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Path planning of USV in confined waters based on improved A * and DWA fusion algorithm

OCEAN ENGINEERING 2025年 322卷

作者： Zhang, Jiadong Ling, Hongjie Tang, Zhihao Song, Wandi Lu, Anqi Jiangsu Univ Sci & Technol Sch Shipbuilding & Ocean Engn Zhenjiang 212003 Peoples R China

In the field of unmanned vessels, path planning in confined and complex environments has become a crucial research focus. Existing methods face issues such as insufficient obstacle avoidance and low planning efficiency. To address these challenges, this paper proposes a hybrid approach combining an improved A* algorithm with an optimized Dynamic Window Approach (DWA). The enhanced A* algorithm adjusts the weight of the heuristic function by introducing a tuning factor (alpha), which directly influences the obstacle density. Additionally, a 5neighborhood search combined with the Floyd algorithm is employed to boost search efficiency and improve path smoothness. The modified DWA algorithm incorporates a path smoothing coefficient and a local target selection strategy, enhancing the safety and stability of local planning. MATLAB simulations demonstrate that the proposed hybrid algorithm generates smooth and safe paths, successfully avoids dynamic obstacles, and shows promising effectiveness and feasibility in unmanned vessel path planning.

关键词： Unmanned surface vehicle Path planning A* algorithm DWA algorithm Dynamic obstacle avoidance fusion algorithm

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IOF-Tracker: A Two-Stage Multiple Targets Tracking Method Using Spatial-Temporal fusion algorithm

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APPLIED SCIENCES-BASEL 2025年第1期15卷 107-107页

作者： Liu, Hongbin Zhao, Yongze Dong, Peng Guo, Xiuyi Wang, Yilin Shandong Jianzhu Univ Sch Informat & Elect Engn Shandong Key Lab Smart Buildings & Energy Efficien Jinan 250101 Peoples R China

Multi-object tracking aims to track multiple objects across consecutive frames in a video, assigning a unique classifier to each object. However, issues such as occlusions, directional changes, or shape alterations can cause appearance variations, leading to detection and matching problems that in turn result in frequent ID switches. To solve these issues, this paper proposes a two-stage multi-object tracking framework based on a spatial and temporal fusion algorithm. First, the video frames are processed by a detector to identify objects and form rectangular detection areas. Meanwhile, an estimator predicts the target rectangular areas in the next frame. Then, we extract the optical flow of the target pixels within the detection and prediction areas, and then a temporal information model is established by calculating the average of the target pixels' optical flow. Afterward, we present a spatial information model using the R-IoU (Reverse of Intersection over Union) between the detection and prediction areas. This spatial and temporal information is combined with weighted matrix fusion, which achieves the feature matching and association task. Finally, we implement a two-stage association multi-object tracking model using the mentioned fusion algorithm. Experiments on the MOTChallenge dataset using the official detector show that our two-stage multi-object tracking method based on the spatial and temporal fusion algorithm is robust in handling occlusions and ID switch issues. As of the submission of this paper, the proposed method has achieved the top ranking in the MOT17 benchmark when evaluated with the official detector.

关键词： multi-object tracking ID switches fusion algorithm spatial and temporal information

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Parametric image design and visualization simulation based on infrared thermal image fusion algorithm

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THERMAL SCIENCE AND ENGINEERING PROGRESS 2025年 60卷

作者： Tang, Guangyi Ma, Xiaozhan Xijing Univ Sch Design & Art Xian 710000 Shaanxi Peoples R China Xian FANYI Univ Sch Art & Design Xian 710000 Shaanxi Peoples R China

Infrared thermal image can provide intuitive information about the surface temperature distribution of objects, but the traditional infrared thermal image processing methods have problems such as low resolution and lack of detailed information, which limits its application in more complex scenes. This paper presents a parametric image design and visualization simulation method based on infrared thermal image fusion algorithm. This paper studies the use of highly sensitive infrared thermal imager to collect thermal image data of target objects under different conditions, and preprocesses the collected infrared thermal images. An algorithm based on multi-scale transformation and image fusion is designed to effectively fuse multiple infrared thermal image data sources, and a parametric design mechanism is introduced to allow users to adjust fusion parameters according to actual application scenarios. In this way, users can customise the generation of thermal images that meet specific needs. Through visual simulation technology, the fusion thermal radiation image is displayed in an intuitive way. In the simulation process, different environmental conditions and object characteristics can be simulated to evaluate the performance and applicability of thermal images in different scenarios. The results show that compared with the traditional method, the thermal radiation image generated by this method has a great improvement in resolution and detail performance. The proposed method not only improves the thermal image quality, but also enhances its applicability and flexibility through parametric design.

