自主移动机器人局部优化导航算法研究

自主移动机器人在未知环境下需要依靠自身装配的传感器不间断地获得周围环境信息,辨别出障碍物的位置,进行计算和自主决策.现有导航算法在面临U型等复杂环境时容易在僵死路径上产生反复,导致导航不能继续.文中提出了一种基于模糊逻辑的局部优化导航算法,采用"辨识-记忆"策略来处理传感器信息.在路径规划中保留最近走过路径的位置和角度特征等相关资源,形成"记忆".当前规划路径形成死区并反复运行时,会形成"辨识"并重新规划路径和导航决策以避免障碍物碰撞.在Webots Pro和Matlab下设计仿真实验,结果表明移动机器人在模糊规则指导下能有效避障和避免死区现象,实现较好的自主导航.

Research of Locally-Optimized Navigation Algorithm for Autonomous Mobile Robots

Autonomous mobile robots in an unknown environment get the information around them through their ow n sensors incessantly to identify the location of the obstaches and make autonmic decision .T he existing navigation algorithms are pronce to repeating on the rigid U-shaped path in sonce unknow n environment ,resulting in failure in navigation .T his paper presents a locally-optimizaed navigation algorithm based on fuzzy logic ,which used the“identfication-mermory” strategy to deal with the information obtained by the sensor .A “resource memory”is formed by keeping the characteristics of the last position and angle of the path the robot has travelled .When a dead zone is formed on the current path ,the robot can identify the obstace ,and then replan it path and make a new racigation descision to avoid their collision .The results of the simulation in Webots Pro and Matlab ,show that the mobile robot ,under the guidance of fuzzy rules ,can effectively avoid obstacles and the dead zone ,achieving a better autonomous navigetion .