A now variant of nonparametric belief propagation for self-localization

Hadi Noureddine Al Moussawi (1, 2) , Nicolas Gresset (3) , Damien Castelain (3) , Ramesh Pyndiah (4, 1)

1 SC - Département Signal et Communications
2 Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (UMR 3192)
3 Mitsubishi Electric ITE-TCL (Entreprise)
4 Lab-STICC_TB_CACS_COM

We consider the problem of relative self-localization of a network of fixed communicating devices that evaluate range measurements between each other. The solution is obtained in two stages: First, a new variant of the Nonparametric Belief Propagation algorithm is used for estimating the beliefs. This variant is based on a Monte-Carlo integration with rejection sampling where a delimited space region is determined for each node in order to reduce the rejection ratio. Then, a new algorithm based on estimation in discrete states space is proposed for solving the flipping ambiguities resulting from the lack of measurements. This solution has the advantage of reducing the amount of communicating particles and the computation cost.

Mots clés: Belief propagation; Clustering algorithms; Coordinate measuring machines; Distance measurement; Distributed algorithms; Graphical models; Military computing; Sampling methods; State estimation; State-space methods

Domaines: Traitement du signal et de l'image [eess.SP]

Hadi Noureddine Al Moussawi, Nicolas Gresset, Damien Castelain, Ramesh Pyndiah. A now variant of nonparametric belief propagation for self-localization. ICT : International Conférence on Telecommunications, Apr 2010, Doha, Qatar. pp.822 - 827, ⟨10.1109/ICTEL.2010.5478820⟩. ⟨hal-00609311⟩