摘要
各行各业的飞速发展致使巡检人员短缺现象愈加严重,巡检机器人需求大幅度增加,其应用范围急剧扩大,应用场景更加多元化,应用缺陷逐渐凸显,尤其是导航控制问题,故提出未知环境下基于机器视觉的巡检机器人自主导航控制方法研究。预处理未知环境机器视觉图像——图像色彩模型转换(RGB→HSV)与图像噪声滤除,以此为基础,结合定位传感器输出的巡检机器人位置信息,计算巡检机器人的偏移角度与偏移距离,结合多次历史测量经验,建立模糊语言值,获取对应的偏移角度与偏移距离隶属度函数,制定模糊策略表,将其输入至模糊控制器,即可引导巡检机器人按照正确方向前进,实现了巡检机器人的自动导航控制。实验数据显示:提出方法应用后巡检机器人偏移角度计算误差最小值为0.12%,偏移距离计算误差最小值为1.02%,巡检机器人自主导航控制结果与期望导航轨迹一致,充分证实提出方法应用性能较佳。
The rapid development of various industries has led to an increasingly serious shortage of inspection personnel.The demand for inspection robots has greatly increased,and their application scope has rapidly expanded.The application scenarios have become more diverse,and application defects have gradually become prominent,especially navigation control problems.Therefore,a research on autonomous navigation control methods for inspection robots based on machine vision in unknown environments is proposed.Preprocessing machine vision images in unknown environments-Image color model conversion(RGB→HSV)and image noise filtering.Based on this,combined with the position information of the inspection robot output by the positioning sensor,the offset angle and distance of the inspection robot are calculated.Combined with multiple historical measurement experiences,fuzzy language values are established to obtain the corresponding offset angle and offset distance membership functions,and a fuzzy strategy table is developed,By inputting it into the fuzzy controller,the inspection robot can be guided to move in the correct direction,achieving automatic navigation control of the inspection robot.The experimental data shows that after the application of the proposed method,the minimum deviation angle calculation error of the inspection robot is 0.12%,and the minimum deviation distance calculation error is 1.02%.The autonomous navigation control results of the inspection robot are consistent with the expected navigation trajectory,fully confirming that the proposed method has better application performance.
作者
朱定赟
ZHU Dingyun(Shanghai Polytechnic University,Shang Hai 201209,China)
出处
《自动化与仪器仪表》
2024年第9期221-224,229,共5页
Automation & Instrumentation
关键词
巡检机器人
机器视觉
路径规划
导航控制
未知环境
自主导航
iInspection robot
machine vision
path planning
navigation control
unknown environment
autonomous navigation
