论文标题
基于光流的视觉电位领域用于自动驾驶
Optical Flow based Visual Potential Field for Autonomous Driving
论文作者
论文摘要
基于单眼视力的自动驾驶导航是一项具有挑战性的任务，因为缺乏足够的信息来计算道路上的物体之间的时间关系。光流是从单眼相机图像中获取时间信息的一种选择，并已广泛使用，目的是识别对象及其相对运动。这项工作建议使用稀疏光流的一系列图像生成人造电位字段，即视觉电位字段，该图像序列与梯度跟踪滑动模式控制器一起使用，以导航车辆到达目的地，而无需与障碍物相撞。车辆的角参考是在线计算的。这项工作认为，车辆不需要从地图上获得先验信息或成功导航的障碍。提出的技术在合成图像和真实图像中都进行了测试。
Monocular vision-based navigation for automated driving is a challenging task due to the lack of enough information to compute temporal relationships among objects on the road. Optical flow is an option to obtain temporal information from monocular camera images and has been used widely with the purpose of identifying objects and their relative motion. This work proposes to generate an artificial potential field, i.e. visual potential field, from a sequence of images using sparse optical flow, which is used together with a gradient tracking sliding mode controller to navigate the vehicle to destination without collision with obstacles. The angular reference for the vehicle is computed online. This work considers that the vehicle does not require to have a priori information from the map or obstacles to navigate successfully. The proposed technique is tested both in synthetic and real images.
