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Integrating wind field analysis in UAV path planning:Enhancing safety and energy efficiency for urban logistics 认领 引用 被引量：3
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作者 Ruijia GU Yifei ZHAO Xinhui REN 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第1期508-533,共26页
Shenzhen,a major city in southern China,has experienced rapid advancements in Unmanned Aerial Vehicle(UAV)technology,resulting in extensive logistics networks with thousands of daily flights.However,frequent disruptio... Shenzhen,a major city in southern China,has experienced rapid advancements in Unmanned Aerial Vehicle(UAV)technology,resulting in extensive logistics networks with thousands of daily flights.However,frequent disruptions due to its subtropical monsoon climate,including typhoons and gusty winds,present ongoing challenges.Despite the growing focus on operational costs and third-party risks,research on low-altitude urban wind fields remains scarce.This study addresses this gap by integrating wind field analysis into UAV path planning,introducing key innovations to the classical model.First,UAV wind resistance and turbulence constraints are analyzed,mapping high-wind-speed and turbulence-prone zones in the airspace.Second,wind dynamics are incorporated into path planning by considering airspeed and groundspeed variation,optimizing waypoint selection and flight speed adjustments to improve overall energy efficiency.Additionally,a wind-aware Theta*algorithm is proposed,leveraging wind vectors to expedite search process,while Computational Fluid Dynamics(CFD)techniques are employed to calculate wind fields.A case study of Shenzhen,examining wind patterns over the past decade,demonstrates a 6.23%improvement in groundspeed and a 7.69%reduction in energy consumption compared to wind-agnostic models.This framework advances UAV logistics by enhancing route safety and energy efficiency,contributing to more cost-effective operations. 展开更多
关键词 Drone logistics Energy consumption Hazardous field region Path planning Unmanned aerial vehicle(UAV) Urban wind fields
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2.5D process path planning for multi-genus shapes based on combining of topological and geometric properties of medial axis transformation 认领 引用 被引量：1
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作者 Xin JIANG Wenjie ZHAO +3 位作者 Cheng SU Guanying HUO Shirong LI Zhiming ZHENG 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第4期640-653,共14页
The 2.5D process is widely utilized in modern industries,with multi-genus cross-sections increasingly encountered in both additive and subtractive manufacturing.Tool paths for multigenus shapes often suffer from disco... The 2.5D process is widely utilized in modern industries,with multi-genus cross-sections increasingly encountered in both additive and subtractive manufacturing.Tool paths for multigenus shapes often suffer from discontinuities that lead to frequent tool liftings,and selfintersections in offset paths,adversely affecting machining accuracy and efficiency.In this context,path topology,stepover uniformity,and degeneration of offset paths represent three fundamental concerns that must be considered in an integrated manner in 2.5D path planning for multi-genus shapes.This study proposes a tool path planning method based on combining of topological and geometric characteristics of medial axis transformation for the shape with multi-genus.A region segmentation strategy tailored to multi-genus shapes is first introduced to prevent global selfintersections in equidistant offset paths.Subsequently,the graph structure of the segmented shape is extracted,and the minimization of tool liftings is formulated as a minimum path cover problem in an undirected graph.A Fermat-spiral-like path topology is adopted within sub-regions to preserve the connectivity of graph and ensure smooth transitions between successive layers of contourparallel paths.Numerical and physical experiment results confirm the proposed method's effectiveness in maintaining stepover uniformity,avoiding degeneration of global self-intersections,and ensuring path connectivity. 展开更多
关键词 2.5D process Medial axis transformation Multi-genus shape Topological segmentation Tool path planning
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Dynamic Integration of Q-Learning and A-APF for Efficient Path Planning in Complex Underground Mining Environments 认领 引用 被引量：1
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作者 Chang Su Liangliang Zhao Dongbing Xiang 《Computers, Materials & Continua》 SCIE EI 2026年第2期1017-1040,共24页
