Practical Implementation of Visual Navigation Based on Semantic Segmentation for Human-Centric Environments

This study focuses on visual navigation methods for autonomous mobile robots based on semantic segmentation results. The challenge is to perform the expected actions without being affected by the presence of pedestrians. Therefore, we implemented a semantics-based localization method that is not aff...

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Bibliographic Details
Published inJournal of robotics and mechatronics Vol. 35; no. 6; pp. 1419 - 1434
Main Authors Adachi, Miho, Honda, Kazufumi, Xue, Junfeng, Sudo, Hiroaki, Ueda, Yuriko, Yuda, Yuki, Wada, Marin, Miyamoto, Ryusuke
Format Journal Article
LanguageEnglish
Published Tokyo Fuji Technology Press Co. Ltd 01.12.2023
Subjects
Accuracy
Cameras
Computer science
Deep learning
Localization
Localization method
Methods
Navigation
Pedestrians
Roads & highways
Robotics
Robots
Semantic segmentation
Semantics
Sensors
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Summary:This study focuses on visual navigation methods for autonomous mobile robots based on semantic segmentation results. The challenge is to perform the expected actions without being affected by the presence of pedestrians. Therefore, we implemented a semantics-based localization method that is not affected by dynamic obstacles and a direction change method at intersections that functions even with coarse-grain localization results. The proposed method was evaluated through driving experiments in the Tsukuba Challenge 2022, where a 290 m run including 10 intersections was achieved in the confirmation run section.
ISSN:0915-3942
1883-8049
DOI:10.20965/jrm.2023.p1419