关键词： Infrared thermal image fusion algorithm Parameterization Image design Visual simulation

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Dynamic path planning fusion algorithm with improved A* algorithm and dynamic window approach

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INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS 2025年第3期16卷 2057-2071页

作者： Zhang, Jianfeng Guo, Jielong Zhu, Daxin Xie, Yufang Quanzhou Normal Univ Sch Math & Comp Sci Quanzhou 362000 Fujian Peoples R China

In the field of robotics, path planning in complex dynamic environments has become a significant research hotspot. Existing methods often suffer from inadequate dynamic obstacle avoidance capabilities and low exploration efficiency. These issues primarily arise from inconsistencies caused by insufficient utilization of environmental maps in actual path planning. To address these challenges, we propose an improved algorithm that integrates the enhanced A* algorithm with the optimized dynamic window approach (DWA). The enhanced A* algorithm improves the robot's path smoothness and accelerates global exploration efficiency, while the optimized DWA enhances local static and dynamic obstacle avoidance capabilities. We performed simulation experiments using MATLAB and conducted experiments in real dynamic environments simulated with Gazebo. Simulation results indicate that, compared to the traditional A* algorithm, our method optimizes traversed grids by 25% and reduces time by 23% in global planning. In dynamic obstacle avoidance, our approach improves path length by 2.7% and reduces time by 19.2% compared to the traditional DWA, demonstrating significant performance enhancements.

关键词： Robot path planning Complex dynamic environment Improved A* approach Modified dynamic windows method fusion algorithm

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A UAV attitude fusion algorithm based on gradient descent-improved EKF

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EARTH SCIENCE INFORMATICS 2025年第2期18卷 1-13页

作者： Zhao, Guiling Wang, Yuan Liang, Weidong Zhao, Hongxing Liaoning Tech Univ Sch Geomat Fu Xin 123000 Peoples R China

When the UAV is in accelerated motion, the non-gravitational acceleration and body vibration lead to high-frequency errors in the accelerometer acquisition data, which affects the accuracy of the attitude calculation of the UAV. To solve the above problems, a UAV attitude solution fusion algorithm based on gradient descent-improved Extended Kalman Filter (EKF) was designed. Firstly, the gradient descent method is used to solve the sensor data to reduce the error caused by the accelerometer and magnetometer. Secondly, the noise covariance matrix and the non-gravity acceleration function are established to improve the shortcomings of the traditional noise matrix that cannot suppress the interference of non-gravity acceleration. Finally, the gradient descent solution value is used as the measured value of the improved EKF to improve the accuracy and filtering effect of the measured value and realize the attitude update. The experimental results show that the maximum error of the UAV roll angle is 0.017 degrees in the static experiment. Compared with the complementary filtering and EKF algorithm, the error is reduced by 82.65% and 57.50%. In the dynamic experiment, compared with the complementary filtering algorithm, the fusion algorithm error is reduced by at least 72.75% in pitch angle;the roll angle reduced by at least 54.84%;the yaw angle reduced by at least 59.09%. Compared with the EKF algorithm, the fusion algorithm error is reduced by at least 65.33% in pitch angle;the roll angle reduced by at least 27.97%;the yaw angle reduced by at least 40.00%. The UAV attitude fusion algorithm based on gradient descent-improved EKF can effectively suppress the influencing factors such as non-gravitational acceleration interference and high-frequency vibration of the airframe, and improve the attitude-solving accuracy of the UAV.

关键词： UAV Gradient descent Improved EKF fusion algorithm Attitude solution

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fusion algorithm Based on Improved A^(*)and DWA for USV Path Planning

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哈尔滨工程大学学报(英文版) 2025年第1期24卷 224-237页

作者： Changyi Li Lei Yao Chao Mi Container Supply Chain Technology Engineering Research Center Ministry of EducationShanghai Maritime UniversityShanghai 201306China Shanghai SMUVision Smart Technology Ltd Shanghai 201306China

The traditional A^(*)algorithm exhibits a low efficiency in the path planning of unmanned surface vehicles(USVs).In addition,the path planned presents numerous redundant inflection waypoints,and the security is low,which is not conducive to the control of USV and also affects navigation *** this paper,these problems were addressed through the following ***,the path search angle and security were comprehensively considered,and a security expansion strategy of nodes based on the 5×5 neighborhood was *** A^(*)algorithm search neighborhood was expanded from 3×3 to 5×5,and safe nodes were screened out for extension via the node security expansion *** algorithm can also optimize path search angles while improving path ***,the distance from the current node to the target node was introduced into the heuristic *** efficiency of the A^(*)algorithm was improved,and the path was smoothed using the Floyd *** the dynamic adjustment of the weight to improve the efficiency of DWA,the distance from the USV to the target point was introduced into the evaluation function of the dynamic-window approach(DWA)***,combined with the local target point selection strategy,the optimized DWA algorithm was performed for local path *** experimental results show the smooth and safe path planned by the fusion algorithm,which can successfully avoid dynamic obstacles and is effective and feasible in path planning for USVs.

关键词： Improved A^(*)algorithm Optimized DWA algorithm Unmanned surface vehicles Path planning fusion algorithm

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Application of LSTM-DT fusion algorithm in Predicting Ocean Temperature and Salinity Fields 24

Application of LSTM-DT Fusion Algorithm in Predicting Ocean ...