To address low learning efficiency and inadequate path safety in spraying robot navigation within complex obstacle-rich environments—with dense,dynamic,unpredictable obstacles challenging conventional methods—this p... To address low learning efficiency and inadequate path safety in spraying robot navigation within complex obstacle-rich environments—with dense,dynamic,unpredictable obstacles challenging conventional methods—this paper proposes a hybrid algorithm integrating Q-learning and improved A*-Artificial Potential Field(A-APF).Centered on theQ-learning framework,the algorithmleverages safety-oriented guidance generated byA-APF and employs a dynamic coordination mechanism that adaptively balances exploration and exploitation.The proposed system comprises four core modules:(1)an environment modeling module that constructs grid-based obstacle maps;(2)an A-APF module that combines heuristic search from A*algorithm with repulsive force strategies from APF to generate guidance;(3)a Q-learning module that learns optimal state-action values(Q-values)through spraying robot-environment interaction and a reward function emphasizing path optimality and safety;and(4)a dynamic optimization module that ensures adaptive cooperation between Q-learning and A-APF through exploration rate control and environment-aware constraints.Simulation results demonstrate that the proposed method significantly enhances path safety in complex underground mining environments.Quantitative results indicate that,compared to the traditional Q-learning algorithm,the proposed method shortens training time by 42.95% and achieves a reduction in training failures from 78 to just 3.Compared to the static fusion algorithm,it further reduces both training time(by 10.78%)and training failures(by 50%),thereby improving overall training efficiency. 展开更多
关键词 Q-learning A*algorithm artificial potential field path planning hybrid algorithm
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Path Planning for Unmanned Surface Vehicles in Dynamic Environments Based on Artificial Potential Field and Global Guided Reinforcement Learning 认领 引用 被引量：2
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作者 Shanqiang Li Chaoxi Li 《哈尔滨工程大学学报（英文版）》 CSCD 2026年第2期575-586,共12页
For unmanned surface vehicles(USVs),how to find an effective,feasible path that substantially improves mission success rates and time efficiency in dynamic marine environments is a critical issue.To address the path p... For unmanned surface vehicles(USVs),how to find an effective,feasible path that substantially improves mission success rates and time efficiency in dynamic marine environments is a critical issue.To address the path planning problem for USVs using deep reinforcement learning(DRL)in dynamic ocean environments,an improved algorithm based on Deep Q-Networks(DQN)is proposed,which is called Fast Guided Deep Q-Network Algorithm(FG-DQN).This algorithm combines DQN with the artificial potential field(APF)method and uses the A*algorithm to initialize a guiding path in a global static environment and to provide prior knowledge for the USVs.Additionally,the configuration of the reward function using APF and the guiding path effectively reduces the frequency of random movements during the early exploration phase of the DQN algorithm,which accelerates convergence,improves the computational efficiency of path planning,and increases path safety.Finally,the performance of the presented algorithm is validated through experiments in a 2D environment.Compared with traditional reinforcement learning methods such as Q-learning and Sarsa,as well as the original DQN algorithm,FG-DQN is more effective for USV path planning. 展开更多
关键词 Deep reinforcement learning Path planning Unmanned surface vehicles Fast guided deep Q-Network algorithm
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Structure design of oxide path mechanism-based electrocatalysts for enhanced oxygen evolution reaction performance 认领 引用 被引量：1
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作者 Jin Yang Shengbo Sang Meiling Wang 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2026年第2期464-483,I0011,共20页
The oxygen evolution reaction(OER)suffers from sluggish kinetics,necessitating efficient electrocatalysts to reduce overpotentials in water splitting.Currently recognized OER mechanisms primarily include the adsorbate... The oxygen evolution reaction(OER)suffers from sluggish kinetics,necessitating efficient electrocatalysts to reduce overpotentials in water splitting.Currently recognized OER mechanisms primarily include the adsorbate evolution mechanism(AEM),lattice oxygen mechanism(LOM),and oxide path mechanism(OPM).Compared to AEM,limited by scaling relationships,and LOM,constrained by stability issues,the OPM offers a promising alternative by enabling direct O-O bond formation via dual active sites,thus bypassing*OOH intermediates and lattice O involvement and achieving a balance between activity and durability.However,activating the OPM process requires precise control over the spatial and electronic structure of active sites,making the design of OPM-based catalysts challenging.While previous reviews have focused on homo/heteronuclear diatomic perspectives of OPM-based catalysts,it is urgent to systematically summarize design strategies to provide a rational reference for their development.Herein,a review of design strategies for OPM-based OER catalysts across three scales is comprehensively presented,including in-situ engineering,doping-enabled sites reconstruction,and introducing new sites for nanoparticles,direct synthesis or post-treatments for molecular catalysts,and doping or template strategies for atom pairs or arrays.The unique advantage of atom arrays is also highlighted,and their future research directions and possible strategies are discussed.This review provides a systematic summary and forward-looking perspectives for rationally designing high-performance OPM-based OER catalysts. 展开更多
