中文摘要：

为解决工厂或农业非线性光照环境下视觉导航算法鲁棒性和实时性差的问题,提出基于主动轮廓模型的导航标识线检测与跟踪算法。首先用多项式曲线模型描述单向标识线,导航问题等价为计算多项式曲线参数;然后依据标识线颜色和边缘等特征,给出关于多项式曲线的主动轮廓模型的内、外部能量函数;最后将能量函数简化为非线性最小二乘问题,应用高斯牛顿法和Armijo-Goldstein不精确一维搜索方法求解曲线最优参数。采用自制视频和自主小车测试算法,结果表明：该算法对非线性光照条件下直线和弯曲标识线的导航正确率为98.96%,运算时间为40.18 ms。试验验证了该算法的鲁棒性和实时性。

英文摘要：

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.