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2023 Fiscal Year Final Research Report

The realization of next-generation SLAM technique based on self-diagnosis map: maintenance-free SLAM

Research Project

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Project/Area Number 20K12008
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Review Section Basic Section 61050:Intelligent robotics-related
Research InstitutionUniversity of Fukui

Principal Investigator

tanaka kanji  福井大学, 学術研究院工学系部門, 准教授 (30325899)

Project Period (FY) 2020-04-01 – 2024-03-31
Keywords移動ロボット / SLAM / 故障診断 / 変化検出 / 自己位置推定 / 地図生成
Outline of Final Research Achievements

We have researched and developed a new SLAM (Simultaneous Localization and Mapping) technology equipped with self-diagnosis functions, aiming to realize intelligent mobile robots capable of long-term operations, such as robot cars and patrol robots. Specifically, our goal was to apply fault diagnosis techniques, which have been developed over many years in the field of machine learning, to the SLAM domain. We conducted research, development, and performance verification of this new real-world information processing technology.

Free Research Field

SLAM

Academic Significance and Societal Importance of the Research Achievements

ロボットカーやパトロールロボットのように、長期間に渡り活動することのできる知能移動ロボットの実現に向けて、自己診断機能を有する、新しいSLAM(自己位置と地図の同時推定)技術を研究開発した。具体的には、機械学習分野において長年に渡り発展してきた故障診断技術を、SLAM分野に応用することを目的とし、新たな実世界情報処理技術の研究開発・性能検証を行った。本研究の成果は、審査の厳しい国際会議プロシーティングや雑誌に掲載された。

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Published: 2025-01-30  

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