关键词 Oxygen evolution reaction Oxide path mechanism Dual sites Nanoparticle catalysts Molecular catalysts Atom arrays Design strategies
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Path planning of autonomous underwater vehicle for data collection of the Internet of everything 认领 引用
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作者 Desheng Chen Meng Xi +3 位作者 Jiabao Wen Jingyi He Huiao Dai Wenjie Li 《Digital Communications and Networks》 SCIE EI CSCD 2026年第3期520-529,共10页
Autonomous Underwater Vehicle(AUV)has become an important tool to accomplish various path planning tasks due to its high intelligence and good maneuverability.Aiming at the problem of data collection at underwater Int... Autonomous Underwater Vehicle(AUV)has become an important tool to accomplish various path planning tasks due to its high intelligence and good maneuverability.Aiming at the problem of data collection at underwater Internet of Everything(IoE)nodes,this paper constructs a complex 3D marine environment based on real marine current data,and proposes a path planning algorithm based on reinforcement learning to ensure that the AUV completes the data collection with a short path length.In particular,in order to address the problem of complex path planning tasks,the Parallel Dense neural Network(PDNet)is proposed to improve the performance of the agent by extracting the core features of the input state.In addition,to simplify the reward shaping,we constructed a marine environment with sparse rewards.Sparse rewards can greatly interfere with the agent’s exploration and learning.To solve the sparse reward problem,the Hindsight Experience Replay(HER)is introduced,which not only solves the sparse reward problem,but also improves the sampling efficiency and convergence of the algorithm. 展开更多
关键词 Internet of everything Autonomous underwater vehicles Path planning Deep reinforcement learning
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I-AOMDV:QoS-Aware Multipath Routing Protocol for Enhanced in Dynamic Multi-Node Vehicle Area Network 认领 引用
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作者 Zhu Mingqiang Zhou Ying +4 位作者 Chu Jianxiang Chen Ziyang Ai Huilin Li Jundi Han Jinze 《China Communications》 SCIE EI CSCD 2026年第3期286-297,共12页
In vehicular networking applications,Mobile Ad hoc networks(MANETs)enable dynamic,infrastructure-free connectivity for multi-node mobile scenarios.Frequent topology changes,however,challenge routing protocols in deliv... In vehicular networking applications,Mobile Ad hoc networks(MANETs)enable dynamic,infrastructure-free connectivity for multi-node mobile scenarios.Frequent topology changes,however,challenge routing protocols in delivering quality of service(QoS)for diverse applications.We propose inhanced Ad-hoc on-demand distance vector multipath(I-AOMDV),an enhanced multipath routing protocol using a primary-backup strategy to meet stringent QoS demands in dynamic vehicular environments.Whereas AOMDV relies on hop count,I-AOMDV integrates hop count,bandwidth,and path stability into a QoS-aware framework for optimized path selection.Extensive NS-2 simulations demonstrate that IAOMDV surpasses AOMDV under high mobility,improving data packet delivery by up to 22%and cutting voice service latency by 8–15%,even in high-mobility scenarios.By addressing vehicular networking needs for latency,reliability,and bandwidth,I-AOMDV delivers a scalable,efficient routing solution. 展开更多
关键词 mobile ad hoc networks multipath routing path selection primary-cackup strategy
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Stress-path dependency of rock shear strength influencedby shear surface integrity:Experimental and numerical investigations 认领 引用
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作者 Tao Li Qiang Zhang +3 位作者 Guilei Han Hongying Wang Linpo Shi Sizhe Ye 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2026年第2期1073-1089,共17页
Excavation causes stress redistribution and affects the stress path during the shearing process of rock.The shear strength of rock varies under different stress paths,and the presence of defects reduces the shear stre... Excavation causes stress redistribution and affects the stress path during the shearing process of rock.The shear strength of rock varies under different stress paths,and the presence of defects reduces the shear strength.To further investigate this phenomenon,this study investigates the shear behaviour of rocks with different shear surface integrities under the influenceof different stress paths through laboratory tests and numerical simulations.The results indicate that the shear strength depends on the stress path and a decrease in the shear surface integrity reduces the degree of dependence.The cohesion and friction angle of the Mohr‒Coulomb criterion decrease with weakening of the shear surface integrity.For different stress paths,the direct shear strength is always greater than that of other shear stress paths.The pattern of changes in the acoustic emission count and cumulative count indirectly reflectsthe above findings.Numerical simulations further indicate that the different principal stress states and normal suppression effects during the shearing process lead to changes in the factors of crack propagation,resulting in different mechanical behaviours under various stress paths.For rocks with different integrity levels,the main reason for the different path dependences of shear strength is that the size of the area affected by shear is different.Shear failure will concentrate on the shear plane when the normal inhibition effect is greater.This study explores the mechanism of rock shear behaviour,providing a theoretical basis for establishing more accurate constitutive models and strength criteria. 展开更多
