论文标题
从LiDAR迫在眉睫的估计
Estimation of Looming from LiDAR
论文作者
论文摘要
迫在眉睫，传统上被定义为观察者视网膜中对象的相对扩展，是对威胁感知感知的基本视觉提示，可用于完成无碰撞导航。迫在眉睫的提示的测量不仅限于视觉，也可以从诸如LIDAR（光检测和范围）之类的范围传感器中获得。在本文中，我们提供了两种处理原始LIDAR数据以估计迫在眉睫的提示的方法。使用迫在眉睫的值，我们展示了如何获得避免碰撞任务的威胁区域。这些方法足够通用，适合任何六度运动运动，并且可以实时实现，而无需进行良好的匹配，点云注册，对象分类或对象分割。使用KITTI数据集的定量结果显示了方法的优点和局限性。
Looming, traditionally defined as the relative expansion of objects in the observer's retina, is a fundamental visual cue for perception of threat and can be used to accomplish collision free navigation. The measurement of the looming cue is not only limited to vision, and can also be obtained from range sensors like LiDAR (Light Detection and Ranging). In this article we present two methods that process raw LiDAR data to estimate the looming cue. Using looming values we show how to obtain threat zones for collision avoidance tasks. The methods are general enough to be suitable for any six-degree-of-freedom motion and can be implemented in real-time without the need for fine matching, point-cloud registration, object classification or object segmentation. Quantitative results using the KITTI dataset shows advantages and limitations of the methods.
