Tracking position and orientation independently affords more agile maneuver for over-actuated multirotor Unmanned Aerial Vehicles (UAVs) while introducing undesired downwash effects; downwash flows generated by thrust generators may counteract others due to close proximity, which significantly threatens the stability of the platform. The complexity of modeling aerodynamic airflow challenges control algorithms from properly compensating for such a side effect. Leveraging the input redundancies in over-actuated UAVs, we tackle this issue with a novel control allocation framework that considers downwash effects and explores the entire allocation space for an optimal solution. This optimal solution avoids downwash effects while providing high thrust efficiency within the hardware constraints. To the best of our knowledge, ours is the first formal derivation to investigate the downwash effects on over-actuated UAVs. We verify our framework on different hardware configurations in both simulation and experiment.
翻译:跟踪位置和定向独立地为过度活化的多机器人无人驾驶飞行器提供了更灵活的操作方法,同时引入了不理想的下洗效应;推力发电机产生的下洗水流可能抵消其他由于距离很近而使平台稳定性受到极大威胁的物体。空气动力空气流模型的复杂性从适当补偿这种副作用的角度对控制算法提出了挑战。在过度活化的无人驾驶飞行器中利用输入的冗余来解决这一问题,我们用一个新的控制分配框架来解决这一问题,该框架考虑到下洗效应,并探索整个分配空间以达成最佳解决方案。这一最佳解决方案避免了下洗效应,同时在硬件限制范围内提供了高推力效率。据我们所知,我们是调查对过度活化的无人驾驶飞行器的下洗效应的首次正式衍生。我们在模拟和实验中都核查了我们在不同硬件配置方面的框架。