Lidar and visual data are affected heavily in adverse weather conditions due to sensing mechanisms,which bring potential safety hazards for vehicle navigation.Radar sensing is desirable to build a more robust navigati...Lidar and visual data are affected heavily in adverse weather conditions due to sensing mechanisms,which bring potential safety hazards for vehicle navigation.Radar sensing is desirable to build a more robust navigation system.In this paper,a cross-modality radar localisation on prior lidar maps is presented.Specifically,the proposed workflow consists of two parts:first,bird's-eye-view radar images are transferred to fake lidar images by training a generative adversarial network offline.Then with online radar scans,a Monte Carlo localisation framework is built to track the robot pose on lidar maps.The whole online localisation system only needs a rotating radar sensor and a pre-built global lidar map.In the experimental section,the authors conduct an ablation study on image settings and test the proposed system on Oxford Radar Robot Car Dataset.The promising results show that the proposed localisation system could track the robot pose successfully,thus demonstrating the feasibility of radar style transfer for metric robot localisation on lidar maps.展开更多
In this paper,the adaptive lifting scheme (ALS) and local gradient maps (LGM) are proposed to isolate the transient feature components from the gearbox vibration signals. Based on entropy minimization rule,the ALS is ...In this paper,the adaptive lifting scheme (ALS) and local gradient maps (LGM) are proposed to isolate the transient feature components from the gearbox vibration signals. Based on entropy minimization rule,the ALS is employed to change properties of an initial wavelet and design adaptive wavelet. Then LGM is applied to characterize the transient feature components in detail signal of decomposition results using ALS. In the present studies, the orthogonal Daubechies 4 (Db 4) wavelet is used as the initial wavelet. The proposed method is applied to both simulated signals and vibration signals acquired from a gearbox for periodic impulses detection. The two conventional methods (cepstrum analysis and Hilbert envelope analysis) and the orthogonal Db4 wavelet are also used to analyze the same signals for comparison. The results demonstrate that the proposed method is more effective in extracting transient components from noisy signals.展开更多
An extended Kalman filter approach of simultaneous localization and mapping(SLAM) was proposed based on local maps. A local frame of reference was established periodically at the position of the robot, and then the ob...An extended Kalman filter approach of simultaneous localization and mapping(SLAM) was proposed based on local maps. A local frame of reference was established periodically at the position of the robot, and then the observations of the robot and landmarks were fused into the global frame of reference. Because of the independence of the local map, the approach does not cumulate the estimate and calculation errors which are produced by SLAM using Kalman filter directly. At the same time, it reduces the computational complexity. This method is proven correct and feasible in simulation experiments.展开更多
The processing maps were used to identify the optimal forging parameters of Ti-24A1- 17Nb-0.5Mo alloy by evaluating the flow data according to the DMM model. The actual local strain rate and strain distribution in the...The processing maps were used to identify the optimal forging parameters of Ti-24A1- 17Nb-0.5Mo alloy by evaluating the flow data according to the DMM model. The actual local strain rate and strain distribution in the samples were obtained by finite element calculations. The local microstructures of the deformed samples were related to the local deformation parameters and correlated with the processing maps at 0.3, 0.4, 0.5 and 0.6 of logarithmic strain. Flow regimes predicted by DMM analysis were then correlated with the local microstructural observations. Five domains of efficient coefficient could be distinguished. Unstable regions were microstructurally related to shear band formation within the （~2~B2 phase deformation field, and to flow localiza- tion at grain boundaries of B2 phase in the near B2 phase deformation field. Stable flow regimes were shown to be associated with dynamic globularization of the plate- like a2 in the a2＋B2 phase deformation zone, and with dynamic recrystallization of B2 in the near B2 phase deformation zone.展开更多
