An Optimal Control Approach to Particle Filtering on Lie Groups

We study the filtering problem over a Lie group that plays an important role in robotics and aerospace applications. present new particle algorithm based on stochastic control. In particular, our is duality between smoothing optimal Leveraging this duality, we reformulate into control problem, by approximately solving it (using, e.g., iLQR) establish superior proposal for smoothing. Combining with suitably designed sliding window mechanism, obtain suffers less from sample degeneracy compared existing methods. The efficacy of illustrated SO(3) satellite attitude estimation.