Robotics: Science and Systems IV

HyPE: Hybrid Particle-Element Approach for Recursive Bayesian Searching and Tracking

Benjamin Lavis, Tomonari Furukawa

Abstract: This paper presents a hybrid particle-element approach, HyPE, suitable for recursive Bayesian searching-and-tracking (SAT). The concept here of a hybrid, which is a synthesis of two RBE methods to represent and maintain the belief about all states in the system, is distinct from the concept behind so call mixed approaches which use different representaitons for different states. HyPE eliminates the need for expensive numerical integration in the prediction stage and allows space reconfiguration, via remeshing, at minimal computational cost. Numerical examples show the efficacy of the approach, and show superior performance to both the particle filter and the element-based method in SAT scenarios with limited iteration time.

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Bibtex:

@INPROCEEDINGS{Lavis-RSS08,
    AUTHOR    = {Benjamin Lavis, Tomonari Furukawa},
    TITLE     = {{H}y{PE}: Hybrid Particle-Element Approach for Recursive Bayesian Searching and Tracking},
    BOOKTITLE = {Proceedings of Robotics: Science and Systems IV},
    YEAR      = {2008},
    ADDRESS   = {Zurich, Switzerland},
    MONTH     = {June},
    DOI       = {10.15607/RSS.2008.IV.018} 
}