Digital maps of soil properties are now widely available.End-users now can access several digital soil mapping(DSM)products of soil properties,produced using different models,calibration/training data,and covariates a...Digital maps of soil properties are now widely available.End-users now can access several digital soil mapping(DSM)products of soil properties,produced using different models,calibration/training data,and covariates at various spatial scales from global to local.Therefore,there is an urgent need to provide easy-to-understand tools to communicate map uncertainty and help end-users assess the reliability of DSM products for use at local scales.In this study,we used a large amount of hand-feel soil texture(HFST)data to assess the performance of various published DSM products on the prediction of soil particle size distribution in Central France.We tested four DSM products for soil texture prediction developed at various scales(global,continental,national,and regional)by comparing their predictions with approximately 3200 HFST observations realized on a 1:50000 soil survey conducted after release of these DSM products.We used both visual comparisons and quantitative indicators to match the DSM predictions and HFST observations.The comparison between the low-cost HFST observations and DSM predictions clearly showed the applicability of various DSM products,with the prediction accuracy increasing from global to regional predictions.This simple evaluation can determine which products can be used at the local scale and if more accurate DSM products are required.展开更多
A new methodology of comparing digital raster maps was proposed which allows not only detecting changes in the maps, but also obtaining quantitative measures of the importance of selected differences. Procedure of obj...A new methodology of comparing digital raster maps was proposed which allows not only detecting changes in the maps, but also obtaining quantitative measures of the importance of selected differences. Procedure of object interpretation of satellite images and forming of OMT (Object Map of Territory) is described. A list of allowable differences between two OMTs is defined. Two steps technique of quantitative measuring is proposed. At the first stage functions are constructed for calculating local measures of differences in the amount, areas and locations of objects on the map, as well as relations between the objects. In the second stage local measures are used to calculate the integral measure in order to get generalized assessment of difference between maps. The methods for constructing functions which calculate local and integral measures of differences are described. Examples of comparing and measuring the differences between OMTs are provided. Obtained results by utilizing this technique can be used to analyze trends, forecast of development and might be helpful for choosing most efficient scenarios for sustainable spatial planning and land management.展开更多
Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors.These vehicles are crucial in various fields,including environ...Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors.These vehicles are crucial in various fields,including environmental science research,ecological and environmental monitoring projects,disaster response,and emergency management.A key method employed in these vehicles for achieving high-precision positioning is LiDAR(lightlaser detection and ranging)-Visual Simultaneous Localization and Mapping(SLAM).However,maintaining highprecision localization in complex scenarios,such as degraded environments or when dynamic objects are present,remains a significant challenge.To address this issue,we integrate both semantic and texture information from LiDAR and cameras to enhance the robustness and efficiency of data registration.Specifically,semantic information simplifies the modeling of scene elements,reducing the reliance on dense point clouds,which can be less efficient.Meanwhile,visual texture information complements LiDAR-Visual localization by providing additional contextual details.By incorporating semantic and texture details frompaired images and point clouds,we significantly improve the quality of data association,thereby increasing the success rate of localization.This approach not only enhances the operational capabilities of ecological monitoring vehicles in complex environments but also contributes to improving the overall efficiency and effectiveness of ecological monitoring and environmental protection efforts.展开更多
