基于视觉的飞行器运动参数串行式递归估计被引量：2

Motion Estimation of a Vehicle Using Sequential Recursive Algorithm from Images

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摘要针对利用视觉方法进行飞行器运动参数估计中旋转与平移参数耦合及计算量大的问题,设计了一种适用于递归方法的串行式运动参数估计模型。证明了旋转运动参数的估计不依赖于平移参数,据此建立了基于特征线的旋转运动参数估计模型,进而设计了串行式运动参数估计模型。给出并证明了利用该模型进行运动参数估计时解的唯一性结论。仿真实验和实测试验表明:相对于集中式模型,使用串行式递归模型进行飞行器运动参数估计时计算耗时减小、姿态精度更高、鲁棒性更强。 Aiming at solving the problem of coupling and time-consuming in estimating the motion parameters of a vehicle based on computer vision, a sequential model for recursive algorithm is designed. It is proved that the estimation of rotation parameters can be separated from that of the translation parameters. With this fact, the rotation model is build based on lines, and then the proposed sequential model is build. A proof for the uniqueness of the motion parameters is given. The sequential model is tested using both simulated and real images, and the results show that the time-consuming problem is solved partly, estimation of rotation parameter is more accurate, and the estimator based on the sequential model is more robust.

作者霍炬仲小清杨明

机构地区哈尔滨工业大学控制与仿真中心

出处《宇航学报》 EI CAS CSCD 北大核心 2010年第2期361-368,共8页 Journal of Astronautics

基金黑龙江省杰出青年科学基金(JC200606) 哈尔滨工业优秀青年教师培养计划(HITQNJS2007021)

关键词计算机视觉运动估计模型解耦运动估计模型唯一性递归算法 Computer vision Motion estimation Motion decoupling Estimation model Uniqueness Recursive algorithm

分类号 TP391 [自动化与计算机技术—计算机应用技术]

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