基于非闭合Snakes和单线激光雷达的路边检测与滤波

Road Edge Detection and Filtering Based on Unclosed Snakes and 2D LIDAR Data

提出了一种序贯路边滤波模型.在传统主动轮廓模型Snakes的基础上,探讨非闭合Snakes的求解方法,并首次利用非闭合Snakes模型对单线激光雷达的路边检测结果进行平滑和滤波.详细讨论了道路以及障碍物的几种模型,基于这些模型可以快速准确地从单帧雷达数据中提取出路边.研究了应用于路边滤波的非闭合Snakes模型的建立、Snakes的初始化以及如何利用雷达数据构造Snakes的图像力等问题.在自主车导航实验中的应用证明了本文方法用于路边滤波时可以有效减少路边检测时的错误和误差,改善路边的连续性,滤波后的路边更加接近真实路边位置.

A filtering model of sequential road edges is proposed.The solution of unclosed snakes is discussed based on traditional active contour models,the snakes.Then,it is applied to the smoothing and filtering of road edges detected from 2D LIDAR（LIght Detection And Ranging） data.Several models to depict roads and obstacles are discussed in detail.Based on these models,road edges can be acquired from a single scan 2D LIDAR data quickly and efficiently.Some problems are investigated,such as building and initialization of unclosed snakes model in the road edge filtering scenario,and acquisition of image forces of snakes from LIDAR data.The proposed algorithm is implemented on our ALV（autonomous land vehicle）,and the navigation experiments demonstrate that our approach can efficiently reduce the mistakes and errors as well as improve the continuity of road edges.The resulted road edges thus are more faithful to the truth.