Bio-inspired visual systems have garnered significant attention in robotics owing to their energy efficiency,rapid dynamic response,and environmental adaptability.Among these,event cameras-bio-inspired sensors that as...Bio-inspired visual systems have garnered significant attention in robotics owing to their energy efficiency,rapid dynamic response,and environmental adaptability.Among these,event cameras-bio-inspired sensors that asynchronously report pixel-level brightness changes called’events’,stand out because of their ability to capture dynamic changes with minimal energy consumption,making them suitable for challenging conditions,such as low light or high-speed motion.However,current mapping and localization methods for event cameras depend primarily on point and line features,which struggle in sparse or low-feature environments and are unsuitable for static or slow-motion scenarios.We addressed these challenges by proposing a bio-inspired vision mapping and localization method using active LED markers(ALMs)combined with reprojection error optimization and asynchronous Kalman fusion.Our approach replaces traditional features with ALMs,thereby enabling accurate tracking under dynamic and low-feature conditions.The global mapping accuracy significantly improved by minimizing the reprojection error,with corner errors reduced from 16.8 cm to 3.1 cm after 400 iterations.The asynchronous Kalman fusion of multiple camera pose estimations from ALMs ensures precise localization with a high temporal efficiency.This method achieved a mean translation error of 0.078 m and a rotational error of 5.411°while evaluating dynamic motion.In addition,the method supported an output rate of 4.5 kHz while maintaining high localization accuracy in UAV spiral flight experiments.These results demonstrate the potential of the proposed approach for real-time robot localization in challenging environments.展开更多
The concept of local shock strength and a quantitative measure index str of local shock strength are proposed,derived from the oblique shock relation and the monotonic relationship between total pressure loss ratio an...The concept of local shock strength and a quantitative measure index str of local shock strength are proposed,derived from the oblique shock relation and the monotonic relationship between total pressure loss ratio and normal Mach number.Utilizing the high density gradient characteristic of shock waves and the oblique shock relation,a post-processing algorithm for two-dimensional flow field data is developed.The objective of the post-processing algorithm is to obtain specific shock wave location coordinates and calculate the corresponding str from flow filed data under the calibration of the oblique shock relation.Valida-tion of this post-processing algorithm is conducted using a standard model example that can be solved analytically.Combining the concept of local shock strength with the post-processing algorithm,a local shock strength quantitative mapping approach is established for the first time.This approach enables a quantitative measure and visualization of local shock strength at distinct locations,represented by color mapping on the shock structures.The approach can be applied to post-processing numerical sim-ulation data of two-dimensional flows.Applications to the intersection of two left-running oblique shock waves(straight shock waves),the bow shock in front of a cylinder(curved shock wave),and Mach reflection(mixed straight and curved shock waves)demonstrate the accuracy,and effectiveness of the mapping approach in investigating diverse shock wave phenomena.The quan-titative mapping approach of str may be a valuable tool in the design of supersonic/hypersonic vehicles and the exploration of shock wave evolution.展开更多
The Grey Wolf Optimization(GWO)algorithm is acknowledged as an effective method for rock acoustic emission localization.However,the conventional GWO algorithm encounters challenges related to solution accuracy and con...The Grey Wolf Optimization(GWO)algorithm is acknowledged as an effective method for rock acoustic emission localization.However,the conventional GWO algorithm encounters challenges related to solution accuracy and convergence speed.To address these concerns,this paper develops a Simplex Improved Grey Wolf Optimizer(SMIGWO)algorithm.The randomly generating initial populations are replaced with the iterative chaotic sequences.The search process is optimized using the convergence factor optimization algorithm based on the inverse incompleteГfunction.The simplex method is utilized to address issues related to poorly positioned grey wolves.Experimental results demonstrate that,compared to the conventional GWO algorithm-based AE localization algorithm,the proposed algorithm achieves a higher solution accuracy and showcases a shorter search time.Additionally,the algorithm demonstrates fewer convergence steps,indicating superior convergence efficiency.These findings highlight that the proposed SMIGWO algorithm offers enhanced solution accuracy,stability,and optimization performance.The benefits of the SMIGWO algorithm extend universally across various materials,such as aluminum,granite,and sandstone,showcasing consistent effectiveness irrespective of material type.Consequently,this algorithm emerges as a highly effective tool for identifying acoustic emission signals and improving the precision of rock acoustic emission localization.展开更多
