Evolutionary computing and particle filtering: a hardware-based motion estimation system

Rodríguez, Alfonso and Moreno González, Félix Antonio (2015). Evolutionary computing and particle filtering: a hardware-based motion estimation system. "IEEE Transactions on Computers", v. 64 (n. 11); pp. 3140-3152. ISSN 0018-9340. https://doi.org/10.1109/TC.2015.2401015.

Description

Title: Evolutionary computing and particle filtering: a hardware-based motion estimation system
Author/s:
  • Rodríguez, Alfonso
  • Moreno González, Félix Antonio
Item Type: Article
Título de Revista/Publicación: IEEE Transactions on Computers
Date: 2015
ISSN: 0018-9340
Volume: 64
Subjects:
Freetext Keywords: Embedded systems, evolutionary computing, FPGAs, particle filtering
Faculty: Centro de Electrónica Industrial (CEI) (UPM)
Department: Automática, Ingeniería Eléctrica y Electrónica e Informática Industrial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Particle filters constitute themselves a highly powerful estimation tool, especially when dealing with non-linear non-Gaussian systems. However, traditional approaches present several limitations, which reduce significantly their performance. Evolutionary algorithms, and more specifically their optimization capabilities, may be used in order to overcome particle-filtering weaknesses. In this paper, a novel FPGA-based particle filter that takes advantage of evolutionary computation in order to estimate motion patterns is presented. The evolutionary algorithm, which has been included inside the resampling stage, mitigates the known sample impoverishment phenomenon, very common in particle-filtering systems. In addition, a hybrid mutation technique using two different mutation operators, each of them with a specific purpose, is proposed in order to enhance estimation results and make a more robust system. Moreover, implementing the proposed Evolutionary Particle Filter as a hardware accelerator has led to faster processing times than different software implementations of the same algorithm.

More information

Item ID: 41052
DC Identifier: http://oa.upm.es/41052/
OAI Identifier: oai:oa.upm.es:41052
DOI: 10.1109/TC.2015.2401015
Official URL: http://ieeexplore.ieee.org/document/7035029/
Deposited by: Memoria Investigacion
Deposited on: 03 Apr 2017 18:01
Last Modified: 03 Apr 2017 18:01
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