Monocular SLAM using a rao-blackwellised particle filter with exhaustive pose space search

This paper presents a method of 3-D SLAM using a single camera. We utilize a Rao-Blackwellised particle filter (RBPF) to deal with a large number of landmarks. A difficulty in monocular SLAM is robustness to outliers and noise, which may cause false estimates especially under short baseline conditions. We propose an exhaustive pose-space search that finds all the plausible hypotheses efficiently using epipolar geometry. The obtained pose hypotheses are refined by the RBPF. Simulations and experiments show that the proposed method successfully performed 3-D SLAM with a small number of particles.