针对弱纹理和变光照环境下基于点特征的视觉SLAM(simultaneous localization and mapping)算法轨迹漂移的问题,提出了一种基于改进自适应阈值ELSED算法(Adaptive-ELSED)的快速点线融合双目视觉SLAM算法。通过在ELSED算法中添加自适应阈...针对弱纹理和变光照环境下基于点特征的视觉SLAM(simultaneous localization and mapping)算法轨迹漂移的问题,提出了一种基于改进自适应阈值ELSED算法(Adaptive-ELSED)的快速点线融合双目视觉SLAM算法。通过在ELSED算法中添加自适应阈值矩阵,动态调整不同光照条件下梯度阈值,并使用长度抑制和短线合并策略,提高线特征的质量。利用基于双目几何约束和图像结构相似性(SSIM)进行快速线段特征三角化。基于历史位姿及误差分析获取初始位姿,通过自适应因子实现光束法平差过程中点线特征的更有效融合。实验结果表明,所提算法在提高线特征质量的同时,耗时仅为LSD算法的50%,线特征匹配速度较传统LBD算法提升67%,挑战性场景下轨迹误差较ORB-SLAM3降低62.2%,系统的平均跟踪帧率为27帧/s,在保证系统实时性的同时,显著提升了系统在弱纹理、变光照环境下的精度和鲁棒性。展开更多
当今主流地图构建系统由于定位精度不高、重投影误差较大等问题,限制了稠密地图的生成。尤其在动态场景中,系统的实时性和地图的高精度之间无法共存,以及物体的往复移动为后续地图精度的提升带来了额外的困难。针对上述问题,提出了一种...当今主流地图构建系统由于定位精度不高、重投影误差较大等问题,限制了稠密地图的生成。尤其在动态场景中,系统的实时性和地图的高精度之间无法共存,以及物体的往复移动为后续地图精度的提升带来了额外的困难。针对上述问题,提出了一种基于闭环检测和自适应降采样的视觉SLAM点云地图构建方法(Visual SLAM point cloud map construction method based on closed-loop detection and adaptive downsampling,PCL-LCAD)。上述方法从视觉SLAM系统建图的角度出发,加入3D点云技术,构建一个闭环检测优化模型,扩大生成地图的面积,再建立一个点云自适应降采样模型,利用KD-tree算法对其体素滤波进行改进。实验结果表明,PCL-LCAD方法能在保障准确性和实时性的同时,降低地图占用空间并且提高地图稠密度。展开更多
In this note we obtain generalization of well known results of carbone and Conti,Sehgal and Singh and Tanimoto concerning the existence of best approximation and simultaneous best approximation of continuous Junctions...In this note we obtain generalization of well known results of carbone and Conti,Sehgal and Singh and Tanimoto concerning the existence of best approximation and simultaneous best approximation of continuous Junctions from the set up of a normed space to the case of a Hausdorff locally convex space.展开更多
基金National Key R&D Program of China,Grant/Award Number:2020YFB1313300National Nature Science Foundation of China under Grant,Grant/Award Number:61903332Hong Kong Center for Construction Robotics(InnoHK center supported by Hong Kong ITC)。
文摘Lidar and visual data are affected heavily in adverse weather conditions due to sensing mechanisms,which bring potential safety hazards for vehicle navigation.Radar sensing is desirable to build a more robust navigation system.In this paper,a cross-modality radar localisation on prior lidar maps is presented.Specifically,the proposed workflow consists of two parts:first,bird's-eye-view radar images are transferred to fake lidar images by training a generative adversarial network offline.Then with online radar scans,a Monte Carlo localisation framework is built to track the robot pose on lidar maps.The whole online localisation system only needs a rotating radar sensor and a pre-built global lidar map.In the experimental section,the authors conduct an ablation study on image settings and test the proposed system on Oxford Radar Robot Car Dataset.The promising results show that the proposed localisation system could track the robot pose successfully,thus demonstrating the feasibility of radar style transfer for metric robot localisation on lidar maps.
基金Higher School Specialized Research Fund for the Doctoral Program Funding Issue(No.2011021120032)Fundamental Research Funds for the Central Universities(No.2012jdhz23)
文摘In this paper,the adaptive lifting scheme (ALS) and local gradient maps (LGM) are proposed to isolate the transient feature components from the gearbox vibration signals. Based on entropy minimization rule,the ALS is employed to change properties of an initial wavelet and design adaptive wavelet. Then LGM is applied to characterize the transient feature components in detail signal of decomposition results using ALS. In the present studies, the orthogonal Daubechies 4 (Db 4) wavelet is used as the initial wavelet. The proposed method is applied to both simulated signals and vibration signals acquired from a gearbox for periodic impulses detection. The two conventional methods (cepstrum analysis and Hilbert envelope analysis) and the orthogonal Db4 wavelet are also used to analyze the same signals for comparison. The results demonstrate that the proposed method is more effective in extracting transient components from noisy signals.
