Positioning Method of Four-Wheel Drive Robots Based on Multi-Sensor Fusion and Improved Adaptive Monte Carlo Algorithm

Li Beijun, Zhang Yi, Shi Zhiqiang

2024

Abstract

This paper proposes an improved method for the traditional Adaptive Monte Carlo Localization (AMCL) algorithm, addressing issues such as long computation time and poor real-time updating ability. In the sampling phase, this method improves the traditional AMCL algorithm by using a parallel approach of stratified low variance sampling and KLD sampling. Additionally, the improved AMCL algorithm is integrated into the ROS-based SLAM package to reduce robot positioning errors and improve map accuracy in unknown environments during simultaneous localization and mapping. It is also integrated into the ROS-based navigation package to enhance robot’s localization accuracy in known environments and optimize both global and local path planning functionality when loading pre-built maps.

Paper Citation

in Harvard Style

Beijun L., Yi Z. and Zhiqiang S. (2024). Positioning Method of Four-Wheel Drive Robots Based on Multi-Sensor Fusion and Improved Adaptive Monte Carlo Algorithm. In Proceedings of the 1st International Conference on Data Mining, E-Learning, and Information Systems - Volume 1: DMEIS; ISBN 978-989-758-715-3, SciTePress, pages 10-16. DOI: 10.5220/0012875700004536

in Bibtex Style

@conference{dmeis24,
author={Li Beijun and Zhang Yi and Shi Zhiqiang},
title={Positioning Method of Four-Wheel Drive Robots Based on Multi-Sensor Fusion and Improved Adaptive Monte Carlo Algorithm},
booktitle={Proceedings of the 1st International Conference on Data Mining, E-Learning, and Information Systems - Volume 1: DMEIS},
year={2024},
pages={10-16},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012875700004536},
isbn={978-989-758-715-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Data Mining, E-Learning, and Information Systems - Volume 1: DMEIS
TI - Positioning Method of Four-Wheel Drive Robots Based on Multi-Sensor Fusion and Improved Adaptive Monte Carlo Algorithm
SN - 978-989-758-715-3
AU - Beijun L.
AU - Yi Z.
AU - Zhiqiang S.
PY - 2024
SP - 10
EP - 16
DO - 10.5220/0012875700004536
PB - SciTePress