输出等方差的视觉同时定位与映射观测器设计
An Observer Design for Visual Simultaneous Localisation and Mapping with Output Equivariance
摘要：
视觉同步定位和地图（VSLAM）是小型嵌入式机器人系统（如飞行器）的关键使能技术。等变滤波器和观测器设计的最新进展为嵌入式系统应用提供了具有低存储器和计算要求的新一代高鲁棒性算法的潜力。本文研究了观测器设计的对称群在以前的工作中提出的作者，在逆深度测量的情况下。利用这种对称性导致一个简单的完全非线性梯度观测器几乎具有全局渐近和局部指数稳定性。仿真实验验证了观测器的设计，并表明，所提出的观测器实现了类似的精度，广泛使用的扩展卡尔曼滤波器的处理时间显着增益（线性与二次边界相对于地标的数量）和定性的鲁棒性的改善。
英文摘要：
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.
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