Interacting multiple model monocular SLAM

— Recent work has demonstrated the benefits of adopting a fully probabilistic SLAM approach in sequential motion and structure estimation from an image sequence. Unlike standard Structure from Motion (SFM) methods, this ‘monocular SLAM’ approach is able to achieve drift-free estimation with high frame-rate real-time operation, particularly benefitting from highly efficient active feature search, map management and mismatch rejection. A consistent thread in this research on real-time monocular SLAM has been to reduce the assumptions required. In this paper we move towards the logical conclusion of this direction by implementing a fully Bayesian Interacting Multiple Models (IMM) framework which can switch automatically between parameter sets in a dimensionless formulation of monocular SLAM. Remarkably, our approach of full sequential probability propagation means that there is no need for penalty terms to achieve the Occam property of favouring simpler models — this arises aut...

• Type: Conference
• Year: 2008
• Where: ICRA
• Authors: Javier Civera, Andrew J. Davison, J. M. M. Montiel
• Keywords: ICRA 2008, Monocular Slam, Probabilistic Slam Approach, Real-time Monocular Slam, Robotics