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Fixed-lag Sampling Strategies for Particle Filtering SLAM

Fixed-lag Sampling Strategies for Particle Filtering SLAM. Kris Beevers Wes Huang Rensselaer Polytechnic Institute Applied Perception, Inc. Two new Monte Carlo sampling techniques for SLAM Fixed-lag roughening: MCMC move step applied to trajectory

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Fixed-lag Sampling Strategies for Particle Filtering SLAM

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  1. Fixed-lag Sampling Strategies for Particle Filtering SLAM Kris Beevers Wes HuangRensselaer Polytechnic Institute Applied Perception, Inc. • Two new Monte Carlo sampling techniques for SLAM • Fixed-lag roughening: MCMC move step applied to trajectory • Block proposal: sample from optimal joint distribution of poses over a fixed lag • Exploits “future” information to improve past pose estimates • Results: significant consistency improvements over FastSLAM 2 NEES error for different sampling techniques

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