In floristic research,the grid mapping method is a crucial and highly effective tool for investigating the flora of specific regions.This methodology aids in the collection of comprehensive data,thereby promoting a th...In floristic research,the grid mapping method is a crucial and highly effective tool for investigating the flora of specific regions.This methodology aids in the collection of comprehensive data,thereby promoting a thorough understanding of regional plant diversity.This paper presents findings from a grid mapping study conducted in the Surkhan-Sherabad botanical-geographic region(SShBGR),acknowledged as one of the major floristic areas in southwestern Uzbekistan.Using an expansive dataset of 14,317 records comprised of herbarium specimens and field diary entries collected from 1897 to 2023,we evaluated the stages and seasonal dynamics of data accumulation,species richness(SR),and collection density(CD)within 5 km×5 km grid cells.We further examined the taxonomic and life form composition of the region's flora.Our analysis revealed that the grid mapping phase(2021–2023)produced a significantly greater volume of specimens and taxonomic diversity compared with other periods(1897–1940,1941–1993,and 1994–2020).Field research spanned 206 grid cells during 2021–2023,resulting in 11,883 samples,including 6469 herbarium specimens and 5414 field records.Overall,fieldwork covered 251 of the 253 grid cells within the SShBGR.Notably,the highest species diversity was documented in the B198 grid cell,recording 160 species.In terms of collection density,the E198 grid cell produced 475 samples.Overall,we identified 1053 species distributed across 439 genera and 78 families in the SShBGR.The flora of this region aligned significantly with the dominant families commonly found in the Holarctic,highlighting vital ecological connections.Among our findings,the Asteraceae family was the most polymorphic,with 147 species,followed by the continually stable and diverse Poaceae,Fabaceae,Brassicaceae,and Amaranthaceae.Besides,our analysis revealed a predominance of therophyte life forms,which constituted 52%(552 species)of the total flora.The findings underscore the necessity for continual data collection efforts to further enhance our understanding of the biodiversity in the SShBGR.The results of this study demonstrated that the application of grid-based mapping in floristic studies proves to be an effective tool for assessing biodiversity and identifying key taxonomic groups.展开更多
For the mobile robot path planning under the complex environment,ant colony optimization with artificial potential field based on grid map is proposed to avoid traditional ant colony algorithm's poor convergence a...For the mobile robot path planning under the complex environment,ant colony optimization with artificial potential field based on grid map is proposed to avoid traditional ant colony algorithm's poor convergence and local optimum.Firstly,the pheromone updating mechanism of ant colony is designed by a hybrid strategy of global map updating and local grids updating.Then,some angles between the vectors of artificial potential field and the orientations of current grid are introduced to calculate the visibility of eight-neighbor cells of cellular automata,which are adopted as ant colony's inspiring factor to calculate the transition probability based on the pseudo-random transition rule cellular automata.Finally,mobile robot dynamic path planning and the simulation experiments are completed by this algorithm,and the experimental results show that the method is feasible and effective.展开更多
With the increasing complexity of substation inspection tasks,achieving efficient and safe path planning for Unmanned Aerial Vehicles in densely populated and structurally complex three-dimensional(3D)environments rem...With the increasing complexity of substation inspection tasks,achieving efficient and safe path planning for Unmanned Aerial Vehicles in densely populated and structurally complex three-dimensional(3D)environments remains a critical challenge.To address this problem,this paper proposes an improved path planning algorithm—Random Geometric Graph(RGG)-guided Rapidly-exploring Random Tree(R-RRT)—based on the classical Rapidly-exploring Random Tree(RRT)framework.First,a refined 3D occupancy grid map is constructed from Light Detection and Ranging point cloud data through ground filtering,noise removal,coordinate transformation,and obstacle inflation using spherical structuring elements.During the planning stage,a dynamic goal-biasing strategy is introduced to adaptively adjust the sampling direction,the sampling distribution is optimized using a pre-generated RGG,and collision detection is accelerated via a K-Dimensional Tree structure.After initial trajectory generation,redundant nodes are eliminated via greedy pruning,and a curvature-minimizing gradient-based optimizationmethod is applied to smooth the trajectory.Experimental results conducted in a simulated substation environment demonstrate that,compared with mainstream path planning algorithms,the proposed R-RRT achieves superior performance in terms of path length,planning time,and trajectory smoothness.Comprehensive analysis shows that the proposed method significantly enhances trajectory quality,planning efficiency,and operational safety,validating its applicability and advantages for high-precision 3D path planning in complex substation inspection scenarios.展开更多
