3D Visual Homing for Commodity UAVs

Hao Cai, Sipan Ye, A. Vardy, Minglun Gong
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Abstract

Visual homing enables an autonomous robot to move to a target (home) position using only visual information. While 2D visual homing has been widely studied, homing in 3D space still requires much attention. This paper presents a novel 3D visual homing method which can be applied to commodity Unmanned Aerial Vehicles (UAVs). Firstly, relative camera poses are estimated through feature correspondences between current views and the reference home image. Then homing vectors are computed and utilized to guide the UAV toward the 3D home location. All computations can be performed in real-time on mobile devices through a mobile app. To validate our approach, we conducted quantitative evaluations on the most popular image sequence datasets and performed real experiments on a quadcopter (i.e., DJI Mavic Pro). Experimental results demonstrate the effectiveness of the proposed method.
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商用无人机的3D视觉定位
视觉归巢使自主机器人仅使用视觉信息就能移动到目标(家)位置。虽然二维视觉寻的方法已经得到了广泛的研究,但是三维空间的寻的方法仍然是一个值得关注的问题。提出了一种适用于商用无人机的三维视觉寻的新方法。首先,通过当前视图与参考主图像之间的特征对应来估计相对相机姿态;然后计算并利用归巢向量引导无人机向三维归巢位置移动。所有计算都可以通过移动应用程序在移动设备上实时执行。为了验证我们的方法,我们对最流行的图像序列数据集进行了定量评估,并在四轴飞行器(即DJI Mavic Pro)上进行了实际实验。实验结果证明了该方法的有效性。
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