Temporal Siamese Networks for Clutter Mitigation Applied to Vision-Based Quadcopter Formation Control
Temporal Siamese Networks for Clutter Mitigation Applied to Vision-Based Quadcopter Formation Control
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DOI：
10.1109/lra.2020.3028056
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发表时间：
2021-01
影响因子：
5.2
通讯作者：
James Dunn;Roberto Tron
中科院分区：
文献类型：
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作者：
James Dunn;Roberto Tron
应用于视频流的卷积神经网络通常会遭受短暂的错误分类或杂物和噪音中的错误警报。我们介绍了一种基于暹罗网络技术的新型网络培训方法，该方法可减轻沙漏CNN中的错误警报，该警报在实时视频流中分离四方。为了实时在现实世界应用程序中演示此方法，我们将其作为基于视觉形成控制的四轮驱动器跟踪器的一部分实现。四轮驱动无人机形成控制是区域监视，搜救，农业和侦察等领域的重要能力。特别令人感兴趣的是在无线通信和/或GP的环境中可以拒绝或不够准确的环境中的形成控制。利用视觉指导四肢驱动器解决了这些情况，但是计算机视觉算法通常在计算上很昂贵，并且遭受了高的错误检测率。我们基于暹罗网络的新型杂物缓解技术是减轻这种混乱的好方法，而无需在运行时增加计算复杂性。我们在ODROID XU4上运行实时实现，并使用安装在四轮驱动器无人机上的标准网络摄像头。运动捕获量中的飞行测试表明，在Leader-prossorpor设置中，有两个四肢旋转器成功地进行了控制。
Convolutional neural networks applied to video streams often suffer from short-lived misclassifications or false alarms from clutter and noise. We introduce a novel network training method based on the Siamese Networks technique that mitigates false alarms in an Hourglass CNN that segments out quadcopters in a live video stream. To demonstrate this method in a real-world application in real-time, we implement it as part of a quadcopter tracker for vision-based formation control. Quadcopter drone formation control is an important capability for fields like area surveillance, search and rescue, agriculture, and reconnaissance. Of particular interest is formation control in environments where wireless communications and/or GPS may be either denied or not sufficiently accurate for the desired application. Using vision to guide the quadcopters addresses these situations, but computer vision algorithms are often computationally expensive and suffer from high false detection rates. Our novel Siamese networks-based clutter mitigation technique is a good way to mitigate this clutter without added computational complexity at run-time. We run our real-time implementation on an ODROID XU4 with a standard webcam mounted to a quadcopter drone. Flight tests in a motion capture volume demonstrate successful formation control with two quadcopters in a leader-follower setup.