LiDARを用いた生物に着想を得た移動ロボットのグローバル自己位置推定システム
A Biologically Inspired Global Localization System for Mobile Robots Using LiDAR Sensor
海馬モデルとランドマークに基づく再位置推定を組み合わせ、LiDARのみで移動ロボットのグローバル自己位置推定を行う生物模倣手法を提案し、モンテカルロ位置推定と同等以上の精度・信頼性を示した。
著者: Genghang Zhuang, Carlo Cagnetta, Zhenshan Bing, Kai Huang, Alois Knoll
分類: cs.RO
原文アブストラクト
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.