基金Project(60234030) supported by the National Natural Science Foundation of China project(A1420060159) supported by the National Basic Research
文摘An extended Kalman filter approach of simultaneous localization and mapping(SLAM) was proposed based on local maps. A local frame of reference was established periodically at the position of the robot, and then the observations of the robot and landmarks were fused into the global frame of reference. Because of the independence of the local map, the approach does not cumulate the estimate and calculation errors which are produced by SLAM using Kalman filter directly. At the same time, it reduces the computational complexity. This method is proven correct and feasible in simulation experiments.
文摘The processing maps were used to identify the optimal forging parameters of Ti-24A1- 17Nb-0.5Mo alloy by evaluating the flow data according to the DMM model. The actual local strain rate and strain distribution in the samples were obtained by finite element calculations. The local microstructures of the deformed samples were related to the local deformation parameters and correlated with the processing maps at 0.3, 0.4, 0.5 and 0.6 of logarithmic strain. Flow regimes predicted by DMM analysis were then correlated with the local microstructural observations. Five domains of efficient coefficient could be distinguished. Unstable regions were microstructurally related to shear band formation within the （~2~B2 phase deformation field, and to flow localiza- tion at grain boundaries of B2 phase in the near B2 phase deformation field. Stable flow regimes were shown to be associated with dynamic globularization of the plate- like a2 in the a2＋B2 phase deformation zone, and with dynamic recrystallization of B2 in the near B2 phase deformation zone.
文摘Digital maps of soil properties are now widely available.End-users now can access several digital soil mapping(DSM)products of soil properties,produced using different models,calibration/training data,and covariates at various spatial scales from global to local.Therefore,there is an urgent need to provide easy-to-understand tools to communicate map uncertainty and help end-users assess the reliability of DSM products for use at local scales.In this study,we used a large amount of hand-feel soil texture(HFST)data to assess the performance of various published DSM products on the prediction of soil particle size distribution in Central France.We tested four DSM products for soil texture prediction developed at various scales(global,continental,national,and regional)by comparing their predictions with approximately 3200 HFST observations realized on a 1:50000 soil survey conducted after release of these DSM products.We used both visual comparisons and quantitative indicators to match the DSM predictions and HFST observations.The comparison between the low-cost HFST observations and DSM predictions clearly showed the applicability of various DSM products,with the prediction accuracy increasing from global to regional predictions.This simple evaluation can determine which products can be used at the local scale and if more accurate DSM products are required.
文摘A new methodology of comparing digital raster maps was proposed which allows not only detecting changes in the maps, but also obtaining quantitative measures of the importance of selected differences. Procedure of object interpretation of satellite images and forming of OMT (Object Map of Territory) is described. A list of allowable differences between two OMTs is defined. Two steps technique of quantitative measuring is proposed. At the first stage functions are constructed for calculating local measures of differences in the amount, areas and locations of objects on the map, as well as relations between the objects. In the second stage local measures are used to calculate the integral measure in order to get generalized assessment of difference between maps. The methods for constructing functions which calculate local and integral measures of differences are described. Examples of comparing and measuring the differences between OMTs are provided. Obtained results by utilizing this technique can be used to analyze trends, forecast of development and might be helpful for choosing most efficient scenarios for sustainable spatial planning and land management.
基金supported by the project“GEF9874:Strengthening Coordinated Approaches to Reduce Invasive Alien Species(lAS)Threats to Globally Significant Agrobiodiversity and Agroecosystems in China”funding from the Excellent Talent Training Funding Project in Dongcheng District,Beijing,with project number 2024-dchrcpyzz-9.
