Tracking multiple moving targets with a mobile robot using particle filters and statistical data association

Proceedings - IEEE International Conference on Robotics and Automation

Volumn 2, Issue , 2001, Pages 1665-1670

  Schulz, D ^a   Burgard, W ^a   Fox, D ^a   Cremers, A B ^a  

^a UNIVERSITY OF BONN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

FEATURE EXTRACTION; OBJECT RECOGNITION; PROBABILITY; STATISTICAL METHODS; TRAJECTORIES;

PARTICLE FILTERS;

MOBILE ROBOTS;

EID: 0034860928     PISSN: 10504729     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (14)

1. A probabilistic framework for matching temporal trajectories: Condensation-based recognition of gestures and expressions
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3. An efficient implementation of reids multiple hypothesis tracking algorithm and its evaluation for the purpose of visual tracking
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5. A novel approach to nonlinear/non-Gaussian Bayesian state estimation
6. An experimental comparison of localization methods
7. Contour tracking by stochastic propagation of conditional density
8. Stochastic simulation algorithms for dynamic probabilistic networks
9. Robot pose estimation in unknown environments by matching 2d range scans
10. A probabilistic exclusion principle for tracking multiple objects
11. Using the condensation algorithm to implement tracking for mobile robots
12. High resolution maps from wide angle sonar
13. Filtering via simulation: Auxiliary panicle filters