Aimed at the problems of a traditional ant colony algorithm,such as the path search direction and field of view,an inability to find the shortest path,a propensity toward deadlock and an unsmooth path,an ant colony al...Aimed at the problems of a traditional ant colony algorithm,such as the path search direction and field of view,an inability to find the shortest path,a propensity toward deadlock and an unsmooth path,an ant colony algorithm for use in a new environment is proposed.First,the feature points of an obstacle are extracted to preprocess the grid map environment,which can avoid entering a trap and solve the deadlock problem.Second,these feature points are used as pathfinding access nodes to reduce the node access,with more moving directions to be selected,and the locations of the feature points to be selected determine the range of the pathfinding field of view.Then,based on the feature points,an unequal distribution of pheromones and a two-way parallel path search are used to improve the construction efficiency of the solution,an improved heuristic function is used to enhance the guiding role of the path search,and the pheromone volatilization coefficient is dynamically adjusted to avoid a premature convergence of the algorithm.Third,a Bezier curve is used to smooth the shortest path obtained.Finally,using grid maps with a different complexity and different scales,a simulation comparing the results of the proposed algorithm with those of traditional and other improved ant colony algorithms verifies its feasibility and superiority.展开更多
To solve the shortest path planning problems on grid-based map efficiently,a novel heuristic path planning approach based on an intelligent swarm optimization method called Multivariant Optimization Algorithm( MOA) an...To solve the shortest path planning problems on grid-based map efficiently,a novel heuristic path planning approach based on an intelligent swarm optimization method called Multivariant Optimization Algorithm( MOA) and a modified indirect encoding scheme are proposed. In MOA,the solution space is iteratively searched through global exploration and local exploitation by intelligent searching individuals,who are named as atoms. MOA is employed to locate the shortest path through iterations of global path planning and local path refinements in the proposed path planning approach. In each iteration,a group of global atoms are employed to perform the global path planning aiming at finding some candidate paths rapidly and then a group of local atoms are allotted to each candidate path for refinement. Further,the traditional indirect encoding scheme is modified to reduce the possibility of constructing an infeasible path from an array. Comparative experiments against two other frequently use intelligent optimization approaches: Genetic Algorithm( GA) and Particle Swarm Optimization( PSO) are conducted on benchmark test problems of varying complexity to evaluate the performance of MOA. The results demonstrate that MOA outperforms GA and PSO in terms of optimality indicated by the length of the located path.展开更多
This article presents information on the study of the flora of Uzbekistan based on grid system mapping. The urban flora of the city of Bukhara was researched in it. As a result of research, the territory of Bukhara ci...This article presents information on the study of the flora of Uzbekistan based on grid system mapping. The urban flora of the city of Bukhara was researched in it. As a result of research, the territory of Bukhara city was divided into 85 indexes based on 1 × 1 km<sup>2</sup> grid mapping system. The diversity and density of species in the indexes are determined. The influence of anthropogenic factors on the diversity of species in the indexes is determined.展开更多
Map building by multi-robot is very important to accomplish autonomous navigation,and one of the basic problems and research hotspots is how to merge the maps into a single one in the field of multi-robot map building...Map building by multi-robot is very important to accomplish autonomous navigation,and one of the basic problems and research hotspots is how to merge the maps into a single one in the field of multi-robot map building.A novel approach is put forward based on adaptive differential evolution to map building for the multi-robot system.The multi-robot mapping-building system adopts the methods of decentralized exploration and concentrated mapping.The adaptive differential evolution algorithm is used to search in the space of possible transformation,and the iterative search is performed with the goal of maximizing overlapping regions.The map is translated and rotated so that the two maps can be overlapped and merged into a single global one successfully.This approach for map building can be realized without any knowledge of their relative positions.Experimental results show that the approach is effective and feasibile.展开更多
在视觉SLAM(Simultaneous Localization and Mapping)系统中,特征匹配对实时定位与建图起着重要作用。ORB-SLAM3系统面临特征匹配效率不高且缺乏稠密地图构建能力的问题,针对该问题文章提出了一种融合网格运动统计策略和稠密建图能力的...在视觉SLAM(Simultaneous Localization and Mapping)系统中,特征匹配对实时定位与建图起着重要作用。ORB-SLAM3系统面临特征匹配效率不高且缺乏稠密地图构建能力的问题,针对该问题文章提出了一种融合网格运动统计策略和稠密建图能力的算法ORB-SLAM3-GD(ORB-SLAM3 with GMS Strategy and Dense Mapping)。新算法在特征匹配阶段,通过比较特征点邻域内的匹配点数量和阈值筛选正确匹配以提升匹配准确率,并引入稠密点云构建线程生成稠密点云地图,在生成地图的过程中采用外点剔除滤波与体素网格滤波技术压缩点云规模。在TUM(Technical University of Munich,TUM)数据集上进行性能评估测试,结果表明:相比ORB-SLAM3,文章所提算法平均匹配点数提升了61.7%,匹配时间缩短45.61%,绝对轨迹误差平均降低21.62%,体现了新算法的优势。展开更多