关键词 Rock integrity Stress path Shear strength Crack propagation Principal stress state
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Vacancy-single-atom dual regulation unlocking lattice-oxygen activation pathway driving a leap in alkaline overall water-splitting performance 认领 引用
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作者 Yun Zhao Xianju Leng +4 位作者 Jiaqian Guan Wentao Ding Yu Zhu Sheng Han Jibo Jiang 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2026年第5期631-643,I0015,共13页
Activating lattice oxygen to directly participate in the oxygen evolution reaction(OER)has emerged as a highly efficient strategy to overcome conventional catalytic bottlenecks,while the dynamic switching of reaction ... Activating lattice oxygen to directly participate in the oxygen evolution reaction(OER)has emerged as a highly efficient strategy to overcome conventional catalytic bottlenecks,while the dynamic switching of reaction pathways is influenced by electronic structure modulation that induces lattice oxygen activation.Using NiFe Prussian blue analogues(PBAs)as a model platform,this study proposes a vacancysingle atom synergistic strategy that couples cyanide vacancies(VCN)with Ru single atoms.Experiments demonstrate that pristine NiFe PBA rapidly reconfigures into NiFeOOH upon potential application,following the conventional adsorbed species evolution mechanism(AEM).Following synergistic design,the lattice oxygen-mediated pathway(LOM)is activated,with electrochemical metrics indicating substantially enhanced performance.The resulting Ru-PBA-VCN/MX material simultaneously functions as both cathode and anode,exhibiting a low cell voltage of 1.53 V at a current density of 10 mA cm-2.Density functional theory(DFT)calculations further elucidate that the dual modification tunes the electronic structure,compressing the free-energy barrier of the OER rate-determining step to 1.64 eV,while simultaneously weakening the*OH/*OOH linear-scaling constraint,thereby enabling stable release of lattice oxygen.This synergistic effect overcomes the inherent linear proportional limitations of AEM,providing a novel blueprint for designing high-performance LOM catalysts. 展开更多
关键词 Reaction path switching LOM Single atom Cyano-vacancies Overall water splitting Theoretical calculations
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Exploring the Temporal Degradation and Drift of AS Path Inference 认领 引用
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作者 Xionglve Li Changsheng Hou +5 位作者 Yuzhou Huang Zhenyu Qiu Gang Hu Bingnan Hou Wei Dong Zhiping Cai 《Computers, Materials & Continua》 SCIE EI 2026年第8期833-853,共21页
The Internet inter-domain paths,i.e.,the AS paths,are important for network management,traffic engineering,and security.Due to business confidentiality,security,and privacy,the AS path information is non-public.Due to... The Internet inter-domain paths,i.e.,the AS paths,are important for network management,traffic engineering,and security.Due to business confidentiality,security,and privacy,the AS path information is non-public.Due to limited measurement resources,obtaining AS path information by measurement-based approaches is not scalable.Therefore,path inference approaches are proposed to broaden the availability of path information.These approaches assume that AS paths remain stable over a certain period of time,yet conflicting research findings question this assumption.Furthermore,the duration of the“certain period of time”is not clearly defined.Thus,we aim to address the following question:“How do the performance and temporal drift of path inference approaches evolve over time?”In this paper,we conduct a quantitative validation study and a temporal drift analysis to examine the evolution of AS path inference performance over time.The quantitative validation study shows that the minimal performance degradation is only 2.09%over eight weeks.The temporal drift analysis shows that,among the three evaluated methods,KnownPath exhibits the slowest drift,GMPI shows a moderate drift rate,and ProbInfer drifts the fastest under the current decision rule.The results provide preliminary evidence on how historical data can be leveraged despite limited measurement resources and can inform refresh-frequency decisions for path inference services under computational constraints. 展开更多
关键词 Network measurement AS path inference temporal drift
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RRT*-GSQ:A hybrid sampling path planning algorithm for complex orchard scenarios 认领 引用
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作者 ZHU Qingzhen ZHAO Jiamuyang +1 位作者 DAI Xu YU Yang 《农业工程学报》 EI CAS CSCD 北大核心 2026年第3期13-25,共13页
