Unmanned aerial vehicle orthogonal laser localization by Gaussian mixture model‐based map representation  

作　　者：Zeyu Wan Changjian Jiang Yu Zhang 

机构地区：[1]State Key Laboratory of Industrial Control Technology,College of Control Science and Engineering,Zhejiang University,Hangzhou,China

出　　处：《IET Cyber-Systems and Robotics》2023年第3期37-44,共8页智能系统与机器人（英文）

基　　金：supported by STI 2030‐Major Projects No.2021ZD0201403,in part by NSFC No.62088101 Autonomous Intelligent Unmanned Systems and in part by the Open Research Project of the State Key Laboratory of Industrial Control Technology,Zhejiang University,China(No.ICT2022B04).

摘　　要：Localization is a core problem in mobile robot navigation.Simultaneous localization and mapping(SLAM)costs much for an unmanned aerial vehicle(UAV).This research aims to design an orthogonal laser scan device for localization and to save computation costs.Based on disturbance analysis,residual influences on sensor state are quantitative,and they are related to uncertainty and sensitivity.This research applied the residual selection method to a UAV.The feature point detection utilises multi‐scale and Gaussian model fitting techniques to guarantee true positives.The map is represented by Gaussian Mixture Models(GMM)with lower memory costs.The orthogonal laser scan device is composed and placed on a UAV for real‐time three‐dimensional localization,whose er-rors are at the centimeter level.

关 键 词：indoor positioning mobile robots unmanned aerial vehicle 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置] V279[自动化与计算机技术—控制科学与工程]