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. ROBOT, 2005, 27(4): 296-300..
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.
[1] Crisman J D, Thorpe C E. Color vision for road following[A]. Proceedings of the International Society for Optical Engineering Conference on Mobile Robots III[C]. Boston, MA: 1988, vol 1007. 175-184. [2] Crisman J D, Thorpe C E. A color vision system that tracks roads and intersections[J]. IEEE Transactions on Robotics and Automation,1993, 9(1):49-58. [3] Mirmehdi M, Petrou M. Segmentation of color textures [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(2): 142-159. [4] Knight J, Reid I. Active visual alignment of a mobile stereo camera platform[A]. Proceedings of the IEEE International Conference on Robotics and Automation [C]. San Francisco, CA, USA: IEEE,2000, vol. 4. 3203-3208. [5] Moreno M A, G6mez-Ramirez E, Yu W, et al. Visual robot kinematics based on stereo vision[EB/OL]. in http://www. ci. ulsa. mx/～mmoreno/projects/3DVisual. PDF, 2001. [6] Davison A J. Mobile Robot Navigation Using Active Vision [D].London: University of Oxford, 1999. [7] 吴东晖.智能移动机器人的视觉导航技术[D].杭州:浙江大学,2001.
