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Semi-supervised Risk Assessment Research for Intelligent Vehicles Inspired by Collective Biological Risk-avoidance Behaviors 认领 引用
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作者 Hongyu Hu Zhonghua Xiong +2 位作者 Zhengyi Li Tianjun Sun Rui Ran 《Journal of Bionic Engineering》 SCIE EI CSCD 2026年第1期225-238,共14页
To address the critical challenge of risk perception and assessment for autonomous vehicles in dynamic interactive envi-ronments,this study proposes a semi-supervised spatiotemporal interaction risk cognition network ... To address the critical challenge of risk perception and assessment for autonomous vehicles in dynamic interactive envi-ronments,this study proposes a semi-supervised spatiotemporal interaction risk cognition network with attention mecha-nism(SS-SIRCN),inspired by the behavioral adaptation patterns of biological groups under external threats.First,by thoroughly analyzing the dynamic interaction characteristics exhibited by typical biological collectives when exposed to risk,the study reveals the underlying patterns of trajectory changes influenced by external danger.Then,an attention-based spatiotemporal risk cognition network is designed to establish a mapping between driving behavior features and potential driving risks.Finally,a semi-supervised learning framework is employed to enable risk assessment for autono-mous vehicles using only a small amount of labeled data.Experimental results on real-world vehicle trajectory datasets demonstrate that the proposed method achieves a risk prediction accuracy of 90.76%,outperforming other baseline models in performance. 展开更多
关键词 Escape behaviour Predator avoidance Brain-like intelligent decision-making Attention mechanism Driving risk Automated driving
A Bio-inspired Bubble Artificial Muscles and TacTip Perception-driven Tri-legged Robot for Obstacle Avoidance 认领 引用
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作者 Chaoqun Xiang Zhengwei Zhong +3 位作者 Wenqiang Wu Xiaocong Chen Yisheng Guan Tao Zou 《Journal of Bionic Engineering》 SCIE EI CSCD 2026年第1期175-191,共17页
Legged robots have considerable potential for traversing unstructured situations;nonetheless,their inflexible frameworks often constrain adaptability and obstacle negotiation.The study article presents a revolutionary... Legged robots have considerable potential for traversing unstructured situations;nonetheless,their inflexible frameworks often constrain adaptability and obstacle negotiation.The study article presents a revolutionary Soft Tri-Legged Robot(STLR)that improves movement and obstacle-avoidance skills by using a bio-inspired pneumatic artificial muscle(Bubble Artificial Muscles)and a bio-inspired tactile sensor(TacTip).The STLR is activated by BAMs,which are flexible,pneu-matic-driven actuators that provide fine control over forward,backward,and steering movements.Obstacle identification and avoidance are facilitated by the TacTip sensor,which delivers tactile input for traversing unstructured terrains.We delineate the mechanical features of the BAMs,assess the functionality of the robot's legs,and elaborate on the incorpora-tion of the tactile sensing system.Experimental results demonstrate that the STLR can effectively achieve multi-directional flexible movement and obstacle avoidance through a cross-modal perception-actuation mechanism.This study highlights the promise of soft robotics for search and rescue,medical aid,and autonomous exploration,while delineating difficulties and opportunities for future improvements in functionality and efficiency. 展开更多
关键词 Legged robot Bio-inspired bubble artificial muscles Bio-inspired TacTip sensor Foot tactile perception Obstacle avoidance
An Optimal Acceleration Control for Collision Avoidance in VANETs Using Convex Optimization 认领 引用
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作者 Awais Ahmad Fakhri Alam Khan +4 位作者 Awais Ahmad Gautam Srivastava Syed Atif Moqurrab Abdul Razaque Dina S.M.Hassan 《Computers, Materials & Continua》 SCIE EI 2026年第6期551-581,共31页
Collision avoidance is recognized as a critical challenge in Vehicular Ad-Hoc Networks(VANETs),which demand real-time decision-making.It plays a vital role in ensuring road safety and traffic efficiency.Traditional ap... Collision avoidance is recognized as a critical challenge in Vehicular Ad-Hoc Networks(VANETs),which demand real-time decision-making.It plays a vital role in ensuring road safety and traffic efficiency.Traditional approaches like rule-based systems and heuristic methods fail to provide optimal solutions in dynamic and unpredictable traffic scenarios.They cannot balance multiple objectives like minimizing collision risk,ensuring passenger comfort,and optimizing fuel efficiency,leading to suboptimal performance in real-world conditions.To tackle collision avoidance,this paper introduces a novel approach by defining the issue as an optimal control problem and solving it using the Convex Optimization model,which results in autonomous braking and acceleration control in smart vehicles.The model begins by collecting real-time vehicle data from its environment,which includes speed,position,and distance.It then uses this information to generate optimal driving profiles for each vehicle and calculate optimal responses.The informational data guides the vehicle to adjust its braking and