农业机械学报2017，Vol.48Issue(2)：20-26,7.DOI:10.6041/j.issn.1000-1298.2017.02.003
基于主动轮廓模型的自动导引车视觉导航
Visual Navigation for Automatic Guided Vehicles Based on Active Contour Model
摘要
Abstract
Lane detection and tracking algorithm based on active contour model was proposed to solve the poor robustness and real-time problem for vision navigation under factory or agricultural nonlinear illumination conditions.First of all,it was illustrated that navigation problem was equivalent to calculation of polynomial curve parameters,which could describe the navigation lanes.Secondly,the external energy function of active contour model was investigated,including three energy terms.The first energy term was about the Euclidean distance between lane colors and colors on one side of polynomial curve,by minimizing the first energy term could attract polynomial curve to navigation lanes.The second energy term was about the edge features,which could attract polynomial curve to lane edges.The third energy term was about the position difference of polynomial curve between adjacent frames,which could limit curve to change abruptly.Finally,the energy function was simplified to a nonlinear least squares problem,and the Gauss-Newton method as well as the Armijo-Goldstein inexact line search method were used to solve this problem.Home video and independent car were tested,the result showed that the algorithm achieved a navigation accuracy of 98.96％ for both the straight lane and bending lane under nonlinear illumination,with average processing time of 40.18 ms,and the independent car could walk along the navigation lane successfully.Experiment result showed that the algorithm was robust and real-time.关键词
自动导引车/主动轮廓模型/高斯牛顿法/视觉导航Key words
automatic guided vehicles/active contour models/Gauss-Newton method/visual navigation分类
信息技术与安全科学引用本文复制引用
林桂潮,邹湘军,张青,熊俊涛..基于主动轮廓模型的自动导引车视觉导航[J].农业机械学报,2017,48(2):20-26,7.基金项目
国家自然科学基金项目(31571568)、广州市科技计划项目(201510010140)和广东省工程中心项目(2014B090904056) （31571568）
