A Biologically-Inspired Global Localization System for Mobile Robots Using LiDAR Sensor

Genghang Zhuang, Carlo Cagnetta, Zhenshan Bing, Hu Cao, Xinyi Li, Kai Huang, Alois Knoll

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Localization in the environment is an essential navigational capability for animals and indoor robotic vehicles. In indoor environments, it is still challenging to perfectly solve the global localization problem using probabilistic methods. However, animals are able to instinctively localize themselves with much less effort. Therefore, an intriguing and promising approach is to seek biological inspiration from animals. In this paper, we present a biologically-inspired global localization system using a LiDAR sensor that utilizes a hippocampal model and a landmark-based relocalization approach. The experiment results show that the proposed method is competitive with Monte Carlo Localization, and the results demonstrate the high accuracy, applicability, and reliability of the proposed biologically-inspired localization system in various localization scenarios.

Original languageEnglish
Title of host publication2022 IEEE Intelligent Vehicles Symposium, IV 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages984-990
Number of pages7
ISBN (Electronic)9781665488211
DOIs
StatePublished - 2022
Event2022 IEEE Intelligent Vehicles Symposium, IV 2022 - Aachen, Germany
Duration: 5 Jun 20229 Jun 2022

Publication series

NameIEEE Intelligent Vehicles Symposium, Proceedings
Volume2022-June

Conference

Conference2022 IEEE Intelligent Vehicles Symposium, IV 2022
Country/TerritoryGermany
CityAachen
Period5/06/229/06/22

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