acceleration autonomously,ensuring that safe distances are maintained among vehicles without compromising comfort.This approach empowers individual vehicles to make real-time decisions independently and adapt swiftly to changing traffic conditions.The performance of the proposed method is evaluated using a simulation study in MATLAB using the CVX optimization toolbox,comparing Adaptive Cruise Control(ACC)and Fuzzy Logic-Based Collision Avoidance(FLCA)using various performance metrics.Compared to these baseline protocols,our approach achieves a higher success rate in preventing collisions by maintaining smoother acceleration profiles and lower fuel consumption,yielding up to a 32%reduction in collision likelihood and a 19%improvement in fuel efficiency.Additionally,unlike existing rule-based and model-predictive approaches,the proposed method introduces a unified cost function that jointly minimizes collision risk,acceleration jerk,and energy consumption in decentralized VANET scenarios.This integration enables real-time decision-making while maintaining safety,comfort,and efficiency across varying traffic densities. 展开更多
关键词 Vehicular ad hoc networks(VANETs) collision avoidance convex optimization autonomous vehicles optimal control
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Design of a Patrol and Security Robot with Semantic Mapping and Obstacle Avoidance System Using RGB-D Camera and LiDAR 认领 引用
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作者 Shu-Yin Chiang Shin-En Huang 《Computers, Materials & Continua》 SCIE EI 2026年第4期1735-1753,共19页
This paper presents an intelligent patrol and security robot integrating 2D LiDAR and RGB-D vision sensors to achieve semantic simultaneous localization and mapping(SLAM),real-time object recognition,and dynamic obsta... This paper presents an intelligent patrol and security robot integrating 2D LiDAR and RGB-D vision sensors to achieve semantic simultaneous localization and mapping(SLAM),real-time object recognition,and dynamic obstacle avoidance.The system employs the YOLOv7 deep-learning framework for semantic detection and SLAM for localization and mapping,fusing geometric and visual data to build a high-fidelity 2D semantic map.This map enables the robot to identify and project object information for improved situational awareness.Experimental results show that object recognition reached 95.4%mAP@0.5.Semantic completeness increased from 68.7%(single view)to 94.1%(multi-view)with an average position error of 3.1 cm.During navigation,the robot achieved 98.0%reliability,avoided moving obstacles in 90.0%of encounters,and replanned paths in 0.42 s on average.The integration of LiDAR-based SLAMwith deep-learning–driven semantic perception establishes a robust foundation for intelligent,adaptive,and safe robotic navigation in dynamic environments. 展开更多
关键词 RGB-D semantic mapping object recognition obstacle avoidance security robot
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Data driven vehicular heterogeneity based intelligent collision avoidance system for Internet of Vehicles(IoV) 认领 引用 被引量：1
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作者 Iqra Adnan Tariq Umer +3 位作者 Ahmad Arsalan Maryam M.Al Dabel Ali Kashif Bashir Arooj Ansif 《Digital Communications and Networks》 SCIE EI CSCD 2026年第1期180-197,共18页
The Internet of Vehicles(IoV)is an emerging technology that aims to connect vehicles,infrastructure,and other devices to enable intelligent transportation systems.One of the key challenges in IoV is to ensure safe and... The Internet of Vehicles(IoV)is an emerging technology that aims to connect vehicles,infrastructure,and other devices to enable intelligent transportation systems.One of the key challenges in IoV is to ensure safe and efficient communication among vehicles of different types and capabilities.This paper proposes a data-driven vehicular heterogeneity-based intelligent collision avoidance system for IoV.The system leverages Vehicle-to-Vehicle(V2V)and Vehicle-to-Infrastructure(V2I)communication to collect real-time data about the environment and the vehicles.The data is collected to acknowledge the heterogeneity of vehicles and human behavior.The data is analyzed using machine learning algorithms to identify potential collision risks and recommend appropriate actions to avoid collisions.The system takes into account the heterogeneity of vehicles,such as their size,speed,and maneuverability,to optimize collision avoidance strategies.The proposed system is experimented with real-time datasets and compared with existing collision avoidance systems.The results are shown using the evaluation metrics that show the proposed system can significantly reduce the number of collisions and improve the overall safety and efficiency of IoV with an accuracy of 96.5%using the SVM algorithm.The trial outcomes demonstrated that the new system,incorporating vehicular,weather,and human behavior factors,outperformed previous systems that only considered vehicular and weather aspects.This innovative approach is poised to lead transportation efforts,reducing accident rates and improving the quality of transportation systems in smart cities.By offering predictive capabilities,the proposed model not only helps control accident rates but also prevents them in advance,ensuring road safety. 展开更多
