2D Particle Filter Accelerator for Mobile Robot Indoor Localization and Pose Estimation
Omer Tariq,
Dongsoo Han
Abstract:Particle filtering is a reliable Monte Carlo algorithm for estimating the state of a system in modeling nonlinear, non-gaussian elements for estimation and tracking applications in various fields, including robotics, navigation, and computer vision. However, particle filtering can be computationally expensive, particularly in high-dimensional state spaces, and can be a bottleneck for real-time applications due to high memory consumption. This paper proposes a particle filter accelerator that employs a cellular… Show more
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