海洋環境におけるUSVの障害物検出と追跡
USV Obstacles Detection and Tracking in Marine Environments
無人水上艇（USV）向けに、カメラとLiDARのセンサフュージョンおよびLiDAR単独の障害物検出・追跡手法を比較し、両者の利点を統合したハイブリッド手法を提案した論文。
詳しい要約
1. どんなもの？
2. 先行研究と比べてどこがすごい？
3. 技術・手法の肝は？
4. どうやって有効だと検証した？
5. 議論はある？
6. 次に読むべき論文は？
※ AIが要旨から生成した要約です。正確性は原文をご確認ください。
著者: Yara AlaaEldin, Enrico Simetti, Francesca Odone
分類: cs.RO, cs.AI
原文アブストラクト
Developing a robust and effective obstacle detection and tracking system for Unmanned Surface Vehicle (USV) at marine environments is a challenging task. Research efforts have been made in this area during the past years by GRAAL lab at the university of Genova that resulted in a methodology for detecting and tracking obstacles on the image plane and, then, locating them in the 3D LiDAR point cloud. In this work, we continue on the developed system by, firstly, evaluating its performance on recently published marine datasets. Then, we integrate the different blocks of the system on ROS platform where we could test it in real-time on synchronized LiDAR and camera data collected in various marine conditions available in the MIT marine datasets. We present a thorough experimental analysis of the results obtained using two approaches; one that uses sensor fusion between the camera and LiDAR to detect and track the obstacles and the other uses only the LiDAR point cloud for the detection and tracking. In the end, we propose a hybrid approach that merges the advantages of both approaches to build an informative obstacles map of the surrounding environment to the USV.
関連論文
- 空中ロボット搭載センサフュージョンによるリアルタイムガラス検出と再投影知覚/センサフュージョン