关键词 Internet of Vehicles Collision avoidance Machine learning Traffic safety Autonomous vehicles Vehicular networks Vehicular heterogeneity Smart transportation Traffic modeling
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DFCOA:Distributed Formation Control and Obstacle Avoidance for Multi-UGV Systems 认领 引用
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作者 Md.Faishal Rahaman Xueyuan Li +3 位作者 Muhammad Amjad Ibrahim Gasimove Md.Shariful Islam S.M.Abul Bashar 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第2期922-954,共33页
Researchers are increasingly focused on enabling groups of multiple unmanned vehicles to operate cohesively in complex,real-world environments,where coordinated formation control and obstacle avoidance are essential f... Researchers are increasingly focused on enabling groups of multiple unmanned vehicles to operate cohesively in complex,real-world environments,where coordinated formation control and obstacle avoidance are essential for executing sophisticated collective tasks.This paper presents a Distributed Formation Control and Obstacle Avoidance(DFCOA)framework for multi-unmanned ground vehicles(UGV).DFCOA integrates a virtual leader structure for global guidance,an improved A*path planning algorithm with an advanced cost function for efficient path planning,and a repulsive-force-based improved vector field histogram star(VFH*)technique for collision avoidance.The virtual leader generates a reference trajectory while enabling distributed execution;the improved A*algorithm reduces planning time and number of nodes to determine the shortest path from the starting position to the goal;and the improved VFH*uses 2D LiDAR data with inter-agent repulsive force to simultaneously avoid collision with obstacles and maintain safe inter-vehicle distances.The formation stability of the proposed DFCOA reaches 95.8%and 94.6%in two scenarios,with root mean square(RMS)centroid errors of 0.9516 and 1.0008 m,respectively.Velocity tracking is precise(velocity centroid error RMS of 0.2699 and 0.1700 m/s),and linear velocities closely match the desired 0.3 m/s.Safety metrics showed average collision risks of 0.7773 and 0.5143,with minimum inter-vehicle distances of 0.4702 and 0.8763 m,confirming collision-free navigation of four UGVs.DFCOA outperforms conventional methods in formation stability,path efficiency,and scalability,proving its suitability for decentralized multi-UGV applications. 展开更多
关键词 Formation control obstacle avoidance virtual leader path planning multi UGV collaboration
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Deep reinforcement learning-based adaptive collision avoidance method for UAV in joint operational airspace 认领 引用
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作者 Yan Shen Xuejun Zhang +1 位作者 Yan Li Weidong Zhang 《Defence Technology（防务技术）》 SCIE EI CAS CSCD 2026年第2期142-159,共18页
As joint operations have become a key trend in modern military development,unmanned aerial vehicles(UAVs)play an increasingly important role in enhancing the intelligence and responsiveness of combat systems.However,t... As joint operations have become a key trend in modern military development,unmanned aerial vehicles(UAVs)play an increasingly important role in enhancing the intelligence and responsiveness of combat systems.However,the heterogeneity of aircraft,partial observability,and dynamic uncertainty in operational airspace pose significant challenges to autonomous collision avoidance using traditional methods.To address these issues,this paper proposes an adaptive collision avoidance approach for UAVs based on deep reinforcement learning.First,a unified uncertainty model incorporating dynamic wind fields is constructed to capture the complexity of joint operational environments.Then,to effectively handle the heterogeneity between manned and unmanned aircraft and the limitations of dynamic observations,a sector-based partial observation mechanism is designed.A Dynamic Threat Prioritization Assessment algorithm is also proposed to evaluate potential collision threats from multiple dimensions,including time to closest approach,minimum separation distance,and aircraft type.Furthermore,a Hierarchical Prioritized Experience Replay(HPER)mechanism is introduced,which classifies experience samples into high,medium,and low priority levels to preferentially sample critical experiences,thereby improving learning efficiency and accelerating policy convergence.Simulation results show that the proposed HPER-D3QN algorithm outperforms existing methods in terms of learning speed,environmental adaptability,and robustness,significantly enhancing collision avoidance performance and convergence rate.Finally,transfer experiments on a high-fidelity battlefield airspace simulation platform validate the proposed method's deployment potential and practical applicability in complex,real-world joint operational scenarios. 展开更多
关键词 Unmanned aerial vehicle Collision avoidance Deep reinforcement learning Joint operational airspace Hierarchical prioritized experience replay
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Imitation Learning for Unmanned Aerial Vehicle Obstacle Avoidance Based on Visual Features with DAgger 认领 引用
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作者 Yuqi Yang Mengyun Wang +1 位作者 Yifeng Niu Bo Wang 《Journal of Beijing Institute of Technology》 EI CAS 2026年第1期114-126,共13页
