Multisensor robust localization in various environment with correlation checking test

ROBOMECH Journal

Yuki Funabora¹  Nozomu Ohashi¹  Shinji Doki¹  Kae Doki² 

[1] Department of Electrical Engineering and Computer Science, Nagoya University, 1 Furo-cho, Chikusa-ku, 464-8603, Nagoya, Japan;Department of Electrical Engineering, Aichi Institute of Technology, 1247 Yachigusa, Yakusa-cho, 470-0392, Toyota, Japan;

关键词: Localization;    Sensor fusion;    Particle filter;    Outlier rejection;   

DOI  :  10.1186/s40648-021-00190-9

来源: Springer

【 摘 要 】

Probabilistic localization based on Bayesian theory has been researched as a sensor fusion method to improve the robustness of localization. Pieces of position information, generated by sensors’ observation models with consideration for noises, are fused according to Bayesian theory. However, having large noises not considered in their observation models, the sensors output erroneous position information; thus, the fusion result has a significant error, even when the other sensors output correct ones. In this research, we have proposed a sensor fusion system with a relative correlation checking test to realize robust localization. Pieces of erroneous position information, biased against others and having a negative correlation with others, are detected and excluded in our proposed system by checking their correlation between all of them. The purpose of this paper is to evaluate the robustness of our fusion system by conducting recursive localization experiments in various environments.

【 授权许可】

CC BY