize the likelihood of inter-agent collisions, we compute a statistical bound on the probability of the system leaving a tube around the planned nominal trajectory. Finally, we propose a metric for evaluating highly dynamic swarms and use this metric to evaluate our approach. We successfully demonstrated our approach through both simulation and hardware experiments, and to our knowledge, this the first time close-quarters swarming has been achieved with physical aerobatic fixed-wing vehicles.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
