Research on Application of Monarch Butterfly Optimization Particle Filter in SLAM

Authors

Zhiqiang Chen, College of Automation and Electronic Engineering, Qingdao University of Science and Technology, Qingdao 266061, ChinaFollow
Menglong Cao, College of Automation and Electronic Engineering, Qingdao University of Science and Technology, Qingdao 266061, China
Wenbin Zhao, College of Automation and Electronic Engineering, Qingdao University of Science and Technology, Qingdao 266061, China

Abstract

In traditional particle filter resampling, weight degradation and loss of particle diversity are prone to occur, which leads to the decrease in filtering accuracy and result in inaccurate robot positioning and inaccurate mapping. An optimized particle filter algorithm based on the improved monarch butterfly algorithm is proposed.The algorithm replaces the particle individual with the monarch butterfly individual, and integrates the migration operator and adjustment operator in the monarch butterfly algorithm into the particle filter algorithm. The adaptive genetic parameters are introduced to the iterative update process of the monarch butterfly, and the linear combination optimization resampling method is used to improve the particle diversity during particle filter resampling.It is verified by simulation experiments that compared with the original algorithm, the proposed particle filter algorithm based on the improved monarch butterfly algorithm improves the prediction accuracy and running speed by more than 29.7% and 5.6% respectively. It can also improve the mapping accuracy by more than 40% and the running speed by 10.5% when applied to the robot simultaneous localization and mapping.

Recommended Citation

Chen, Zhiqiang; Cao, Menglong; and Zhao, Wenbin (2023) "Research on Application of Monarch Butterfly Optimization Particle Filter in SLAM," Journal of System Simulation: Vol. 35: Iss. 6, Article 18.
DOI: 10.16182/j.issn1004731x.joss.22-0090
Available at: https://dc-china-simulation.researchcommons.org/journal/vol35/iss6/18

First Page

1351

Revised Date

2022-03-21

DOI Link

http://dx.doi.org/10.16182/j.issn1004731x.joss.22-0090

Last Page

1361

CLC

TP242

Recommended Citation

Zhiqiang Chen, Menglong Cao, Wenbin Zhao. Research on Application of Monarch Butterfly Optimization Particle Filter in SLAM[J]. Journal of System Simulation, 2023, 35(6): 1351-1361.

DOI

10.16182/j.issn1004731x.joss.22-0090