基金supported by the grant from the State Programs"Grid Mapping of the Flora of Uzbekistan'during 2020–2024"the grant from the State Programs"Creation of the Digital Platform of the Plant World of Central Uzbekistan"during 2025–2029the State Research Project"Taxonomic Revision of Polymorphic Plant Families of the Flora of Uzbekistan"from the Institute of Botany,Academy of Sciences of the Republic of Uzbekistan (A-FA-2021-427)
文摘In floristic research,the grid mapping method is a crucial and highly effective tool for investigating the flora of specific regions.This methodology aids in the collection of comprehensive data,thereby promoting a thorough understanding of regional plant diversity.This paper presents findings from a grid mapping study conducted in the Surkhan-Sherabad botanical-geographic region(SShBGR),acknowledged as one of the major floristic areas in southwestern Uzbekistan.Using an expansive dataset of 14,317 records comprised of herbarium specimens and field diary entries collected from 1897 to 2023,we evaluated the stages and seasonal dynamics of data accumulation,species richness(SR),and collection density(CD)within 5 km×5 km grid cells.We further examined the taxonomic and life form composition of the region's flora.Our analysis revealed that the grid mapping phase(2021–2023)produced a significantly greater volume of specimens and taxonomic diversity compared with other periods(1897–1940,1941–1993,and 1994–2020).Field research spanned 206 grid cells during 2021–2023,resulting in 11,883 samples,including 6469 herbarium specimens and 5414 field records.Overall,fieldwork covered 251 of the 253 grid cells within the SShBGR.Notably,the highest species diversity was documented in the B198 grid cell,recording 160 species.In terms of collection density,the E198 grid cell produced 475 samples.Overall,we identified 1053 species distributed across 439 genera and 78 families in the SShBGR.The flora of this region aligned significantly with the dominant families commonly found in the Holarctic,highlighting vital ecological connections.Among our findings,the Asteraceae family was the most polymorphic,with 147 species,followed by the continually stable and diverse Poaceae,Fabaceae,Brassicaceae,and Amaranthaceae.Besides,our analysis revealed a predominance of therophyte life forms,which constituted 52%(552 species)of the total flora.The findings underscore the necessity for continual data collection efforts to further enhance our understanding of the biodiversity in the SShBGR.The results of this study demonstrated that the application of grid-based mapping in floristic studies proves to be an effective tool for assessing biodiversity and identifying key taxonomic groups.
基金National Natural Science Foundation of China(No.61373110)the Science-Technology Project of Wuhan,China(No.2014010101010005)
文摘For the mobile robot path planning under the complex environment,ant colony optimization with artificial potential field based on grid map is proposed to avoid traditional ant colony algorithm's poor convergence and local optimum.Firstly,the pheromone updating mechanism of ant colony is designed by a hybrid strategy of global map updating and local grids updating.Then,some angles between the vectors of artificial potential field and the orientations of current grid are introduced to calculate the visibility of eight-neighbor cells of cellular automata,which are adopted as ant colony's inspiring factor to calculate the transition probability based on the pseudo-random transition rule cellular automata.Finally,mobile robot dynamic path planning and the simulation experiments are completed by this algorithm,and the experimental results show that the method is feasible and effective.
基金Funding for this research was provided by the Program for Scientific Research Innovation Team in Colleges and Universities of Anhui Province(No.2022AH010095)the Hefei Key Technology R&D“Champion-Based Selection”Project(No.2023SGJ011).
文摘With the increasing complexity of substation inspection tasks,achieving efficient and safe path planning for Unmanned Aerial Vehicles in densely populated and structurally complex three-dimensional(3D)environments remains a critical challenge.To address this problem,this paper proposes an improved path planning algorithm—Random Geometric Graph(RGG)-guided Rapidly-exploring Random Tree(R-RRT)—based on the classical Rapidly-exploring Random Tree(RRT)framework.First,a refined 3D occupancy grid map is constructed from Light Detection and Ranging point cloud data through ground filtering,noise removal,coordinate transformation,and obstacle inflation using spherical structuring elements.During the planning stage,a dynamic goal-biasing strategy is introduced to adaptively adjust the sampling direction,the sampling distribution is optimized using a pre-generated RGG,and collision detection is accelerated via a K-Dimensional Tree structure.After initial trajectory generation,redundant nodes are eliminated via greedy pruning,and a curvature-minimizing gradient-based optimizationmethod is applied to smooth the trajectory.Experimental results conducted in a simulated substation environment demonstrate that,compared with mainstream path planning algorithms,the proposed R-RRT achieves superior performance in terms of path length,planning time,and trajectory smoothness.Comprehensive analysis shows that the proposed method significantly enhances trajectory quality,planning efficiency,and operational safety,validating its applicability and advantages for high-precision 3D path planning in complex substation inspection scenarios.
