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Driving assistance system based on data fusion of multisource sensors for autonomous unmanned ground vehicles

机译：基于数据融合的自主无人机地面车辆数据融合的驾驶辅助系统

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摘要

Autonomous unmanned ground vehicle is a product of technological development. At present, it has become a trend to provide multi-view real-time environmental state for autonomous unmanned ground vehicles. And more and more object detection algorithms will be applied in autonomous driving. In the recent years, multi-sensor-based driving assistance systems have become a way to solve these problems. In this paper, we introduce a driving assistance system based on data fusion of multiple sensors for autonomous driving. On the one hand, six fisheye cameras and twelve ultrasonic radars are used to collect surround-view environmental state. On the other hand, this system uses a low-light camera and a lidar to provide forward-view environmental state. In the meantime, we design panoramic mosaic algorithm, surround-view data fusion algorithm and forward-view data fusion algorithm. Besides, object detection algorithm is used to provide forward-view detection results. This driving assistance system will advance research into autonomous unmanned ground vehicles.
机译：自主无人面的地面车辆是技术发展的产物。目前，它已成为为自主无人机地面车辆提供多视图实时环境状态的趋势。越来越多的对象检测算法将应用于自主驾驶中。近年来，基于多传感器的驾驶辅助系统已成为解决这些问题的方法。在本文中，我们介绍了一种基于多个传感器数据融合的驾驶辅助系统，用于自主驾驶。一方面，六个鱼眼相机和12个超声波雷达用于收集环绕式环境状态。另一方面，该系统使用低光相机和LIDAR来提供前瞻性环境状态。与此同时，我们设计全景马赛克算法，环绕式数据融合算法和正向数据融合算法。此外，对象检测算法用于提供正向视图检测结果。这项驾驶援助系统将推进自动无人机地面车辆的研究。

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