Traditional sampling-based path planning algorithms,such as the rapidly-exploring random tree star(RRT*),encounter critical limitations in unstructured orchard environments,including low sampling efficiency in narr... Traditional sampling-based path planning algorithms,such as the rapidly-exploring random tree star(RRT*),encounter critical limitations in unstructured orchard environments,including low sampling efficiency in narrow passages,slow convergence,and high computational costs.To address these challenges,this paper proposes a novel hybrid global path planning algorithm integrating Gaussian sampling and quadtree optimization(RRT*-GSQ).This methodology aims to enhance path planning by synergistically combining a Gaussian mixture sampling strategy to improve node generation in critical regions,an adaptive step-size and direction optimization mechanism for enhanced obstacle avoidance,a Quadtree-AABB collision detection framework to lower computational complexity,and a dynamic iteration control strategy for more efficient convergence.In obstacle-free and obstructed scenarios,compared with the conventional RRT*,the proposed algorithm reduced the number of node evaluations by 67.57%and 62.72%,and decreased the search time by 79.72%and 78.52%,respectively.In path tracking tests,the proposed algorithm achieved substantial reductions in RMSE of the final path compared to the conventional RRT*.Specifically,the lateral RMSE was reduced by 41.5%in obstacle-free environments and 59.3%in obstructed environments,while the longitudinal RMSE was reduced by 57.2%and 58.5%,respectively.Furthermore,the maximum absolute errors in both lateral and longitudinal directions were constrained within 0.75 m.Field validation experiments in an operational orchard confirmed the algorithm's practical effectiveness,showing reductions in the mean tracking error of 47.6%(obstacle-free)and 58.3%(with obstructed),alongside a 5.1%and 7.2%shortening of the path length compared to the baseline method.The proposed algorithm effectively enhances path planning efficiency and navigation accuracy for robots,presenting a superior solution for high-precision autonomous navigation of agricultural robots in orchard environments and holding significant value for engineering applications. 展开更多
关键词 robot path planning orchard improved RRT*algorithm Gaussian sampling autonomous navigation
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Cooperative coverage path planning of multiple underwater gliders considering sonar detection performance and energy efficiency 认领 引用
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作者 Hao Hu Tonghao Wang +1 位作者 Yang Cao Xingguang Peng 《Defence Technology（防务技术）》 SCIE EI CAS CSCD 2026年第7期198-215,共18页
This paper proposes a Cooperative Coverage Path Planning method for Multiple Underwater Gliders(MUG-CCPP)that considers sonar detection performance and energy efficiency.Unlike traditional phased methods that require ... This paper proposes a Cooperative Coverage Path Planning method for Multiple Underwater Gliders(MUG-CCPP)that considers sonar detection performance and energy efficiency.Unlike traditional phased methods that require task allocation or area partitioning,our method directly optimizes collaborative paths to complete coverage tasks.We establish a regional detection range model for the sonar by combining environmental data(temperature,salinity,depth)with the Bellhop3D acoustic model and the sonar equation.To balance coverage rate and energy consumption,we design a two-stage fitness function.The first stage guarantees feasible solutions that satisfy coverage rate constraints while accounting for invalid and overlapping coverage,path intersections,energy consumption,and safety.The second stage minimizes energy consumption within the coverage area.Furthermore,we present a Discrete Search-Assisted(DSA)strategy to improve initial solution quality and coverage ordering.Simulation results show that our MUG-CCpP method outperforms a state-of-the-art phased method,achieving higher coverage rates and greater energy efficiency,thereby offering a practical solution for coverage detection tasks. 展开更多
关键词 Underwater glider Coverage path planning Sonar detection performance Fitness function Discrete search-assisted
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Motion Strategy and Control Parameters Optimization for an Underwater Glider Based on 3D Dubins Paths 认领 引用
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作者 HOU Dong-bo CAO Wei +1 位作者 WANG Wen-jun WANG Cong 《China Ocean Engineering》 SCIE EI CSCD 2026年第3期604-618,共15页
This research examines the optimization of motion strategy and control parameters for an Autonomous Underwater Glider(AUG)navigating between two points.For scenarios with specified initial position,target position,and... This research examines the optimization of motion strategy and control parameters for an Autonomous Underwater Glider(AUG)navigating between two points.For scenarios with specified initial position,target position,and heading,this study proposes a three-dimensional multimodal path planning methodology based on the 3D-Dubins path,ensuring both task fulfillment and motion feasibility within AUG dynamics constraints.The path planning approach incorporates ocean current interference and utilizes task objectives and control parameters as inputs.It systematically calculates information including horizontal Dubins type,vertical plane motion modes,and turning point depths to generate the path planning solution.The motion control strategy implements initial control parameter values and utilizes depth measurements as evaluation criteria.Through control parameter adjustments,the strategy facilitates tracking of the designated path.This control approach requires minimal feedback information,with computations executable by shore-based facilities,thereby reducing computational and measurement demands on the AUG and enhancing operational reliability.For specified task objectives,multi-objective optimization of control parameters is conducted using the proposed path planning method and motion control strategy,yielding optimized control parameters and corresponding motion control strategies for various operational requirements. 展开更多