文摘Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors.These vehicles are crucial in various fields,including environmental science research,ecological and environmental monitoring projects,disaster response,and emergency management.A key method employed in these vehicles for achieving high-precision positioning is LiDAR(lightlaser detection and ranging)-Visual Simultaneous Localization and Mapping(SLAM).However,maintaining highprecision localization in complex scenarios,such as degraded environments or when dynamic objects are present,remains a significant challenge.To address this issue,we integrate both semantic and texture information from LiDAR and cameras to enhance the robustness and efficiency of data registration.Specifically,semantic information simplifies the modeling of scene elements,reducing the reliance on dense point clouds,which can be less efficient.Meanwhile,visual texture information complements LiDAR-Visual localization by providing additional contextual details.By incorporating semantic and texture details frompaired images and point clouds,we significantly improve the quality of data association,thereby increasing the success rate of localization.This approach not only enhances the operational capabilities of ecological monitoring vehicles in complex environments but also contributes to improving the overall efficiency and effectiveness of ecological monitoring and environmental protection efforts.
基金Supported by Beijing Natural Science Foundation(Grant No.L231004)Young Elite Scientists Sponsorship Program by CAST(Grant No.2022QNRC001)+2 种基金Fundamental Research Funds for the Central Universities(Grant No.2025JBMC039)National Key Research and Development Program(Grant No.2022YFC2805200)National Natural Science Foundation of China(Grant No.52371338).
文摘Bio-inspired visual systems have garnered significant attention in robotics owing to their energy efficiency,rapid dynamic response,and environmental adaptability.Among these,event cameras-bio-inspired sensors that asynchronously report pixel-level brightness changes called’events’,stand out because of their ability to capture dynamic changes with minimal energy consumption,making them suitable for challenging conditions,such as low light or high-speed motion.However,current mapping and localization methods for event cameras depend primarily on point and line features,which struggle in sparse or low-feature environments and are unsuitable for static or slow-motion scenarios.We addressed these challenges by proposing a bio-inspired vision mapping and localization method using active LED markers(ALMs)combined with reprojection error optimization and asynchronous Kalman fusion.Our approach replaces traditional features with ALMs,thereby enabling accurate tracking under dynamic and low-feature conditions.The global mapping accuracy significantly improved by minimizing the reprojection error,with corner errors reduced from 16.8 cm to 3.1 cm after 400 iterations.The asynchronous Kalman fusion of multiple camera pose estimations from ALMs ensures precise localization with a high temporal efficiency.This method achieved a mean translation error of 0.078 m and a rotational error of 5.411°while evaluating dynamic motion.In addition,the method supported an output rate of 4.5 kHz while maintaining high localization accuracy in UAV spiral flight experiments.These results demonstrate the potential of the proposed approach for real-time robot localization in challenging environments.
基金supported by the National Natural Science Foundation of China(Grant No.12372233)the Fund of NPU-Duke China Seed Program(Grant No.119003067)the“111 Project”of China(Grant No.B17037-106).
文摘The concept of local shock strength and a quantitative measure index str of local shock strength are proposed,derived from the oblique shock relation and the monotonic relationship between total pressure loss ratio and normal Mach number.Utilizing the high density gradient characteristic of shock waves and the oblique shock relation,a post-processing algorithm for two-dimensional flow field data is developed.The objective of the post-processing algorithm is to obtain specific shock wave location coordinates and calculate the corresponding str from flow filed data under the calibration of the oblique shock relation.Valida-tion of this post-processing algorithm is conducted using a standard model example that can be solved analytically.Combining the concept of local shock strength with the post-processing algorithm,a local shock strength quantitative mapping approach is established for the first time.This approach enables a quantitative measure and visualization of local shock strength at distinct locations,represented by color mapping on the shock structures.The approach can be applied to post-processing numerical sim-ulation data of two-dimensional flows.Applications to the intersection of two left-running oblique shock waves(straight shock waves),the bow shock in front of a cylinder(curved shock wave),and Mach reflection(mixed straight and curved shock waves)demonstrate the accuracy,and effectiveness of the mapping approach in investigating diverse shock wave phenomena.The quan-titative mapping approach of str may be a valuable tool in the design of supersonic/hypersonic vehicles and the exploration of shock wave evolution.
