Cai Jia, Huang Panfeng, Zhang Bin, Wang Dongke
National Key Laboratory of Aerospace Flight Dynamics, Northwestern Polytechnical University, 710072 Xi'an, China.
Research Center for Intelligent Robotics, School of Astronautics, Northwestern Polytechnical University, 710072 Xi'an, China.
Sensors (Basel). 2015 Dec 21;15(12):32152-67. doi: 10.3390/s151229884.
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.
所谓的系留空间机器人(TSR)是一种新型的主动式空间碎片清除系统。为了解决其在近距离交会过程中非合作目标识别的问题,本文提出了一种基于未校准单目互补金属氧化物半导体(CMOS)的实时视觉伺服系统框架。当使用小模板与大场景进行匹配时,总是会导致不匹配,因此提出了一种新颖的模板匹配算法来解决该问题。首先,该新颖的匹配算法根据加速段特征(FAST)算法采用空心环形结构,使该方法具有旋转不变性。此外,空心结构可以减小累积偏差。匹配函数由模板与目标图像之间的灰度和梯度差异组成,这有助于降低光照和噪声的影响。然后,设计了一种动态模板更新策略,以避免因错误匹配或遮挡导致的跟踪失败。最后,该系统综合了最小二乘积分预测器,实现了在复杂环境下的在线跟踪。地面实验结果表明,所提出的算法可以减少复杂计算的需求并提高匹配精度。