【摘要】 提出了一种改进的多状态约束卡尔曼滤波器(IMSCKF)双目视觉惯性导航算法。该算法在初始阶段采用Sigma滤波器和三焦点张量约束快速完成初始化,产生的状态向量与MSCKF一致,可以实现初始化和后续导航之间的无缝过渡,提高了系统状态估计的精度和鲁棒性。实验结果表明,本文提出的IMSCKF方法位置跟踪误差维持在±1 mm,角度误差维持在±1°,可以提高双目视觉惯性导航的鲁棒性和精度。更多还原

【Abstract】 We proposed an improved multi state constrained Kalman filter( IMSCKF) algorithm for binocular vision inertial navigation. In the initial stage,the algorithm uses sigma filter and three focus tensor constraints to complete the initialization quickly. The generated state vector is consistent with MSCKF,which can realize the seamless transition between initialization and subsequent navigation,and improve the accuracy and robustness of system state estimation. The experimental results show that the IMSCKF method proposed in this paper can maintain the position tracking error in ± 1 mm range and the angular error in ± 1°,which can improve the robustness and accuracy of binocular vision inertial navigation.更多还原