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

TL;DR

This paper introduces a biologically-inspired global localization system for mobile robots using LiDAR, inspired by animal navigation, demonstrating high accuracy and reliability comparable to traditional probabilistic methods.

Contribution

The paper presents a novel biologically-inspired localization approach utilizing hippocampal models and landmark re-localization with LiDAR, improving robustness and applicability.

Findings

Competitive accuracy to Monte Carlo Localization

High reliability across different scenarios

Effective biological inspiration enhances localization

Abstract

Localization in the environment is an essential navigational capability for animals and mobile robots. In the indoor environment, the global localization problem remains challenging to be perfectly solved with probabilistic methods. However, animals are able to instinctively localize themselves with much less effort. Therefore, it is intriguing and promising 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 re-localization approach. The experiment results show that the proposed method is competitive to Monte Carlo Localization, and the results demonstrate the high accuracy, applicability, and reliability of the proposed biologically-inspired localization system in different localization scenarios.