论文标题
在谎言组上进行粒子过滤的最佳控制方法
An optimal control approach to particle filtering on Lie groups
论文作者
论文摘要
我们研究了一个在机器人技术和航空应用中起重要作用的谎言组的过滤问题。我们提出了一种基于随机控制的新粒子过滤算法。特别是，我们的算法基于平滑和最佳控制之间的双重性。 Leveraging this duality, we reformulate the smoothing problem into an optimal control problem, and by approximately solving it (using, e.g., iLQR) we establish a superior proposal for particle smoothing.与现有方法相比，将其与适当设计的滑动窗口机构结合起来，获得了一种粒子过滤算法，该算法较少。通过过滤问题（3）来估算算法的效果，以说明了我们的算法的功效。
We study the filtering problem over a Lie group that plays an important role in robotics and aerospace applications. We present a new particle filtering algorithm based on stochastic control. In particular, our algorithm is based on a duality between smoothing and optimal control. Leveraging this duality, we reformulate the smoothing problem into an optimal control problem, and by approximately solving it (using, e.g., iLQR) we establish a superior proposal for particle smoothing. Combining it with a suitably designed sliding window mechanism, we obtain a particle filtering algorithm that suffers less from sample degeneracy compared with existing methods. The efficacy of our algorithm is illustrated by a filtering problem over SO(3) for satellite attitude estimation.
