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A high-speed iterative closest point tracker on an FPGA platform .

机译:FPGA平台上的高速迭代最近点跟踪器。

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摘要

The Iterative Closest Point (ICP) algorithm is one of the most commonly used range image processing methods. However, slow operational speeds and high input bandwidths limit the use of ICP in high-speed real-time applications.;This thesis presents and examines a novel hardware implementation of a high-speed ICP object tracking system that uses stereo vision disparities as input. Although software ICP trackers already exist, this innovative hardware tracker utilizes the efficiencies of custom hardware processing, thus enabling faster high-speed real-time tracking. A custom hardware design has been implemented in an FPGA to handle the inherent bottlenecks that result from the large input and processing bandwidths of the range data. The hardware ICP design consists of four stages: Pre-filter, Transform, Nearest Neighbor, and Transform Recovery.;This custom hardware has been implemented and tested on various objects, using both software simulation and hardware tests. Results indicate that the tracker is able to successfully track free-form objects at over 200 frames-per-second along arbitrary paths. Tracking errors are low, in spite of substantial noisy stereo input. The tracker is able to track stationary paths within 0.42 mm and 1.42 degrees, linear paths within 1.57 mm and 2.80 degrees, and rotational paths within 0.39 degrees axis error. With further degraded data by occlusion, the tracker is able to handle 60% occlusion before a slow decline in performance. The high-speed hardware implementation (that uses 16 parallel nearest neighbor circuits), is more then five times faster than the software K-D tree implementation.;This tracker has been designed as the hardware component of 'FastTrack', a high frame rate, stereo vision tracking system, that will provide a known object's pose in real-time at 200 frames per second. This hardware ICP tracker is compact, lightweight, has low power requirements, and is integratable with the stereo sensor and stereo extraction components of the 'FastTrack' system on a single FPGA platform.;High-speed object tracking is useful for many innovative applications, including advanced spaced-based robotics. Because of this project's success, the 'FastTrack' system will be able to aid in performing in-orbit, automated, remote satellite recovery for maintenance.
机译:迭代最近点(ICP)算法是最常用的距离图像处理方法之一。但是,慢速的操作速度和高的输入带宽限制了ICP在高速实时应用中的使用。本论文介绍并研究了以立体视觉差异作为输入的高速ICP对象跟踪系统的新型硬件实现。尽管软件ICP跟踪器已经存在,但是这种创新的硬件跟踪器利用了自定义硬件处理的效率,因此可以实现更快的高速实时跟踪。在FPGA中实现了自定义硬件设计,以处理因范围数据的输入和处理带宽较大而导致的固有瓶颈。硬件ICP设计包括四个阶段:预滤波器,变换,最近邻居和变换恢复。该自定义硬件已使用软件仿真和硬件测试在各种对象上实现和测试。结果表明,跟踪器能够沿任意路径以每秒200帧的速度成功跟踪自由格式的对象。尽管立体声输入很大,但跟踪误差仍然很小。跟踪器能够跟踪0.42 mm和1.42度以内的固定路径,1.57 mm和2.80度以内的线性路径以及0.39度以内的轴误差。通过遮挡使数据进一步降级,跟踪器能够在性能缓慢下降之前处理60%的遮挡。高速硬件实现(使用16个并行的最近邻电路)比软件KD树实现快五倍以上;该跟踪器被设计为“ FastTrack”的硬件组件,即高帧率立体声视觉跟踪系统,它将以每秒200帧的速度实时提供已知物体的姿势。该硬件ICP跟踪器紧凑,轻巧,功耗低,并且可以在单个FPGA平台上与'FastTrack'系统的立体声传感器和立体声提取组件集成在一起;高速对象跟踪对于许多创新应用非常有用,包括先进的基于空间的机器人技术。由于该项目的成功,“ FastTrack”系统将能够帮助进行在轨,自动化,远程卫星恢复以进行维护。

著录项

  • 作者

    Belshaw, Michael Sweeney.;

  • 作者单位

    Queen's University (Canada).;

  • 授予单位 Queen's University (Canada).;
  • 学科 Engineering Electronics and Electrical.
  • 学位 M.Sc.
  • 年度 2008
  • 页码 134 p.
  • 总页数 134
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电电子学、电信技术;
  • 关键词

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