Gao Yu, Kong Xingwei, Dong Xinmin, Wang Haitao, Wang Jian. Refueling drogue tracking based on trackinglearningdetection algorithm[J]. Journal of Applied Optics, 2016, 37(3): 385-391. DOI: 10.5768/JAO201637.0302004
Citation: Gao Yu, Kong Xingwei, Dong Xinmin, Wang Haitao, Wang Jian. Refueling drogue tracking based on trackinglearningdetection algorithm[J]. Journal of Applied Optics, 2016, 37(3): 385-391. DOI: 10.5768/JAO201637.0302004

Refueling drogue tracking based on trackinglearningdetection algorithm

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  • Received Date: November 04, 2015
  • Revised Date: January 06, 2016
  • To solve the drogue tracking problem during the capture phase of autonomous aerial refueling, a trackinglearningdetection (TLD) algorithm was proposed. The algorithm decomposes the drogue tracking task into 3 subtasks: tracking, learning and detection. The tracking component is based on the LucasKanade (LK) method extended with failure detection and chooses tracking points with good performance to track the refueling drogue; and the detector constructs cascaded classifier to sort the picture patches scanned by scanningwindow and returns patches containing object, which integrates with tracking component result and gives final tracking result; and then the PN constraints are introduced into the learning component to correct wrong samples and then learn and update the detector. A scene simulation for aerial refueling was developed based on Creator/Vega Prime. The experimental results of the test on the video of scene simulation show that the success rate of tracking drogue is 95.5%, the average time consumption is about 31.4 ms, and the algorithm can meet well requirements of drogue tracking, such as robustness, precision and real time performance.
  • [1]Dong Xinmin, Xu Yuejian, Chen Bo. Process and challenges in automatic aerial refueling [J]. Journal of Air Force Engineering University (Natural Science Edition), 2008, 9(6): 15.
    董新民, 徐跃鉴, 陈博. 自动空中加油技术研究进展与关键问题[J]. 空军工程大学学报:自然科学版, 2008, 9 (6):15.
    [2]Bolkcom C, Klaus J D. Air force aerial refueling methods: flying boom versus hoseanddrogue[R].[S.l.]:[s.n.], 2005.
    [3]Thomas P R ,  Bhandari U,  Bullock S, et al. Advances in air to air refueling[J]. Progress in Aerospace Science. 2014, 71:1435.
    [4]Hansen J L, Murray J E, Campos N V. The NASA Dryden AAR project: a flight test approach to an aerial refueling system: AIAA Atmospheric Flight Mechanics Conference and Exhibit, Providence, RI,Aug 1619, 2004[C].[S.l.]:[s.n.],c2005.
    [5]Valasek J, Gunnam K, Kimmett J , et al, Visionbased sensor and navigation system for autonomous air refueling[J]. Guidance Control Dyn. ,2005, 28(5): 832844.
    [6]Pollini L, Innocenti M, Mati R. AIAA modeling and simulation technologies conference and exhibi[C].[S.l.]:[s.n.],2005:115.
    [7]Wilson D B ,Gktoan A H ,  Sukkarieh S. 2015 IEEE international conference on robotics and automation[C]. USA:IEEE,2015:53185323.
    [8]Gao Shibo, Cheng Yongmei, Song Chuanhua. Drogue detection for visionbased autonomous aerial refueling via low rank and sparse decomposition with multiple features [J]. Infrared Physics and Technology,  2013, 60(9):266274.
    [9]Martinez C, Richardson T, Thomas P, et al. A visionbased strategy for autonomous aerial refueling tasks [J]. Robotics and Autonomous Systems. 2013, 61(8):876895.
    [10]Kalal Z , Mikolajczyk K,  Matas J. Trackinglearningdetecti on[J].IEEE Trans. PAMI 2012,34(7),14091422.
    [11]Kalal Z, Mikolajczyk K. Matas J. 12th IEEE international conference on computer vision workshops(ICCV Workshops)[C].USA:IEEE,2009:14171424.
    [12]Kalal Z, Mikolajczyk K. Matas J. IEEE international conference on computer vision and pattern recognition[C].USA:IEEE, 2010:14171424.
    [13]Kalal Z. Matas J. Mikolajczyk K. IEEE conference on computer vision and pattern recognition(CVPR)[C].USA:IEEE,2010:14171424.
    [14]Wang Xufeng, Dong Xinmin, Kong Xingwei, et al. MSKF fusion algorithm for drogue tracking [J]. Journal of Applied Optics, 2013, 34(6):951956.
    王旭峰, 董新民, 孔星炜, 等. MSKF 锥套融合算法用于锥套跟踪[J]. 应用光学, 2013, 34(6):951956.
    [15]Yang Bowen, Sun Yongrong, Huang Bin, et al. HoughLS rapid detection for longdistance refueling drogue image[J]. OptoElectronic Engineering, 2015,42(4):4448.
    杨博文, 孙永荣, 黄斌, 等. 加油锥套远距图像的HoughLS快速检测[J].光电工程, 2015, 42(4):4448.
    [16]Zhao Yinling, Wu Chengfu, Chen Huaimin. Application and research of UAV scene simulation based on Vega[J]. Measurement & Control Technology, 2008, 27(1): 9699.
    赵银玲, 吴成富, 陈怀民. 基于Vega的无人机视景仿真应用研究[J]. 测控技术, 2008, 27(1): 9699.
    [17]Wang Haitao, Dong Xinmin, Guo Jun, et al. Dynamic modeling and analysis of hose whipping phenomenon of aerial refueling hosedrogue assembly[J]. Acta Aeronautica et Astronautica Sinica, 2015, 36(9):31163127.
    王海涛,董新民,郭军,等. 空中加油软管锥套组合体甩鞭现象动力学建模与分析[J]. 航空学报, 2015, 09: 31163127.
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