基于眼手视觉伺服的自主无人机碰撞着陆控制

Nikolai Kummer, Alexandra Beresowskaja, H. Firouzi, H. Najjaran
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引用次数: 3

摘要

固定翼无人机在着陆阶段最容易发生灾难性损伤。为了解决这一问题,已有文献提出了基于视觉的小型无人机自主着陆方法。本文改进了先前关于通过与大型充气气囊的可控碰撞实现基于视觉的着陆的工作。在提出的方法中,无人机转向一个大的、多色的、圆顶状的安全气囊,使用从安装在无人机上的摄像机获得的视觉反馈。提出了一种基于颜色的多色安全气囊,以实现图像中球体的实时检测。所提出的视觉伺服控制器将圆顶位置转换为所需的俯仰和偏航率命令,以实现图像误差的指数衰减。设计了一种模型预测无人机控制器,实现了期望的横摇和偏航速率,并进行了仿真测试。对无人机的横向和纵向动力学进行解耦,建立了无人机的线性离散状态空间模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Autonomous UAV controlled collision landing via eye-in-hand visual servoing
Catastrophic damage to fixed-wing unmanned aerial vehicles (UAV) is most likely to occur during the landing stage. Vision-based autonomous landing methods for small UAV have been proposed in literature to address the issue. This paper improves on previous work on vision-based landing via a controlled collision with a large inflatable airbag. In the proposed method the UAV steers towards a large, multi-coloured, dome-shaped airbag using visual feedback obtained from a UAV-mounted camera. A multi-colour airbag is proposed to facilitate a robust and efficient colour-based detection method for real-time detection of the dome in images. A proposed visual servoing controller translates the dome location into desired pitch and yaw rate commands to achieve an exponential decay of the image error. A model predictive UAV controller that achieves desired roll and yaw rates is designed and tested in simulations. The lateral and longitudinal UAV dynamics were decoupled and a linear discrete state space model of the dy...
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