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A novel algorithm and hardware architecture for fast video-based shape reconstruction of space debris

机译:一种基于视频的空间碎片快速形状重构的新算法和硬件架构

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In order to enable the non-cooperative rendezvous, capture, and removal of large space debris, automatic recognition of the target is needed. Video-based techniques are the most suitable in the strict context of space missions, where low-energy consumption is fundamental, and sensors should be passive in order to avoid any possible damage to external objects as well as to the chaser satellite. This paper presents a novel fast shape-from-shading (SfS) algorithm and a field-programmable gate array (FPGA)-based system hardware architecture for video-based shape reconstruction of space debris. The FPGA-based architecture, equipped with a pair of cameras, includes a fast image pre-processing module, a core implementing a feature-based stereo-vision approach, and a processor that executes the novel SfS algorithm. Experimental results show the limited amount of logic resources needed to implement the proposed architecture, and the timing improvements with respect to other state-of-the-art SfS methods. The remaining resources available in the FPGA device can be exploited to integrate other vision-based techniques to improve the comprehension of debris model, allowing a fast evaluation of associated kinematics in order to select the most appropriate approach for capture of the target space debris.
机译:为了能够非合作地会合,捕获和清除大空间碎片,需要自动识别目标。基于视频的技术最适合严格的太空飞行任务,在这种情况下,低能耗是至关重要的,传感器应该是无源的,以避免对外部物体和追赶者卫星造成任何可能的损害。本文提出了一种新颖的基于阴影的快速成型算法(SfS)和基于现场可编程门阵列(FPGA)的系统硬件架构,用于基于视频的空间碎片形状重构。基于FPGA的架构配备了一对摄像机,包括一个快速图像预处理模块,一个实现基于特征的立体视觉方法的内核以及一个执行新颖SfS算法的处理器。实验结果表明,实现所提出的体系结构所需的逻辑资源数量有限,并且相对于其他最新的SfS方法,其时序也得到了改善。可以利用FPGA器件中剩余的资源来集成其他基于视觉的技术,以提高对碎片模型的理解,从而可以快速评估相关的运动学,以便选择最合适的方法来捕获目标空间碎片。

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