Unmanned aerial vehicles(UAVs)face the challenge of autonomous obstacle avoidance in complex,multi-obstacle environments.Behavior cloning offers a promising approach to rapidly acquire a learning policy from limited e... Unmanned aerial vehicles(UAVs)face the challenge of autonomous obstacle avoidance in complex,multi-obstacle environments.Behavior cloning offers a promising approach to rapidly acquire a learning policy from limited expert demonstrations.However,pure imitation learning inherently suffers from poor exploration and limited generalization,typically necessitating extensive datasets to train competent student policies.We utilize a cross-modal variational autoencoder(CM-VAE)to extract compact features from raw visual inputs and UAV states,which then feed into a policy network.We evaluated our approach in a simulated environment featuring a challenging circular trajectory with eight gate obstacles.The results demonstrate that the policy trained with pure behavior cloning consistently failed.In stark contrast,our DAgger-augmented behavior cloning method successfully traversed all gates without collision.Our findings confirm that DAgger effectively mitigates the shortcomings of behavior cloning,enabling the creation of reliable and sample-efficient navigation policies for UAVs. 展开更多
关键词 imitation learning unmanned aerial vehicle obstacle avoidance DAgger
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BMI and social avoidance:The mediating roles of body dissatisfaction and self-esteem 认领 引用
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作者 Huan Song Yuan Zhao Chenglin He 《Journal of Psychology in Africa》 2026年第2期249-255,共7页
This study aimed to explore the mediating roles of body dissatisfaction and self-esteem on the relationship between body mass index(BMI)and among female college students.Using a cross-sectional study design,669 Chines... This study aimed to explore the mediating roles of body dissatisfaction and self-esteem on the relationship between body mass index(BMI)and among female college students.Using a cross-sectional study design,669 Chinese female college students completed the Body Mass Index,the Body Image States Scale,the Self-Esteem Scale,and the Social Avoidance and Distress Scale.The results showed that body dissatisfaction partially mediated the relationship between BMI and social avoidance.Additionally,body dissatisfaction and self-esteem together formed a serial mediation pathway between BMI and social avoidance.In other words,BMI shows a direct association with social avoidance among female college students,as well as indirect associations through the simple mediation of body dissatisfaction and the serial mediation of body dissatisfaction and self-esteem.Findings suggest that increased body satisfaction and self-esteem can reduce social avoidance among female college students. 展开更多
关键词 College students body mass index body dissatisfaction self-esteem social avoidance
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Research on Collaborative Avoidance Design Technology for Road Horizontal Alignment and Underground Pipelines Based on BIM 认领 引用
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作者 Xiang Zhang 《Journal of World Architecture》 2026年第1期20-27,共8页
Traditional road horizontal alignment design faces bottlenecks such as limited terrain representation,inefficient information updates,and inadequate multi-factor collaboration.Underground pipeline design also encounte... Traditional road horizontal alignment design faces bottlenecks such as limited terrain representation,inefficient information updates,and inadequate multi-factor collaboration.Underground pipeline design also encounters issues of professional fragmentation and frequent conflicts.The lack of coordination between the two leads to construction rework and increased costs.Based on this,this paper first constructs a BIM-based technical system for road horizontal alignment and then explores collaborative avoidance techniques for underground pipelines.Using engineering examples,it investigates the BIM-integrated application of collaborative avoidance between road horizontal alignment and underground pipelines.Through analysis,the paper aims to address the challenges of coordination in road and underground pipeline design,break down professional information barriers,proactively avoid conflicts,and provide technical support and practical references for enhancing the quality and efficiency of municipal engineering design. 展开更多
关键词 BIM Road Horizontal alignment Underground pipeline Collaborative avoidance design technology
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Intelligent sequential multi-impulse collision avoidance method for non-cooperative spacecraft based on an improved search tree algorithm 认领 引用 被引量：3
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作者 Xuyang CAO Xin NING +4 位作者 Zheng WANG Suyi LIU Fei CHENG Wenlong LI Xiaobin LIAN 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2025年第4期378-393,共16页
