摘要
目前降压变电站、升压变电站等电力系统中的关键节点大部分采用人工巡检方式,随着自动化和人工智能技术高速发展,传统人工巡检方式将被机器人巡检替代。现有的变电站巡检机器人大多采用单一的导航方式,这些导航方法都存在精度低、稳定性差等问题。提出了一种将视觉与激光自适应融合导航方法,在导航过程中,分别对视觉和激光导航方法的准确性进行评判,并对评判结果归一化处理,根据评判结果将两种导航方式进行融合,得到更准确、稳定的机器人位姿信息。经过反复的实验,在导航线被污渍遮盖的环境中,使用所提的融合导航方法定位精度达到2.0 cm;在周围场景变化较大,且激光导航效果较差的环境下,定位精度达到1.7 cm。由此可知,所提方法能够满足智能巡检机器人在复杂环境下的定位与导航。
With the rapid development of automation and artificial intelligence technology,the traditional manual inspection method of step-down substation and step-up substation substations will be replaced by robot inspection.Most of the existing substation inspection robots use a single navigation method,and these navigation methods have problems such as low precision and poor stability.An adaptive fusion method of vision and laser navigation is proposed.During the navigation process,the accuracy of the vision and laser navigation methods are judged respectively,and the judgement results are normalized.Fusion to obtain more accurate and stable robot pose information.After repeated experiments,using the mentioned method in the environment where the navigation line is covered,the positioning accuracy of the fusion navigation method proposed reaches 2.0 cm;in the environment where the surrounding scene changes greatly and the laser navigation effect is poor,the positioning accuracy reaches 1.7 cm,which can meet the positioning and navigation of intelligent inspection robots in complex environments.
作者
尹杭
樊绍胜
杨权
YIN Hang;FAN Shao-sheng;YANG Quan(School of Electrical and Information Engineering,Changsha University of Science and Technology,Changsha 410114,China)
出处
《电力学报》
2022年第3期209-218,共10页
Journal of Electric Power
关键词
电力系统
巡检机器人
视觉导航
激光导航
数据融合
power systems
inspection robot
visual navigation
laser navigation
data fusion
