— We describe two new sampling strategies for Rao-Blackwellized particle filtering SLAM. The strategies, called fixed-lag roughening and the block proposal distribution, both e...
Abstract— Particle Filters have been widely used as a powerful optimization tool for nonlinear, non-Gaussian dynamic models such as Simultaneous Localization and Mapping (SLAM) a...
The implementation of a particle filter (PF) for vision-based bearing-only simultaneous localization and mapping (SLAM) of a mobile robot in an unstructured indoor environment is p...
We propose a novel geometric Rao-Blackwellized particle filtering framework for monocular SLAM with locally planar landmarks. We represent the states for the camera pose and the la...
Junghyun Kwon (Seoul National University) and Kyou...
Abstract. In this paper we discuss new adaptive proposal strategies for sequential Monte Carlo algorithms--also known as particle filters--relying on new criteria evaluating the qu...