The problem of collision avoidance for non-cooperative targets has received significant attention from researchers in recent years.Non-cooperative targets exhibit uncertain states and unpredictable behaviors,making co... The problem of collision avoidance for non-cooperative targets has received significant attention from researchers in recent years.Non-cooperative targets exhibit uncertain states and unpredictable behaviors,making collision avoidance significantly more challenging than that for space debris.Much existing research focuses on the continuous thrust model,whereas the impulsive maneuver model is more appropriate for long-duration and long-distance avoidance missions.Additionally,it is important to minimize the impact on the original mission while avoiding noncooperative targets.On the other hand,the existing avoidance algorithms are computationally complex and time-consuming especially with the limited computing capability of the on-board computer,posing challenges for practical engineering applications.To conquer these difficulties,this paper makes the following key contributions:(A)a turn-based(sequential decision-making)limited-area impulsive collision avoidance model considering the time delay of precision orbit determination is established for the first time;(B)a novel Selection Probability Learning Adaptive Search-depth Search Tree(SPL-ASST)algorithm is proposed for non-cooperative target avoidance,which improves the decision-making efficiency by introducing an adaptive-search-depth mechanism and a neural network into the traditional Monte Carlo Tree Search(MCTS).Numerical simulations confirm the effectiveness and efficiency of the proposed method. 展开更多
关键词 Non-cooperative target Collision avoidance Limited motion area Impulsive maneuver model Search tree algorithm Neural networks
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Efficient obstacle avoidance planning for multi-robot suspension system based on a collaborative optimization for force and position 认领 引用 被引量：1
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作者 Xiangtang Zhao Zhigang Zhao +2 位作者 Cheng Su Jiadong Meng Hutang Sang 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2025年第12期135-154,共20页
To avoid collisions between a suspended object,cables,towing robots,and obstacles in the environment in a multi-robot suspension system,obstacle avoidance planning was studied based on a collaborative optimization met... To avoid collisions between a suspended object,cables,towing robots,and obstacles in the environment in a multi-robot suspension system,obstacle avoidance planning was studied based on a collaborative optimization method for force and position.Based on the analysis of the kinematics and dynamics of the system,the inverse kinematics and inverse dynamics of the system are solved using the least variance method.The obstacle avoidance planning is performed in the solved collisionfree feasible space using the stable dung beetle optimization(SDBO)algorithm,which ensures that the suspended object can move stably to the target point in the workspace.The optimal obstacle avoidance trajectory of the multi-robot suspension system can be accurately determined by using the collaborative optimization method for force and position to plan the towing robot and the cable.Finally,the correctness of the obstacle avoidance planning method is verified by simulations.By taking a special scenario,the remarkable findings reveal that the SDBO algorithm outperforms the dung beetle optimization algorithm by reducing the length of the planned trajectory of the suspended object by 14.51%and the height by 79.88%,and reducing the minimum fitness by 95.84%and the average fitness by 94.77%.The results can help the multi-robot suspension system to perform various towing tasks safely and stably,and extend the related planning and control theory. 展开更多
关键词 Suspension system Obstacle avoidance planning Collision-free feasible space Stable dung beetle optimization Collaborative optimization for force and position
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Cooperative Collision Avoidance Control with Relative Velocity Information for Redundant Dual-arm Robotic Manipulators 认领 引用 被引量：1
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作者 Jinyue Liu Chao Xu +2 位作者 Xiaohui Jia Yi Wu Tiejun Li 《Journal of Bionic Engineering》 SCIE EI CSCD 2025年第3期1111-1125,共15页
In this paper,a novel cooperative collision avoidance control strategy with relative velocity information for redundant robotic manipulators is derived to guarantee the behavioral safety of robots in the cooperative o... In this paper,a novel cooperative collision avoidance control strategy with relative velocity information for redundant robotic manipulators is derived to guarantee the behavioral safety of robots in the cooperative operational task.This strategy can generate the collision-free trajectory of the robotic links in real-time,which is to realize that the robot can avoid moving obstacles less conservatively and ensure tracking accuracy of terminal end-effector tasks in performing cooperative tasks.For the case where there is interference between the moving obstacle and the desired path of the robotic end-effector,the method inherits the null-space-based self-motion characteristics of the redundant manipulator,integrates the relative motion information,and uses the improved artificial potential field method to design the control items,which are used to generate the collision avoidance motion and carry out moving obstacles smoothly and less conservatively.At the same time,the strategy maintains the kinematic constraint relationship of dual-arm cooperatives,to meet the real-time collision avoidance task under collaborative tasks.Finally,the algorithm simulation indicates that the method can better ensure the tracking accuracy of the end-effector task and carry out moving obstacles smoothly.The experimental results show that the method can generate the real-time collision-free trajectory of the robot in the cooperative handling task,and the joint movement is continuous and stable. 展开更多
