Cooperative simultaneous localization and tracking (CoSLAT) with reduced complexity and communication

Paper i proceeding, 2013

The recently introduced framework of cooperative simultaneous localization and tracking (CoSLAT) combines Bayesian cooperative agent self-localization with distributed target tracking. The original CoSLAT algorithm suffers from high computation and communication costs because it uses a particle-based message representation. Here, we propose an advanced hybrid particle-based and parametric message passing algorithm for CoSLAT in which both costs are significantly reduced. Simulation results show that the localization/tracking performance is not affected.