基金support from the National Science Foundation of China(52304137,5192780752274124,52325403)Tiandi Science and Technology Co.,Ltd.(2022-2-TDMS012 and SKLIS202417)Sichuan University(SKHL2215).
文摘The Grey Wolf Optimization(GWO)algorithm is acknowledged as an effective method for rock acoustic emission localization.However,the conventional GWO algorithm encounters challenges related to solution accuracy and convergence speed.To address these concerns,this paper develops a Simplex Improved Grey Wolf Optimizer(SMIGWO)algorithm.The randomly generating initial populations are replaced with the iterative chaotic sequences.The search process is optimized using the convergence factor optimization algorithm based on the inverse incompleteГfunction.The simplex method is utilized to address issues related to poorly positioned grey wolves.Experimental results demonstrate that,compared to the conventional GWO algorithm-based AE localization algorithm,the proposed algorithm achieves a higher solution accuracy and showcases a shorter search time.Additionally,the algorithm demonstrates fewer convergence steps,indicating superior convergence efficiency.These findings highlight that the proposed SMIGWO algorithm offers enhanced solution accuracy,stability,and optimization performance.The benefits of the SMIGWO algorithm extend universally across various materials,such as aluminum,granite,and sandstone,showcasing consistent effectiveness irrespective of material type.Consequently,this algorithm emerges as a highly effective tool for identifying acoustic emission signals and improving the precision of rock acoustic emission localization.
文摘针对弱纹理和变光照环境下基于点特征的视觉SLAM(simultaneous localization and mapping)算法轨迹漂移的问题,提出了一种基于改进自适应阈值ELSED算法(Adaptive-ELSED)的快速点线融合双目视觉SLAM算法。通过在ELSED算法中添加自适应阈值矩阵,动态调整不同光照条件下梯度阈值,并使用长度抑制和短线合并策略,提高线特征的质量。利用基于双目几何约束和图像结构相似性(SSIM)进行快速线段特征三角化。基于历史位姿及误差分析获取初始位姿,通过自适应因子实现光束法平差过程中点线特征的更有效融合。实验结果表明,所提算法在提高线特征质量的同时,耗时仅为LSD算法的50%,线特征匹配速度较传统LBD算法提升67%,挑战性场景下轨迹误差较ORB-SLAM3降低62.2%,系统的平均跟踪帧率为27帧/s,在保证系统实时性的同时,显著提升了系统在弱纹理、变光照环境下的精度和鲁棒性。
文摘当今主流地图构建系统由于定位精度不高、重投影误差较大等问题,限制了稠密地图的生成。尤其在动态场景中,系统的实时性和地图的高精度之间无法共存,以及物体的往复移动为后续地图精度的提升带来了额外的困难。针对上述问题,提出了一种基于闭环检测和自适应降采样的视觉SLAM点云地图构建方法(Visual SLAM point cloud map construction method based on closed-loop detection and adaptive downsampling,PCL-LCAD)。上述方法从视觉SLAM系统建图的角度出发,加入3D点云技术,构建一个闭环检测优化模型,扩大生成地图的面积,再建立一个点云自适应降采样模型,利用KD-tree算法对其体素滤波进行改进。实验结果表明,PCL-LCAD方法能在保障准确性和实时性的同时,降低地图占用空间并且提高地图稠密度。
文摘In this note we obtain generalization of well known results of carbone and Conti,Sehgal and Singh and Tanimoto concerning the existence of best approximation and simultaneous best approximation of continuous Junctions from the set up of a normed space to the case of a Hausdorff locally convex space.