关键词 underwater glider Dubins paths motion strategy parameters optimization energy consumption
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Pile installation effects in natural soft clays:A semi-analytical solution using strain path method 认领 引用
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作者 Liang Li Pan Zhou +3 位作者 Jingpei Li Seyedmohsen Miraei Peng Feng Mingdong Wei 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2026年第1期728-744,共17页
This paper develops a semi-analytical solution for pile penetration in natural soft clays using the strain path method(SPM).The stress-strain behavior of soils is characterized by the S-CLAY1S model,which can capture ... This paper develops a semi-analytical solution for pile penetration in natural soft clays using the strain path method(SPM).The stress-strain behavior of soils is characterized by the S-CLAY1S model,which can capture the anisotropic evolution and destructuring nature of soft clays.By integrating the S-CLAY1S model into the theoretical framework of the SPM,a set of ordinary differential equations is formulated with respect to the vertical coordinate of soil particles.The distribution of excess pore water pressure(EPWP)following pile installation is approximated through one-dimensional(1D)radial integration around the pile shaft.The distribution of stresses and EPWP,along with the evolution of fabric anisotropy within the soil surrounding the pile,is presented to illustrate the response of pile penetration in natural soft clays.The proposed solution is validated against existing theoretical solutions using the SPM and cavity expansion method(CEM),along with experimental data.The findings demonstrate that the SPM reveals lower radial effective stresses and EPWP at the pile shaft than that of CEM.Pile penetration alters the soil's anisotropic properties,inducing rotational hardening and affecting post-installation stress distribution.Soil destructuration eliminates bonding among particles near the pile,resulting in a complete disruption of soil structure at the pile surface,which is particularly pronounced for higher initial soil structure ratios.Minimal variation was observed in the three principal stresses and shear stress on the cone side surface as the angle increased from 18°to 60°,except for a slight reduction in EPWP. 展开更多
关键词 Pile penetration Strain path method Natural soft clays Anisotropy evolution Destructuration
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Optimization of Flying Ad Hoc Network Topology and Collaborative Path Planning for Multiple UAVs 认领 引用
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作者 Ming He Peizhao Wang +2 位作者 Haihua Chen Bin Sun Hongpeng Wang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第6期1339-1352,共14页
Multiple unmanned aerial vehicles(UAVs)play a vital role in monitoring and data collection in wide area environments with harsh conditions.In most scenarios,issues such as real-time data retrieval and real-time UAV po... Multiple unmanned aerial vehicles(UAVs)play a vital role in monitoring and data collection in wide area environments with harsh conditions.In most scenarios,issues such as real-time data retrieval and real-time UAV positioning are often disregarded,essentially neglecting the communication constraints.In this paper,we comprehensively address both the coverage of the target area and the data transmission capabilities of the flying ad hoc network(FANET).The data throughput of the network is therefore maximized by optimizing the network topology and UAV trajectories.The resultant optimization problem is effectively solved by the proposed reinforcement learning-based trajectory planning(RL-TP)algorithm and the convex-based topology optimization(C-TOP)algorithm sequentially.The RL-TP optimizes the UAV paths while considering the constraints of FANET.The C-TOP maximizes the data throughput of the network while simultaneously constraining the neighbors and transmit powers of the UAVs,which is shown to be a convex problem that can be efficiently solved in polynomial time.Simulations and field experimental results show that the proposed optimization strategy can effectively plan the UAV trajectories and significantly improve the data throughput of the FANET over the adaptive local minimum spanning tree(A-LMST)and cyclic pruning-assisted power optimization(CPAPO)methods. 展开更多
关键词 Convex optimization flying ad hoc network (FANET) path planning reinforcement learning (RL) topology control
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Adaptive Path-Planning for Autonomous Robots:A UCH-Enhanced Q-Learning Approach 认领 引用
