| 引用本文: | 张梁,徐锦法,夏青元,等.地面目标特征识别与无人飞行器位姿估计.[J].国防科技大学学报,2015,37(1):159-164.[点击复制] |
| ZHANG Liang,XU Jinfa,XIA Qingyuan,et al.Feature recognition of ground target and position and attitude estimation for unmanned aerial vehicle[J].Journal of National University of Defense Technology,2015,37(1):159-164[点击复制] |
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| 地面目标特征识别与无人飞行器位姿估计 |
| 张梁1, 徐锦法1, 夏青元2, 于永军1 |
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(1.南京航空航天大学 直升机旋翼动力学国家级重点实验室，江苏 南京 210016;2.南京理工大学 高维信息智能感知与系统教育部重点实验室，江苏 南京 210094)
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| 摘要: |
| 针对小型无人飞行器位置姿态估计问题，提出了一种基于视觉图像目标特征的相对位姿估计算法。应用Camshift算法获取目标初始位置，利用非线性尺度空间下的KAZE特征进行跟踪区域特征点提取，与源目标特征点进行匹配，得到精确的目标位置信息，实现了在图像平面内的目标快速跟踪，并得到机体轴系下无人飞行器与目标间相对位置和姿态角的估计值。对算法进行了实验验证，具有优良的跟踪性和实时性。 |
| 关键词: 无人飞行器 目标识别 位姿估计 KAZE特征 Camshift算法 |
| DOI：10.11887/j.cn.201501027 |
| 投稿日期：2014-05-28 |
| 基金项目:国家部委预研基金资助项目(9140C400504130C40003)；教育部重点实验室基金资助项目（30920140122006）；中国博士后科学基金资助项目(2013M541668) |
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| Feature recognition of ground target and position and attitude estimation for unmanned aerial vehicle |
| ZHANG Liang1, XU Jinfa1, XIA Qingyuan2, YU Yongjun1 |
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(1. National key Laboratory of Rotorcraft Aeromechanics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;2. Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information, Ministry of Education,
Nanjing University of Science and Technology, Nanjing 210094, China)
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| Abstract: |
| Aimed at the problem of position and attitude estimation for UAV, a relative position and attitude estimation algorithm based on target features in image was proposed. The initial location of the target was obtained with Camshift algorithm. The feature points in tracking area based on the nonlinear scale space were picked up with KAZE features, which were used to match with the feature points of the source target. The exact location of the target could be obtained and the target could be tracked quickly in the picture plane. The estimation of relative position and attitude between the unmanned aerial vehicle and target was conducted in the body frame of axes. Some experiments were fulfilled for the verification of the algorithm. Results show that the proposed algorism has strong tracking and real-time performance. |
| Keywords: unmanned aerial vehide target recognition position/attitude estimation KAZE features camshift algorithm |
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