论文标题
视觉同时定位和映射的观察者设计
An Observer Design for Visual Simultaneous Localisation and Mapping with Output Equivariance
论文作者
论文摘要
视觉同时定位和映射（VSLAM）是针对小型嵌入式机器人系统（例如航空车辆）的关键促进技术。近似滤镜和观察者设计的最新进展提供了新一代高度健壮算法的潜力，对于嵌入式系统应用，记忆力低和计算要求。本文研究了作者先前工作中提出的对称组的观察者设计，如果可用深度测量值。利用这种对称性会导致一个简单的完全非线性梯度的观察者，具有几乎全局渐近和局部指数稳定性。仿真实验验证了观察者的设计，并证明所提出的观察者的精度与广泛使用的扩展的卡尔曼滤波器具有相似的精度，并且在处理时间（线性经文相对于地标数量的数量）和鲁棒性的质量改善，具有显着的增长（线性经文相对于二次界限）。
Visual Simultaneous Localisation and Mapping (VSLAM) is a key enabling technology for small embedded robotic systems such as aerial vehicles. Recent advances in equivariant filter and observer design offer the potential of a new generation of highly robust algorithms with low memory and computation requirements for embedded system applications. This paper studies observer design on the symmetry group proposed in previous work by the authors, in the case where inverse depth measurements are available. Exploiting this symmetry leads to a simple fully non-linear gradient based observer with almost global asymptotic and local exponential stability properties. Simulation experiments verify the observer design, and demonstrate that the proposed observer achieves similar accuracy to the widely used Extended Kalman Filter with significant gains in processing time (linear verses quadratic bounds with respect to number of landmarks) and qualitative improvements in robustness.