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作者 Wei Liu Ruiyang Wang Guangwei Liu 《Computers, Materials & Continua》 SCIE EI 2026年第2期731-753,共23页
Q-learning is a classical reinforcement learning method with broad applicability.It can respond effectively to environmental changes and provide flexible strategies,making it suitable for solving robot path-planning p... Q-learning is a classical reinforcement learning method with broad applicability.It can respond effectively to environmental changes and provide flexible strategies,making it suitable for solving robot path-planning problems.However,Q-learning faces challenges in search and update efficiency.To address these issues,we propose an improved Q-learning(IQL)algorithm.We use an enhanced Ant Colony Optimization(ACO)algorithmto optimizeQtable initialization.We also introduce the UCH mechanism to refine the reward function and overcome the exploration dilemma.The IQL algorithm is extensively tested in three grid environments of different scales.The results validate the accuracy of themethod and demonstrate superior path-planning performance compared to traditional approaches.The algorithm reduces the number of trials required for convergence,improves learning efficiency,and enables faster adaptation to environmental changes.It also enhances stability and accuracy by reducing the standard deviation of trials to zero.On grid maps of different sizes,IQL achieves higher expected returns.Compared with the original Q-learning algorithm,IQL improves performance by 12.95%,18.28%,and 7.98% on 10*10,20*20,and 30*30 maps,respectively.The proposed algorithm has promising applications in robotics,path planning,intelligent transportation,aerospace,and game development. 展开更多
关键词 Path planning IQL algorithms UCH mechanism
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Stress path effect and loading failure mechanism of surrounding rock in steeply dipping pitching oblique stope 认领 引用
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作者 HUANG Bao-fa XIE Pan-shi +6 位作者 WU Yong-ping ZHANG Xi ZHAO Wei-gang DUAN Si-yu LI Guo-xin YI Lei-lei XU Hui 《Journal of Central South University》 SCIE EI CAS CSCD 2026年第6期2627-2650,共24页
Discovering and revealing the stress path effect and load failure mechanism of surrounding rock in steeply dipping pitching oblique stope is the basis for realizing safe and efficient mining of such coal seams.Based o... Discovering and revealing the stress path effect and load failure mechanism of surrounding rock in steeply dipping pitching oblique stope is the basis for realizing safe and efficient mining of such coal seams.Based on the study of the evolution law of roof caving and filling in pitching oblique stope,the three-dimensional physical simulation experiment,numerical calculation,theoretical analysis and field monitoring are used to reveal the load and instability mechanism of roof rock mass structure in different areas under the non-equilibrium constraint of gangue,and the temporal and spatial evolution law of overburden mining stress in different positions along the strike and tendency of working face is deeply analyzed.The results show that there are obvious regional characteristics of roof fracture and migration in steeply dipping pitching oblique stope.The lower fracture lags behind the middle and upper parts,and the effective support area of filling gangue is about 2/5 of the length of working face.The basic roof stress evolves from a wedge to an inverted trapezoid.The roof strata are damaged by tension and compression in the middle and upper regions,and by compression in the lower region.With the advancement of the working face,the magnitude and direction of the three-dimensional mining stress of the overlying rock have changed significantly.The asymmetric deflection transfer of the stress path leads to the failure and instability of the rock layer inside the bearing arch,and the bearing arch increases first and then tends to be stable.The peak abutment pressure of surrounding rock has a cumulative effect.The stress concentration in the lower area has a lag.The peak abutment pressure in the upper area is smaller than that in the true inclined working face,and the stability of the roof is enhanced.The peak values of the bending moment in the upper,middle and lower regions of the inclination are 483.71,306.95 and 230.26 kN·m,respectively,and the peak values are located at 2−3 m in front of the coal wall.The relationship between the'support-surrounding rock'of the stope presents significant regional characteristics.The research results have important guiding significance for the stability control of surrounding rock and safe and efficient mining of scarce high-quality coal seams,such as steeply dipping coal seams. 展开更多
关键词 steeply dipping coal seam pitching oblique stope gangue sliding filling stress path fracture instability
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Innovation-driven disturbance rejection enhancement for robust AUV path tracking 认领 引用
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作者 Wanping Song Mingwei Sun +3 位作者 Zengqiang Chen Qinglin Sun Mikulas Huba Pavol Bistak 《Control Theory and Technology》 EI CSCD 2026年第2期214-229,共16页
