摘要
为了实现重于水型自治潜器(Heavier-Than-Water Autonomous Underwater Vehicle,AUV)在未知水下环境中的局部路径规划。首先根据AUV的运动方程和机翼升力特性,在Matlab中建立动力学模型。设计模糊控制器,以声呐对障碍物探测得到的距离和方位信息作为输入量,实现了AUV在水下障碍物环境中的路径规划。最后,为提高AUV的能量利用效率,用遗传算法对模糊控制器的隶属度函数进行优化,并通过仿真试验证明了优化后AUV在避障期间能源消耗更少,说明该路径规划方法具有实际应用价值。
In order to achieve the goal of local path planning of a Heavier-Than-Water AUV in unknown underwater environment. A matlab kinematic model of the AUV was built based on its equation of motion and lift characteristics. A fuzzy controller was designed that enables AUV to plan path in real time. The controller takes obstacles＇ distance and orientation obtained from the sonar as input to control the AUV. At last, genetic algorithm was used to optimize the membership function of the fuzzy controller for improving energy utilization. And simulation tests showed that AUV consumed less energy during obstacle avoidance stage after optimization, which proved that the path planning method has practical value.
作者
俞炅旻
吴超
赵敏
葛彤
YU Jiong-min;WU Chao;ZHAO Min;GE Tong(School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiaotong University, Shanghai 200240, Chin)
出处
《舰船科学技术》
北大核心
2017年第12期76-80,117,共6页
Ship Science and Technology
基金
国家重大仪器研制资助项目(41427806)
关键词
重于水型AUV
模糊路径规划
遗传算法
避障
Heavier-Than-Water AUV
fuzzy path planning
genetic algorithm
obstacle avoidance