基金the National Natural Science Founda-tion(Nos.62063019 and 61763026)the Gansu Nat-ural Science Foundation Project(No.20JR10RA152)the Gansu Provincial Department of Educa-tion:Excellent Graduate“Innovation Star”Project(No.2021CXZX-507)。
文摘Aimed at the problems of a traditional ant colony algorithm,such as the path search direction and field of view,an inability to find the shortest path,a propensity toward deadlock and an unsmooth path,an ant colony algorithm for use in a new environment is proposed.First,the feature points of an obstacle are extracted to preprocess the grid map environment,which can avoid entering a trap and solve the deadlock problem.Second,these feature points are used as pathfinding access nodes to reduce the node access,with more moving directions to be selected,and the locations of the feature points to be selected determine the range of the pathfinding field of view.Then,based on the feature points,an unequal distribution of pheromones and a two-way parallel path search are used to improve the construction efficiency of the solution,an improved heuristic function is used to enhance the guiding role of the path search,and the pheromone volatilization coefficient is dynamically adjusted to avoid a premature convergence of the algorithm.Third,a Bezier curve is used to smooth the shortest path obtained.Finally,using grid maps with a different complexity and different scales,a simulation comparing the results of the proposed algorithm with those of traditional and other improved ant colony algorithms verifies its feasibility and superiority.
基金Sponsored by the National Natural Science Foundation of China(Grant No.61261007,61002049)the Key Program of Yunnan Natural Science Foundation(Grant No.2013FA008)
文摘To solve the shortest path planning problems on grid-based map efficiently,a novel heuristic path planning approach based on an intelligent swarm optimization method called Multivariant Optimization Algorithm( MOA) and a modified indirect encoding scheme are proposed. In MOA,the solution space is iteratively searched through global exploration and local exploitation by intelligent searching individuals,who are named as atoms. MOA is employed to locate the shortest path through iterations of global path planning and local path refinements in the proposed path planning approach. In each iteration,a group of global atoms are employed to perform the global path planning aiming at finding some candidate paths rapidly and then a group of local atoms are allotted to each candidate path for refinement. Further,the traditional indirect encoding scheme is modified to reduce the possibility of constructing an infeasible path from an array. Comparative experiments against two other frequently use intelligent optimization approaches: Genetic Algorithm( GA) and Particle Swarm Optimization( PSO) are conducted on benchmark test problems of varying complexity to evaluate the performance of MOA. The results demonstrate that MOA outperforms GA and PSO in terms of optimality indicated by the length of the located path.
文摘This article presents information on the study of the flora of Uzbekistan based on grid system mapping. The urban flora of the city of Bukhara was researched in it. As a result of research, the territory of Bukhara city was divided into 85 indexes based on 1 × 1 km<sup>2</sup> grid mapping system. The diversity and density of species in the indexes are determined. The influence of anthropogenic factors on the diversity of species in the indexes is determined.
基金Supported by the National Natural Science Foundation of China(No.90820302,60805027)the Provincial Natural Science Foundation of Hunan(No.12JJ3064)+1 种基金the Construct Program of the Key Discipline in Hunan Province(No.201176)the Planned Science and Technology Project of Hunan Province(No.2011SK3135,2012FJ3059)
文摘Map building by multi-robot is very important to accomplish autonomous navigation,and one of the basic problems and research hotspots is how to merge the maps into a single one in the field of multi-robot map building.A novel approach is put forward based on adaptive differential evolution to map building for the multi-robot system.The multi-robot mapping-building system adopts the methods of decentralized exploration and concentrated mapping.The adaptive differential evolution algorithm is used to search in the space of possible transformation,and the iterative search is performed with the goal of maximizing overlapping regions.The map is translated and rotated so that the two maps can be overlapped and merged into a single global one successfully.This approach for map building can be realized without any knowledge of their relative positions.Experimental results show that the approach is effective and feasibile.
文摘在视觉SLAM(Simultaneous Localization and Mapping)系统中,特征匹配对实时定位与建图起着重要作用。ORB-SLAM3系统面临特征匹配效率不高且缺乏稠密地图构建能力的问题,针对该问题文章提出了一种融合网格运动统计策略和稠密建图能力的算法ORB-SLAM3-GD(ORB-SLAM3 with GMS Strategy and Dense Mapping)。新算法在特征匹配阶段,通过比较特征点邻域内的匹配点数量和阈值筛选正确匹配以提升匹配准确率,并引入稠密点云构建线程生成稠密点云地图,在生成地图的过程中采用外点剔除滤波与体素网格滤波技术压缩点云规模。在TUM(Technical University of Munich,TUM)数据集上进行性能评估测试,结果表明:相比ORB-SLAM3,文章所提算法平均匹配点数提升了61.7%,匹配时间缩短45.61%,绝对轨迹误差平均降低21.62%,体现了新算法的优势。
