中山大学学报（自然科学版）（中英文）2025，Vol.64Issue(3)：109-118,10.DOI:10.13471/j.cnki.acta.snus.ZR20240348
基于语义地图的灾探无人机重定位方法
A semantic map-based drones relocalization method for UAV in disaster exploration
摘要
Abstract
In response to the potential failure of global positioning systems in disaster environments and the degradation of visible light images,as well as the low success rate of traditional computer vision-based relocalization algorithms due to insufficient image feature points,a semantic map-based drone relocalization method for unmanned aerial vehicle(UAV)is proposed.This method relies on RGB-D images to identify and construct landmark points in the disaster-affected environment.These landmark points are then matched with prior maps to optimize and estimate the relative pose of the drone.By reducing the suppression of the potential general object recognition capability within object recognition networks,high-level feature points in the image are obtained,effectively addressing the problem of difficult relocalization due to insufficient feature points.Building on the generalized object-based reconstruction of landmark points,an efficient method for retrieving and matching these points is proposed.Experimental results demonstrate that the approach can reconstruct a richer set of landmarks in unknown environments and effectively utilize them for localization,compared to other object recognition-based landmark point construction methods.In disaster scenarios with image degradation,this method exhibits higher recall rates and robustness than widely used image retrieval methods.关键词
城市火灾/无人机/重定位/语义地图/回环检测Key words
urban fire/UAV/relocalization/semantic map/loop closure detection分类
信息技术与安全科学引用本文复制引用
黎容熙,唐家成,胡天江..基于语义地图的灾探无人机重定位方法[J].中山大学学报（自然科学版）（中英文）,2025,64(3):109-118,10.基金项目
广东省重点领域研发计划(2024B1111060004) （2024B1111060004）
