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

DOI Web Site Web Site 参考文献39件
  • Adachi Miho
    Department of Computer Science, Graduate School of Science and Technology, Meiji University
  • Honda Kazufumi
    Department of Computer Science, Graduate School of Science and Technology, Meiji University
  • Xue Junfeng
    Department of Computer Science, Graduate School of Science and Technology, Meiji University
  • Sudo Hiroaki
    Department of Computer Science, Graduate School of Science and Technology, Meiji University
  • Ueda Yuriko
    Department of Computer Science, Graduate School of Science and Technology, Meiji University
  • Yuda Yuki
    Department of Computer Science, Graduate School of Science and Technology, Meiji University
  • Wada Marin
    Department of Computer Science, Graduate School of Science and Technology, Meiji University
  • Miyamoto Ryusuke
    Department of Computer Science, School of Science and Technology, Meiji University

この論文をさがす

抄録

<p>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.</p>

収録刊行物

参考文献 (39)*注記

もっと見る

キーワード

詳細情報 詳細情報について

問題の指摘

ページトップへ