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A Multi-modality Sensor System for Unmanned Surface Vehicle

机译：用于无人曲面车辆的多模态传感器系统

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摘要

The onboard multi-modality sensors significantly expand perception ability of Unmanned Surface Vehicle (USV). This paper aims to fully utilize various onboard sensors and enhance USV's object detection performance. We solve several unique challenges for application of USV multi-modality sensor system in the complex maritime environment. By utilizing deep learning networks, we achieved accurate object detection on water surface. We firstly propose a multi-modality sensor calibration method. The network fuses RGB images with multiple point clouds from various sensors. The well-calibrated image and point cloud are input to our deep object detection network, and conduct 3D detection through proposal generation network and object detection network. Meanwhile, we made a series of improvements to the system framework, which accelerate the detection procedures. We collected two datasets from the real-world offshore field and the simulation scenes respectively. The experiments on both datasets showed valid calibration results. On this basis, our object detection network achieves better accuracy than other methods. The performance of the proposed multi-modality sensor system meets the application requirement of our prototype USV platform.
机译：板载多模态传感器显着扩展无人面车辆（USV）的感知能力。本文旨在充分利用各种板载传感器，提高USV的物体检测性能。我们解决了在复杂的海洋环境中应用USV多模态传感器系统的几个独特挑战。通过利用深度学习网络，我们在水面上实现了精确的物体检测。我们首先提出了一种多模态传感器校准方法。网络使RGB图像融合来自各种传感器的多个点云。校准的图像和点云被输入到我们的深度对象检测网络，并通过提案生成网络和对象检测网络进行3D检测。同时，我们对系统框架进行了一系列改进，加速了检测程序。我们分别从现实世界的海上场和仿真场景中收集了两个数据集。两个数据集的实验显示有效的校准结果。在此基础上，我们的物体检测网络能够比其他方法更好地实现精度。所提出的多模态传感器系统的性能符合我们原型USV平台的应用要求。

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  • 来源
    《Neural processing letters》 |2020年第2期|977-992|共16页
  • 作者

    Hao Liu; Jie Nie; Yingjian Liu; Yingying Wu; Hanxing Wang; Fangchao Qu; Wei Liu; Yangyang Li;

  • 作者单位

    Department of Computer Science and Technology Ocean University of China Qingdao 266100 Shandong China National Laboratory for Marine Science and Technology (Qingdao) Qingdao 266000 Shandong China;

    Department of Computer Science and Technology Ocean University of China Qingdao 266100 Shandong China;

    Department of Computer Science and Technology Ocean University of China Qingdao 266100 Shandong China;

    Department of Computer Science and Technology Ocean University of China Qingdao 266100 Shandong China;

    Department of Computer Science and Technology Ocean University of China Qingdao 266100 Shandong China;

    Department of Computer Science and Technology Ocean University of China Qingdao 266100 Shandong China;

    Department of Computer Science and Technology Ocean University of China Qingdao 266100 Shandong China;

    Department of Computer Science and Technology Ocean University of China Qingdao 266100 Shandong China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Multi-modality sensor; Unmanned Surface Vehicle; Object detection; Sensor calibration;

    机译：多模态传感器;无人面的表面车辆;对象检测;传感器校准;

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