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Vision-based pose estimation of a multi-rotor unmanned aerial vehicle

机译:一种基于视觉的多旋翼无人机姿态估计

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Purpose - The purpose of this paper is to facilitate autonomous landing of a multi-rotor unmanned aerial vehicle (UAV) on a moving/tilting platform using a robust vision-based approach. Design/methodology/approach - Autonomous landing of a multi-rotor UAV on a moving or tilting platform of unknown orientation in a GPS-denied and vision-compromised environment presents a challenge to common autopilot systems. The paper proposes a robust visual data processing system based on targets' Oriented FAST and Rotated BRIEF features to estimate the UAVs three-dimensional pose in real time. Findings - The system is able to visually locate and identify the unique landing platform based on a cooperative marker with an error rate of 1° or less for all roll, pitch and yaw angles. Practical implications - The proposed vision-based system aims at on-board use and increased reliability without a significant change to the computational load of the UAV. Originality/value - The simplicity of the training procedure gives the process the flexibility needed to use a marker of any unknown/irregular shape or dimension. The process can be easily tweaked to respond to different cooperative markers. The on-board computationally inexpensive process can be added to off-the-shelf autopilots.
机译:目的-本文的目的是使用一种强大的基于视觉的方法来促进多旋翼无人机(UAV)在移动/倾斜平台上的自主着陆。设计/方法/方法-在GPS受限且视力受损的环境中,多旋翼无人机在未知方向的移动或倾斜平台上的自动降落对常见的自动驾驶系统提出了挑战。本文提出了一种基于目标的定向FAST和Rotated Brief特征的鲁棒的视觉数据处理系统,以实时估计无人机的三维姿态。结果-系统能够基于协作标记在视觉上定位和识别唯一的着陆平台,所有侧倾,俯仰和偏航角的错误率均小于或等于1°。实际意义-拟议的基于视觉的系统旨在机载使用并提高可靠性,而不会显着改变无人机的计算负荷。原创性/价值-培训过程的简单性为过程提供了使用任何未知/不规则形状或尺寸的标记所需的灵活性。可以轻松调整该过程以响应不同的协作标记。机载计算上不昂贵的过程可以添加到现成的自动驾驶仪上。

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