A Convex Formulation for Motion Estimation using Visual and Inertial Sensors
A Convex Formulation for Motion Estimation using Visual and Inertial Sensors
复制标题
使用视觉和惯性传感器进行运动估计的凸公式
DOI：
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发表时间：
2014
期刊：
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通讯作者：
Anastasios I. Mourikis
中科院分区：
文献类型：
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作者：
Mingyang Li;Anastasios I. Mourikis
大多数现有的视觉辅助惯性导航算法依赖于线性化，因此需要良好的初始状态估计来可靠地操作。在本文中，我们提出了一种方法来计算这样的估计在没有先验运动信息的情况下，通过融合惯性测量和观察自然发生的点特征提取的图像。具体来说，我们提出了一个凸最小化配方，这是作为一个近似的最佳最大后验估计。在这个公式中，惯性和视觉测量联合使用，并采用一个强大的成本函数（二元Huber）提供鲁棒性离群值。仿真和真实数据的实验结果表明，该方法优于竞争方法的显着保证金。
Most existing algorithms for vision-aided inertial navigation rely on linearization, and thus require good initial estimates of the state to operate reliably. In this paper, we present a method for computing such estimates in absence of prior motion information, by fusing the inertial measurements and observations of naturally-occurring point features extracted from images. Specifically, we propose a convex-minimization formulation, which is derived as an approximation to the optimal maximum-a-posteriori estimator. In this formulation, both the inertial and visual measurements are jointly used, and a robust cost function (bivariate Huber) is employed to provide robustness to outliers. Experimental results on both simulated and realworld data demonstrate that the proposed approach outperforms competing methods by a significant margin.