基于多层Morphin搜索树的UGV局部路径规划算法  

A Local Path Planning Algorithm for UGV Based on Multilayer Morphin Search Tree

作　　者：诸葛程晨[1] 唐振民[1] 石朝侠[1] 

机构地区：[1]南京理工大学模式识别与人工智能研究所,江苏南京210094

出　　处：《机器人》2014年第4期491-497,共7页Robot

基　　金：国家自然科学基金资助项目(91220301;61371040)

摘　　要：以地面自主车辆(UGV)为实际应用背景,提出了一种基于多层Morphin搜索树的局部路径规划算法.该算法结合车辆非完整性约束构造多层Morphin搜索树,通过模糊Q学习进行动态行为控制的学习,并以此为依据对搜索树进行评估,从而得到一条具备车辆非完整约束的平滑可跟踪路径,克服了传统Morphin算法搜索轨迹不灵活的缺点.最后,通过仿真实验以及实车实验验证了算法的有效性和正确性.Aiming at the application of unmanned ground vehicle （UGV）, a local path planning algorithm based on multi- layer Morphin search tree is proposed. By considering the nonholonomic constraints of vehicle, a multilayer Morphin search tree is constructed. Then control of dynamic behavior is learned by fuzzy Q-learning, as a basis for the evaluation of search tree to get a smooth and trackable trajectory with nonholonomic constraints of vehicle. This algorithm overcomes the inflexibility of Morphin algorithm in trajectory searching. The simulation results and the test on a real vehicle verify correctness and effectiveness of the algorithm.

关 键 词：多层Morphin搜索树 UGV 非完整性约束 模糊Q学习 局部路径规划 

分 类 号：TP249[自动化与计算机技术—检测技术与自动化装置]