Unknown external disturbances and hydrodynamic uncertainties pose significant challenges to accurate path tracking of autonomous underwater vehicles(AUVs).To address this problem,a guidance law ensuring trajectory con... Unknown external disturbances and hydrodynamic uncertainties pose significant challenges to accurate path tracking of autonomous underwater vehicles(AUVs).To address this problem,a guidance law ensuring trajectory convergence is proposed by incorporating position error and AUV dynamics.A deviation compensation disturbance rejection(DCDR)controller is developed by introducing an independent tunable gain to decouple disturbance rejection from state observer dynamics,thereby enabling separate design and coordination of nominal control and robust enhancement.The transfer function-based DCDR implementation is derived to demonstrate a systematic parameter tuning guideline,and the closed-loop stability is established through invariant set analysis.The effectiveness of the proposed method is validated through straight and circular path tracking simulations with and without wave-induced external disturbances.By maintaining an explicit control structure,the proposed DCDR can achieve improved tracking performance and reduced control effort compared with the linear active disturbance rejection control(LADRC)and the compensation function observer-based controller(CFO-C). 展开更多
关键词 Autonomous underwater vehicles Path tracking Active disturbance rejection control Compensation function observer
Dynamic tuning of acidic oxygen evolution reaction pathways in Ru catalysts via Cu-induced surface restructuring 认领 引用
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作者 Hyunseok Yoon Hee Jo Song +7 位作者 Yumin Park Andi Haryanto Dohun Kim Kyuri Cho Chanyeon Kim Wooyul Kim Chan Woo Lee Dong-Wan Kim 《Chinese Journal of Catalysis》 SCIE EI CAS CSCD 2026年第4期363-375,共13页
Achieving both high activity and long-term stability for the oxygen evolution reaction(OER)in acidic media remains a critical challenge for proton exchange membrane water electrolyzers(PEMWEs).In this study,we propose... Achieving both high activity and long-term stability for the oxygen evolution reaction(OER)in acidic media remains a critical challenge for proton exchange membrane water electrolyzers(PEMWEs).In this study,we proposed a Cu-incorporated ruthenium(Ru)catalyst(CuRu-250)that exhibited superior performance via dynamic surface modulation during operation.Rather than serving solely as a static dopant,Cu actively influenced the catalyst surface by undergoing partial dissolution and inducing surface restructuring.This dynamic behavior enabled pathway tuning from the adsorbate evolution mechanism to the oxide path mechanism,enhancing the intermediate turnover and suppressing the overoxidation of Ru.Consequently,CuRu-250 demonstrated markedly improved durability and competitive activity compared to undoped Ru and commercial RuO2.Single-cell PEMWE tests validated its catalytic performance under realistic conditions.These findings highlight the role of active dopant behavior in tuning acidic OER pathways and improving electrochemical resilience,thus offering a practical strategy for advanced catalyst design. 展开更多
关键词 Ruthenium Dynamic surface restructuring Oxygen evolution reaction Proton exchange membrane water electrolyzer Oxide path mechanism
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From variety improvement to a field management system:dual-path breeding of Zhongtang and Zhongfu for modern sugarcane production 认领 引用
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作者 Peilin Wang Qibin Wu +6 位作者 Benpeng Yang Wenwei Cai Yimei Gan Zhengying Cao Yuanli Wu Yuebin Zhang Youxiong Que 《Tropical Plants》 CSCD 2026年第1期4-8,共5页
Against the backdrop of intensifying global competition in the sugar industry and accelerating domestic agricultural transformation,the Chinese sugarcane industry faces rising production costs and urgent labor shortag... Against the backdrop of intensifying global competition in the sugar industry and accelerating domestic agricultural transformation,the Chinese sugarcane industry faces rising production costs and urgent labor shortages.In response,sugarcane(Saccharum officinarum)germplasm innovation was conducted to develop high-yield,high-sucrose cultivars with enhanced stress tolerance and suitability for mechanization.This has driven the development of the‘Zhongtang'(ZT)and‘Zhongfu'(ZF)cultivars in the Sugarcane Research Center of the Chinese Academy of Tropical Agricultural Sciences.Among these,Zhongtang 3(ZT3)has emerged as a representative cultivar,demonstrating an increase in yield and improved mechanization compatibility,making it ideal for large-scale mechanical harvesting.Zhongfu 1(ZF1),a space radiation-induced mutant from the Shenzhou-10 spacecraft mission,offers a distinct yet complementary technological pathway.Recently,ZT3 and ZF1,integrated with solutions that combine their superior varietal traits,mechanization,and sustainable cultivation principles,have been widely adopted to drive the modernization of the sugarcane industry.Together,the elite sugarcane cultivars,along with high-efficiency cultivation,are expected to systemically address these challenges in the Chinese sugarcane industry. 展开更多
关键词 Zhongtang high yield global competition Zhongfu variety improvement modern sugarcane production field management system dual path breeding
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