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Design of an Embedded Multi-Camera Vision System—A Case Study in Mobile Robotics

机译:嵌入式多摄像机视觉系统的设计 - 移动机器人案例研究

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摘要

The purpose of this work is to explore the design principles for a Real-Time Robotic Multi Camera Vision System, in a case study involving a real world competition of autonomous driving. Design practices from vision and real-time research areas are applied into a Real-Time Robotic Vision application, thus exemplifying good algorithm design practices, the advantages of employing the “zero copy one pass” methodology and associated trade-offs leading to the selection of a controller platform. The vision tasks under study are: (i) recognition of a “flat” signal; and (ii) track following, requiring 3D reconstruction. This research firstly improves the used algorithms for the mentioned tasks and finally selects the controller hardware. Optimization for the shown algorithms yielded from 1.5 times to 190 times improvements, always with acceptable quality for the target application, with algorithm optimization being more important on lower computing power platforms. Results also include a 3-cm and five-degree accuracy for lane tracking and 100% accuracy for signalling panel recognition, which are better than most results found in the literature for this application. Clear results comparing different PC platforms for the mentioned Robotic Vision tasks are also shown, demonstrating trade-offs between accuracy and computing power, leading to the proper choice of control platform. The presented design principles are portable to other applications, where Real-Time constraints exist.
机译:这项工作的目的是为了探索实时机器人多摄像头视觉系统的设计原则,在涉及自动驾驶的一个真实的世界竞争的案例研究。从视觉和实时的研究领域设计实践被应用到实时机器人视觉应用程序,从而例证好的算法设计手法,采用“零拷贝一个通”方法的优点和相关的权衡导致的选择控制器平台。所研究的视觉任务是:(i)识别“平坦”信号;和(ii)跟踪以下,需要三维重建。该研究首先改善了上述任务所使用的算法,并最终选择了控制器硬件。优化用于从1.5倍屈服于190倍的改进,总是与用于目标应用可接受的质量,用算法优化是在较低的计算能力的平台的更多重要所示的算法。结果还包括用于车道跟踪3厘米和五度的精度和100%的准确度用于信令面板识别,这是比大多数的结果在文献中用于该应用中。比较对于所提到的机器人视觉任务不同的PC平台上清除结果也显示,表明精度和计算能力之间进行权衡,从而控制平台的正确选择。所提出的设计原则是移植到其他的应用,其中实时约束存在。

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