Analysis of resampling process for the particle depletion problem in FastSLAM

Proceedings - IEEE International Workshop on Robot and Human Interactive Communication

Volumn , Issue , 2007, Pages 200-205

  Kwak, Nosan ^a,b   Kim, In Kyu ^a   Lee, Heon Cheol ^a   Lee, Beom Hee ^a,b  

^a Seoul National University   (South Korea)

^b IEEE

Author keywords

FastSLAM; Particle depletion; Particle filter; Resampling

Indexed keywords

ARSENIC COMPOUNDS; COMPUTATIONAL METHODS; COMPUTER SIMULATION; DIESEL ENGINES; ERROR ANALYSIS; GENETIC ALGORITHMS; METROPOLITAN AREA NETWORKS; REVERSE OSMOSIS; ROBOTICS; ROBOTS; SAMPLING; SIGNAL FILTERING AND PREDICTION; STANDARDS; UNCERTAINTY ANALYSIS;

FASTSLAM; INTERACTIVE COMMUNICATIONS; INTERNATIONAL CONFERENCES; PARTICLE DEPLETION PROBLEM; PERFORMANCE MEASURE (PF); RE SAMPLING; RESAMPLING ALGORITHMS; ROOT MEAN-SQUARE ERROR (RMSE); SAMPLE SIZES; SIMULATION RESULTS; SIMULTANEOUS LOCALIZATION AND MAPPING (SLAM); SYSTEMATIC (CO);

PARTICLE SIZE ANALYSIS;

EID: 48749110685     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ROMAN.2007.4415080     Document Type: Conference Paper

References (15)

1. M. Montemerlo, "FastSLAM: A factored solution to the simultaneous localization and mapping problem with unknown data assocation," Ph.D. thesis, Carnegie Mellon Univeristy, 2003.
2. P. Newman, J. Leonard, J. Neira, and J. Tardos, "Explore and return: Experimental validation of real-time concurrent mapping and localization." Proceedings of the IEEE International Conference on Robotics and Automation, 2002.
3. A. Doucet, N. de Freitas, K. Murphy, and S. Russell, "Rao- Blackwellized particle filtering for dynamic Bayesian networks," Proceedings of Conference on Uncertainty in Artificial Intelligence, 2000.
4. K. Murphy, "Bayesian map learning in dynamic environments," Advances in Neural Information Processing Systems. MIT Press, 1999.
5. M. Montemerlo and S. Thrun S, "Simultaneous localization and mapping with unknown data association using FastSLAM," IEEE International Conference on Robotics and Automation, pp. 1985-1991, 2003.
6. S. Thrun, W. Burgard, and D. Fox, "Probabilistic robotics," MIT Press, Cambridge, 2005.
7. T. Bailey, J. Nieto, and E. Nebot, "Consistency of the FastSLAM algorithm," IEEE International Conference on Robotics and Automation. pp. 424-429, 2006.
8. A. Kong, J. S. Liu, and W. H. Wong, "Sequential imputations and Bayesian missing data problems," Journal of the American Statistical Association, vol. 89, pp. 278-288, 1994.
9. M. Montemerlo, S. Thrun, D. Koller, and B. Wegbreit, "Fast-SLAM2.0: An improved particle filtering algorithm for simultaneous localization and mapping that provably converges," Proceeding of the International Joint Conference on Artificial Inteligence., pp. 1151-1156, 2003.
10. M. Bolić, P. M. Djurić, and S. Hong, "Resampling algorithms for particle filters: a computational complexity perspective," Journal on Applied Signal Processing, no. 15, pp. 2267-2277, 2004.
11. M. Bolić, P. M. Djurić, and S. Hong, "New resampling algorithms for particle filters," IEEE International Conference on Robotics and Automation, pp.424-429, 2003.
12. J. E. Baker, "Adaptive selection methods for genetic algorithms," International Conference on Genetic Algorithms and Their Applications, pp. 101-111, 1985.
13. R. Merwe, A. Doucet, N. de Freitas, and E. Wan, "The unscented particle filter," Technical Report CUED/F INFENG/TR 380, Cambridge University Engineering Department, 2000.
14. D. Whitely, "The genitor algorithm and selection pressure: why rank-based allocation of reproductive trial is best," Proceedings of 3rd Internationall Conference on Genetic Algorithms and Their Applications, pp. 116-121, 1989.
15. J. S. Liu, "Metropolized independent sampling with comparison to rejection sampling and importance sampling," Statistics and Computing, 6:113-119, 1996.