华中科技大学学报（自然科学版）Issue(z1)：420-423,427,5.DOI:10.13245/j.hust.15S1100
一种小型无人机的 FastSLAM 算法
A FastSLAM algorithm for small unmanned aerial vehicle
摘要
Abstract
In order to solve the problem of autonomous flight of the small unmanned aerial vehicle (SUAV)in unknown environment,simultaneous localization and mapping(SLAM)algorithm was ex-panded from two-dimensional environment of the ground robot to three-dimensional environment of SUAV.First,the mathematic model of SUAV SLAM algorithm was built to obtain the nonlinear state equation of SUAV.Second,the SLAM problem of SUAV was decomposed into the estimation over path using a particle filter and the estimations over landmarks using extended Kalman filters for the purpose of designing a FastSLAM algorithm for SUAV.Finally,simulation researches respective-ly based on extended Kalman filter (EKF)and FastSLAM algorithm were carried out on SUAV.Re-sults show that FastSLAM algorithm has better performance in location accuracy than EKF algo-rithm.关键词
同步定位与地图构建/小型无人机/三维/FastSLAM 算法/扩展卡尔曼滤波器Key words
simultaneous localization and mapping (SLAM)/small unmanned aerial vehicle (SUAV)/three-dimensional/FastSLAM algorithm/extended Kalman filter (EKF)分类
信息技术与安全科学引用本文复制引用
丛楚滢,王从庆,丁臻极,李志宇..一种小型无人机的 FastSLAM 算法[J].华中科技大学学报（自然科学版）,2015,(z1):420-423,427,5.基金项目
江苏省科技支撑计划资助项目（BE2014712；BE2010190）． （）
