摘要
为解决传统粒子滤波(Rao-Blackwellized Particle Filter,RBPF)巡检机器人建图方法在非结构化环境中计算精度低、计算量大等问题,文章提出一种基于点云匹配的改进RBPF变电站巡检机器人建图方法。基于RBPF方法设计子图构建策略,引入Adaboost学习算法识别相邻子图;针对传统点云匹配方法在拼接仅有部分重合的子图时,拼接精度低的现象,将NDT和ICP算法相结合,设计匹配算法,求解子图间相对位姿。然后,根据子图间相对位姿,通过图优化(General Graph Optimization,G2O)算法对子图全局位姿进行优化求解,得到完整的变电站地图;采用Gazebo软件进行仿真,对不同方法的建图效果进行对比。结果表明:改进RBPF方法在变电站的复杂环境下能够降低硬件成本、提高建图精度,可以为无人值守变电站的设计提供参考。
In order to solve the problems of traditional Rao-Blackwellized particle filter(RBPF)inspection robot mapping method in the unstructured environment,such as low calculation accuracy and large calculation amount,an improved RBPF substation inspection robot mapping method based on point cloud matching is proposed in this paper.Firstly,based on the RBPF method,the subgraph construction strategy is designed,and the Adaboost learning algorithm is introduced to identify adjacent subgraphs.Secondly,in view of the low splicing accuracy of traditional point cloud matching methods when splicing only partially overlapping sub-images,the NDT and ICP algorithms are combined to design a matching algorithm to solve the relative poses between sub-images.Thirdly,according to the relative poses between the sub-graphs,the global pose of the sub-graphs is optimized through the general graph optimization(G2O)algorithm to obtain a complete substation map.Finally,the Gazebo software is used for simulation to compare the mapping effects of different methods.The results show that the improved RBPF method can reduce costs of hardware,improve the accuracy of mapping in the complex environment of substations,and can provide a reference for the design of unattended substations.
作者
于志浩
张艳荣
张安迪
徐雪莲
Yu Zhihao;Zhang Yanrong;Zhang Andi;Xu Xuelian(School of Mechanical Engineering,Southwest Jiaotong University,Chengdu 610031,China;School of Information Science and Engineering,Yanshan University,Qinhuangdao 066004,Hebei,China)
出处
《电测与仪表》
北大核心
2023年第6期26-31,共6页
Electrical Measurement & Instrumentation
基金
四川省科技计划项目(2017GZ0164)
四川省科委科研基金项目(2020YJ0035)。
关键词
地图构建
变电站
粒子滤波
点云匹配
机器人巡检
mapping construction
substation
Rao-Blackwellized particle filter
point cloud matching
robot inspection
