摘要
由于壁面爬行机器人导航避障的过程中,无法准确判定障碍物节点所处的位置,导致避障效果较差。为此,文中提出一种基于蝗虫优化算法的壁面爬行机器人导航避障方法。首先,基于对蝗虫优化算法个体对象的表示构建障碍物节点的目标函数,并对目标函数进行求解,获取的解即为局部搜索的障碍物节点,以此判定障碍物所处的位置;然后,分析壁面爬行机器人的运动行为,建立壁面爬行机器人的运动学模型,对机器人运动行为的坐标进行转换后,根据障碍物所处的位置对壁面爬行机器人的导航行进路线进行规划。实验结果表明,所提方法的壁面爬行机器人在单位运动区域内的避障有效性超过95%,可以准确躲避障碍物节点,能够有效提升机器人运动避障能力。
In the process of navigation and obstacle avoidance,the wall crawling robot can not accurately determine the position of the obstacle node,resulting in poor obstacle avoidance effect.On this basis,a method of wall climbing robot navigation obstacle avoidance based on locust optimization algorithm is proposed.The objective function of obstacle node is constructed based on the representation of individual object of locust optimization algorithm,and the objective function is solved to obtain the obstacle node of local search,so as to determine the location of the obstacle.The motion behavior of the wall crawling robot is analyzed,the kinematics model of the wall crawling robot is established,the coordinates of the robot′s motion behavior are converted,and the navigation route of the wall crawling robot is planed according to the location of the obstacles.The experimental results show that the obstacle avoidance effectiveness of the wall crawling robot in the unit motion area of the proposed method can exceed 95%,and it can accurately avoid the obstacle nodes,which can play an effective role in improving the obstacle avoidance ability of the robot.
作者
张新华
ZHANG Xinhua(Xiamen University,Xiamen 361005,China)
出处
《现代电子技术》
2022年第24期131-135,共5页
Modern Electronics Technique
关键词
蝗虫优化算法
壁面爬行机器人
导航避障
个体对象
目标函数
运动学坐标
坐标转换
全局路径
locust optimization algorithm
wall crawling robot
navigation obstacle avoidance
individual objects
objective function
Kinematic coordinates
coordinate conversion
global path
