Turning at Intersections Using Virtual LiDAR Signals Obtained from a Segmentation Result

  • 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
  • Miyamoto Ryusuke
    Department of Computer Science, School of Science and Technology, Meiji University

この論文をさがす

説明

<p>We implemented a novel visual navigation method for autonomous mobile robots, which is based on the results of semantic segmentation. The novelty of this method lies in its control strategy used for a robot during road-following: the robot moves toward a target point determined through semantic information. Previous implementations of the method sometimes failed to turn at an intersection owing to a fixed value of the turning angle. To address this issue, this study proposes a novel method for turning at an intersection using a control method based on a target point, which was originally developed for road-following. Here, an intersection is modeled as consisting of multiple straight roads. Evaluation using the CARLA simulator showed that the proposed method could accurately estimate the parameters representing a virtual road composing an intersection. In addition, run experiments conducted at the Ikuta Campus of Meiji University using an actual robot confirmed that the proposed method could appropriately make turns at intersections.</p>

収録刊行物

被引用文献 (3)*注記

もっと見る

参考文献 (23)*注記

もっと見る

関連プロジェクト

もっと見る

詳細情報 詳細情報について

問題の指摘

ページトップへ