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Multiswarm Particle Filter for vision based SLAM
2009
2009 IEEE/RSJ International Conference on Intelligent Robots and Systems
Particle Filters have been widely used as a powerful optimization tool for nonlinear, non-Gaussian dynamic models such as Simultaneous Localization and Mapping (SLAM) and visual tracking. Particle filters, however, often suffer from particle impoverishment, which is caused by a mismatch between proposal distribution and target distribution. To solve this problem, we propose a new method to improve the efficiency of particle filters by employing the Particle Swarm Optimization (PSO), which is a
doi:10.1109/iros.2009.5354144
dblp:conf/iros/LeeL09a
fatcat:ey35djhesjbmberiovyzmgbuii