关键词 Redundant dual-arm robotic manipulators Cooperative operational tasks Collision avoidance Relative velocity information
Distributed event-triggered collision avoidance coordinated control for QUAVs based on flexible virtual tubes 认领 引用 被引量：1
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作者 Hongzhen GUO Mou CHEN +1 位作者 Mihai LUNGU Baomin LI 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2025年第2期339-352,共14页
In this paper,a distributed Event-Triggered(ET)collision avoidance coordinated control for Quadrotor Unmanned Aerial Vehicles(QUAVs)is proposed based on Virtual Tubes(VTs)with flexible boundaries in the presence of un... In this paper,a distributed Event-Triggered(ET)collision avoidance coordinated control for Quadrotor Unmanned Aerial Vehicles(QUAVs)is proposed based on Virtual Tubes(VTs)with flexible boundaries in the presence of unknown external disturbances.Firstly,VTs are constructed for each QUAV,and the QUAV is restricted into the corresponding VT by the artificial potential field,which is distributed around the boundary of the VT.Thus,the collisions between QUAVs are avoided.Besides,the boundaries of the VTs are flexible by the modification signals,which are generated by the self-regulating auxiliary systems,to make the repulsive force smaller and give more buffer space for QUAVs without collision.Then,a novel ET mechanism is designed by introducing the concept of prediction to the traditional fixed threshold ET mechanism.Furthermore,a disturbance observer is proposed to deal with the adverse effects of the unknown external disturbance.On this basis,a distributed ET collision avoidance coordinated controller is proposed.Then,the proposed controller is quantized by the hysteresis uniform quantizer and then sent to the actuator only at the ET instants.The boundedness of the closed-loop signals is verified by the Lyapunov method.Finally,simulation and experimental results are performed to demonstrate the superiority of the proposed control method. 展开更多
关键词 Quadrotor unmanned aerial vehicles Collision avoidance Virtual tubes with flexible boundaries Event-triggered mechanism Hysteresis uniform quantizer Distributed coordinated control
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Fluid-based moderate collision avoidance for UAV formation in 3-D low-altitude environments 认领 引用 被引量：1
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作者 Menghua ZHANG Honglun WANG +5 位作者 Zhiyu LI Yanxiang WANG Xianglun ZHANG Qiang TANG Shichao MA Jianfa WU 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2025年第6期533-551,共19页
Aiming to address the Unmanned Aerial Vehicle(UAV) formation collision avoidance problem in Three-Dimensional(3-D) low-altitude environments where dense various obstacles exist, a fluid-based path planning framework n... Aiming to address the Unmanned Aerial Vehicle(UAV) formation collision avoidance problem in Three-Dimensional(3-D) low-altitude environments where dense various obstacles exist, a fluid-based path planning framework named the Formation Interfered Fluid Dynamical System(FIFDS) with Moderate Evasive Maneuver Strategy(MEMS) is proposed in this study.First, the UAV formation collision avoidance problem including quantifiable performance indexes is formulated. Second, inspired by the phenomenon of fluids continuously flowing while bypassing objects, the FIFDS for multiple UAVs is presented, which contains a Parallel Streamline Tracking(PST) method for formation keeping and the traditional IFDS for collision avoidance. Third, to rationally balance flight safety and collision avoidance cost, MEMS is proposed to generate moderate evasive maneuvers that match up with collision risks. Comprehensively containing the time and distance safety information, the 3-D dynamic collision regions are modeled for collision prediction. Then, the moderate evasive maneuver principle is refined, which provides criterions of the maneuver amplitude and direction. On this basis, an analytical parameter mapping mechanism is designed to online optimize IFDS parameters. Finally, the performance of the proposed method is validated by comparative simulation results and real flight experiments using fixed-wing UAVs. 展开更多
关键词 Unmanned aerial vehicle Formation collision avoidance:3-D low-altitude environments Interfered fluid dynamical system 3-D dynamic collision region
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Hazard-Aware Weighted Advantage Combination for UAV Target Tracking and Obstacle Avoidance 认领 引用
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作者 Lele Xu Jian Liu +2 位作者 Xiaoguang Chang Xuping Liu Changyin Sun 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2025年第6期1260-1271,共12页
