吴树锋, 傅卫平, 杨静, 李德信, 谢敬. 基于核心区域信息和经验知识的道路理解算法[J]. 机器人, 2005, 27(4): 296-300.
引用本文: 吴树锋, 傅卫平, 杨静, 李德信, 谢敬. 基于核心区域信息和经验知识的道路理解算法[J]. 机器人, 2005, 27(4): 296-300.
WU Shu-feng, FU Wei-ping, YANG Jing, LI De-xin, XIE Jing. A Road Understanding Algorithm Based on Kernel Region Information and General Knowledge[J]. ROBOT, 2005, 27(4): 296-300.
Citation: WU Shu-feng, FU Wei-ping, YANG Jing, LI De-xin, XIE Jing. A Road Understanding Algorithm Based on Kernel Region Information and General Knowledge[J]. ROBOT, 2005, 27(4): 296-300.

基于核心区域信息和经验知识的道路理解算法

A Road Understanding Algorithm Based on Kernel Region Information and General Knowledge

  • 摘要: 针对户外移动机器人视觉导航,提出了一种基于核心区域和经验知识的道路理解算法.本算法引入核心区域信息融合经验知识加强道路理解的准确性,引入时间影响因子增强道路理解系统的鲁棒性.根据模糊原理对于不同的区域赋予相应的道路颜色隶属度,为安全度要求不同的机器人导航提供更为精确的信息.算法设计中通过优化算法,兼顾了导航的实时性要求.

     

    Abstract: Aiming at visual navigation of mobile robots in outdoor environment, a road understanding algorithm based on the kernel region information and general knowledge is presented. In this algorithm, kernel region information and general knowledge are used to improve the accuracy of road understanding, and time-concerning impact factor is used to improve the robustness of the algorithm. Based on fuzzy theory, the degrees of membership of road color are allocated to each sub-region, so more precise information can be offered for robot navigation with different degrees of safety. This algorithm is well designed with optimization algorithm, taking the real-timeness of navigation into consideration.

     

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