Fixed-lag Sampling Strategies for Particle Filtering SLAM
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Fixed-lag Sampling Strategies for Particle Filtering SLAM Kris Beevers Wes Huang Rensselaer Polytechnic Institute Applied Perception, Inc. NEES error for different sampling techniques • 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
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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 - PowerPoint PPT Presentation
Transcript of 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.
NEES error for different sampling techniques
• 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