In recent years,the rapid evolution of unmanned aerial vehicles(UAVs)has brought about transformative changes across various industries.However,addressing fundamental challenges in UAV technology,particularly target t... In recent years,the rapid evolution of unmanned aerial vehicles(UAVs)has brought about transformative changes across various industries.However,addressing fundamental challenges in UAV technology,particularly target tracking and obstacle avoidance,remains crucial for wildlife protection,military industry security,etc.Many existing methods based on reinforcement learning to solve UAV multi-tasks need to be redesigned and retrained,and cannot be quickly and effectively extended to other scenarios.To this end,we propose a novel solution based on a hazard-aware weighted advantage combination for UAV target tracking and obstacle avoidance.First,we independently trained the UAV target tracking and obstacle avoidance using the dueling double deep Q-network reinforcement learning algorithm.Subsequently,in a multitasking scenario,we introduce the two pre-trained networks.Meanwhile,we design a weight determined by the present risk level encountered by the UAV.This weight is utilized to perform a weighted summation of the advantage values from both networks,eliminating the need for retraining to obtain the final action.We validate our approach through extensive simulation experiments in the robotics simulator known as CoppeliaSim.The results demonstrate that our method outper-forms current state-of-the-art techniques,achieving superior performance in both tracking accuracy and avoidance of collisions. 展开更多
关键词 Multi-task obstacle avoidance reinforcement learning tracking unmanned aerial vehicles(UAV)
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Cooperative RISE learning-based circumnavigation of networked unmanned aerial vehicles with collision avoidance and connectivity preservation 认领 引用
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作者 Jawhar Ghommam Amani Ayeb +1 位作者 Brahim Brahmi Maarouf Saad 《Control Theory and Technology》 EI CSCD 2025年第2期266-293,共28页
In this paper, a bearing-based three-dimensional self-localization and distributed circumnavigation with connectivity preservation and collision avoidance are investigated for a group of quadrotor-type unmanned aerial... In this paper, a bearing-based three-dimensional self-localization and distributed circumnavigation with connectivity preservation and collision avoidance are investigated for a group of quadrotor-type unmanned aerial vehicles (UAVs). A leader–follower structure is adopted, wherein the leader moves with reference dynamics (a target). Different from the existing approaches that necessitate full knowledge of the time-varying reference trajectory, in this paper, it is assumed that only some vehicles (at least one) have access to the bearing relative to the target, and all other vehicles are equipped with sensors capable of measuring the bearings relative to neighboring vehicles. In this paper, a consensus estimator is proposed to estimate the global position for each vehicle using relative bearing measurements and an estimate of neighboring vehicles received from a direct communication network. Then, a continuous robust integral of the sign of the error (RISE) control approach is effectively integrated with the distributed vector field approach to ensure UAV formation orbiting around the moving target while avoiding obstacles and maintaining network links within available communication ranges. In contrast to the classical RISE control rule, a \(anh (\cdot )\) function is used instead of the \(ext {sgn}(\cdot )\) function to further decrease the high-gain feedback and to obtain a smoother control signal. Furthermore, by using the localized radial basis function (RBF) neural networks (NNs) in a cooperative way, deterministic learning theory is employed to accurately identify/learn model uncertainties resulting from the attitude dynamics. The convergence of the entire closed-loop system is illustrated using the Lyapunov theory and is shown to be uniformly ultimately bounded. Finally, numerical simulations show the effectiveness of the proposed approach. 展开更多
关键词 RISE-based backstepping approach Input constraints Auxiliary compensated systems Circumnavigation Distributed localization Collision avoidance Vector-field potential
Computational Design of Interval Type-2 Fuzzy Control for Formation and Containment of Multi-Agent Systems with Collision Avoidance Capability 认领 引用 被引量：1
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作者 Yann-Horng Lin Wen-Jer Chang +2 位作者 Yi-Chen Lee Muhammad Shamrooz Aslam Cheung-Chieh Ku 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第8期2231-2262,共32页
An Interval Type-2(IT-2)fuzzy controller design approach is proposed in this research to simultaneously achievemultiple control objectives inNonlinearMulti-Agent Systems(NMASs),including formation,containment,and coll... An Interval Type-2(IT-2)fuzzy controller design approach is proposed in this research to simultaneously achievemultiple control objectives inNonlinearMulti-Agent Systems(NMASs),including formation,containment,and collision avoidance.However,inherent nonlinearities and uncertainties present in practical control systems contribute to the challenge of achieving precise control performance.Based on the IT-2 Takagi-Sugeno Fuzzy Model(T-SFM),the fuzzy control approach can offer a more effective solution for NMASs facing uncertainties.Unlike existing control methods for NMASs,the Formation and Containment(F-and-C)control problem with collision avoidance capability under uncertainties based on the IT-2 T-SFM is discussed for the first time.Moreover,an