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A TSR Visual Servoing System Based on a Novel Dynamic Template Matching Method

机译:基于新型动态模板匹配方法的TSR视觉伺服系统

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摘要

The so-called Tethered Space Robot (TSR) is a novel active space debris removal system. To solve its problem of non-cooperative target recognition during short-distance rendezvous events, this paper presents a framework for a real-time visual servoing system using non-calibrated monocular-CMOS (Complementary Metal Oxide Semiconductor). When a small template is used for matching with a large scene, it always leads to mismatches, so a novel template matching algorithm to solve the problem is presented. Firstly, the novel matching algorithm uses a hollow annulus structure according to a FAST (Features from Accelerated Segment) algorithm and makes the method be rotation-invariant. Furthermore, the accumulative deviation can be decreased by the hollow structure. The matching function is composed of grey and gradient differences between template and object image, which help it reduce the effects of illumination and noises. Then, a dynamic template update strategy is designed to avoid tracking failures brought about by wrong matching or occlusion. Finally, the system synthesizes the least square integrated predictor, realizing tracking online in complex circumstances. The results of ground experiments show that the proposed algorithm can decrease the need for sophisticated computation and improves matching accuracy.
机译:所谓的拴系太空机器人(TSR)是一种新颖的主动空间碎片清除系统。为了解决其在短距离集合点事件中的非合作目标识别问题,本文提出了一种使用非校准单眼CMOS(互补金属氧化物半导体)的实时视觉伺服系统的框架。当小模板与大场景匹配时,总是会导致不匹配,因此提出了一种新颖的模板匹配算法。首先,该新颖的匹配算法根据FAST(来自加速段的特征)算法使用空心环形结构,并使该方法具有旋转不变性。此外,中空结构可以减小累积偏差。匹配功能由模板和对象图像之间的灰度和梯度差异组成,这有助于减少照明和噪声的影响。然后,设计一种动态模板更新策略,以避免跟踪由错误的匹配或遮挡引起的故障。最后,系统综合最小二乘综合预测器,在复杂情况下实现在线跟踪。地面实验结果表明,该算法可以减少复杂计算的需求,提高匹配精度。

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