IT-2 fuzzy tracking control approach is proposed to solve the formation task for leaders in NMASs without requiring communication.This control scheme makes the design process of the IT-2 fuzzy Formation Controller(FC)more straightforward and effective.According to the communication interaction protocol,the IT-2 Containment Controller(CC)design approach is proposed for followers to ensure convergence into the region defined by the leaders.Leveraging the IT-2 T-SFM representation,the analysis methods developed for linear Multi-Agent Systems(MASs)are successfully extended to perform containment analysis without requiring the additional assumptions imposed in existing research.Notably,the IT-2 fuzzy tracking controller can also be applied in collision avoidance situations to track the desired trajectories calculated by the avoidance algorithm under the Artificial Potential Field(APF).Benefiting from the combination of vortex and source APFs,the leaders can properly adjust the system dynamics to prevent potential collision risk.Integrating the fuzzy theory and APFs avoidance algorithm,an IT-2 fuzzy controller design approach is proposed to achieve the F-and-C purposewhile ensuring collision avoidance capability.Finally,amulti-ship simulation is conducted to validate the feasibility and effectiveness of the designed IT-2 fuzzy controller. 展开更多
关键词 Interval type-2 Takagi-Sugeno fuzzy model multi-agent systems formation and containment control fuzzy collision avoidance artificial potential field
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Understanding Corporate Tax Avoidance:A Review of Internal and External Influencing Factors 认领 引用
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作者 Johan Adhitakarya Yudha +1 位作者 Iskandar Muda Erlina 《Journal of Modern Accounting and Auditing》 2025年第3期209-217,共9页
This study aims to systematically review the various factors influencing corporate tax avoidance.Tax avoidance refers to legal strategies used to minimize tax liabilities and has become a critical issue in accounting ... This study aims to systematically review the various factors influencing corporate tax avoidance.Tax avoidance refers to legal strategies used to minimize tax liabilities and has become a critical issue in accounting and corporate governance.The study examines key determinants of tax avoidance,including firm characteristics(such as size,leverage,and multinational scale),managerial attributes,executive compensation,ownership structure,corporate social responsibility(CSR)performance,as well as the impact of regulations and legal reforms.The review findings highlight that the motivations behind tax avoidance are multifaceted,driven by the interaction of economic incentives,organizational ethics,external pressures,and public policies.Moreover,strict regulatory environments and strong CSR practices can mitigate tax avoidance behaviors,although their effectiveness is often contingent upon a firm’s cultural and political context.This study offers a comprehensive mapping of the current literature and recommends future research that integrates additional variables and broader time spans to enhance the understanding of tax avoidance behavior across different national contexts. 展开更多
关键词 tax avoidance determinant tax avoidance motivation
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Localization and tracking of multiple quadrotors with collision avoidance:Theory and experiment 认领 引用
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作者 Guang Yang Juntong Qi +4 位作者 Mingming Wang Yan Peng Chong Wu Yuan Ping Hailong Huang 《Defence Technology（防务技术）》 SCIE EI CAS CSCD 2025年第8期338-350,共13页
Multiple quadrotors target encirclement is widely used in the intelligent field,as it can effectively monitor and control target behavior.However,it faces the danger of collision,as well as difficulties in localizatio... Multiple quadrotors target encirclement is widely used in the intelligent field,as it can effectively monitor and control target behavior.However,it faces the danger of collision,as well as difficulties in localization and tracking.Therefore,we propose a complete target encirclement method.Firstly,based on Hooke's law,a collision avoidance controller is designed to maintain a safe flying distance among quadrotors.Then,based on the consensus theory,a formation tracking controller is designed to meet the requirements of formation transformation and encirclement tasks,and a stability proof based on Lyapunov was provided.Besides,the target detection is designed based on YOLOv5s,and the target location model is constructed based on the principle of pinhole projection and triangle similarity.Finally,we conducted experiments on the built platform,with 3 reconnaissance quadrotors detecting and localization 3 target vehicles and 7 hunter quadrotors tracking them.The results show that the minimum average error for localization targets with reconnaissance quadrotors can reach 0.1354 m,while the minimum average error for tracking with hunter quadrotors is only 0.2960 m.No quadrotors collision occurred in the whole formation transformation and tracking experiment.In addition,compared with the advanced methods,the proposed method has better performance. 展开更多
关键词 Multiple quadrotors Collision avoidance Target localization Tracking Outdoor experiments
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