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Proceedings of the 2024 3rd International Symposium on Computing and Artificial Intelligence

作者： Zhanfeng Yuan Hong Zhao Ocean University of China Qingdao Shandong China

ISBN: (纸本)9798400710674

With the swift progress in ocean monitoring technology, the ease of observing sea surface information contrasts with the paucity of subsurface data, which constrains the profound exploration of ocean dynamics and impedes the comprehensive use of oceanic information. To address this issue, this paper introduces a new method that combines satellite remote sensing, reanalysis, and actual measurement data to facilitate the three-dimensional reconstruction of ocean subsurface hydrological profiles. The study utilized 36 independent variables such as sea surface temperature, sea surface salinity, and evaporation to conduct predictive analysis of the temperature and salinity fields beneath the surface of certain areas of the northwest Pacific Ocean. A prediction using the LSTM (Long Short-Term Memory) model for temperature and salinity was proposed. Given that the model's performance is sensitive to hyperparameters, it was enhanced with the Crested Porcupine Optimizer to improve the forecasting of temperature and salinity, significantly reducing the RMSE (Root-Mean-Square Errors) . Following this, an innovative method, the LDFA (LSTM-DT fusion algorithm) model was introduced, which, compared to the LSTM and DT (Decision Tree) algorithms, markedly increased prediction accuracy, bringing the mean RMSE for predicted temperature and salinity down to 1.193 and 0.123, respectively.

关键词： fusion algorithm

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fusion algorithm for Accurate Delineation of QRS Complex in ECG Signal

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2019年第4期38卷 1811-1832页

作者： Sabherwal, Pooja Agrawal, Monika Singh, Latika NorthCap Univ Gurgaon India IIT Delhi CARE Delhi India

In this paper, a novel algorithm for the accurate localization of QRS complex with low average time error is proposed. The idea is thought that the various features of ECG signal like P, Q, R, S and T peaks can be independently detected from raw ECG recording and fused together to obtain a better estimate of QRS position. To explore, in this paper, an algorithm is suggested to first estimate R peak and S peak from raw ECG signal and then fused together to detect and localize QRS complex. The algorithm is validated on all the signals of MIT-BIH arrhythmia database, QT database and noise stress database taken from ***. The algorithm performs reasonably well even for the signals highly corrupted with noise, and these noises are generated by adding the power line interference, electrode motion artifact, baseline wandering interference and muscle artifact to all the signals of MIT-BIH arrhythmia database and QT database. The algorithm performance is confirmed not only with a very high sensitivity and positive predictivity, but also with a very low average time error of 0.63ms against the 3.03ms the best results reported so far for the signals of MIT-BIH arrhythmia database and 0.85ms against the 3.6ms the best results reported in the literature for the signals of QT database.

关键词： QRS complex localization ECG signal Wavelet transform S peak fusion algorithm

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A Docking Mechanism Based on a Stewart Platform and Its Tracking Control Based on Information fusion algorithm

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SENSORS 2022年第3期22卷 770-770页

作者： Zhan, Gan Niu, Shaohua Zhang, Wencai Zhou, Xiaoyan Pang, Jinhui Li, Yingchao Zhan, Jigang Beijing Inst Technol Sch Mechatron Engn Beijing 100081 Peoples R China Beijing Jiaotong Univ Sch Elect Engn Beijing 100044 Peoples R China Beijing Inst Technol Sch Comp Sci & Technol Beijing 100081 Peoples R China Beijing Zhongxin Hengyuan Technol Co Ltd Beijing 100081 Peoples R China

Aiming at the problem of unmanned reconfiguration and docking of ground vehicles under complex working conditions, we designed a piece of docking equipment composed of an active mechanism based on a six-degree-of-freedom platform and a locking mechanism with multi-sensors. Through the proposed control method based on laser and image sensor information fusion calculation, the six-dimensional posture information of the mechanism during the docking process is captured in real time so as to achieve high-precision docking. Finally, the effectiveness of the method and the feasibility of the 6-DOF platform are verified by the established model. The results show that the mechanism can meet the requirements of smooth docking of ground unmanned vehicles.

关键词： docking mechanism Stewart platform visual control fusion algorithm

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Pore Structure Identification Method for Pervious Concrete Based on Improved UNet and fusion algorithm

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KSCE JOURNAL OF CIVIL ENGINEERING 2023年第11期27卷 4834-4848页

作者： Yu, Fan Li, Kailang Zhang, Hua Zhang, Rui Gao, Zhang Huang, Yubin Three Gorges Univ Key Lab Geol Hazards Three Gorges Reservoir Area Minist Educ Yichang 443002 Peoples R China China Three Gorges Univ Coll Civil Engn & Architecture Yichang 443002 Peoples R China China Three Gorges Univ Coll Comp & Informat Technol Yichang 443002 Peoples R China Chongqing Univ Sch Civil Engn Chongqing 400045 Peoples R China

This paper aims to establish an automatic and accurate pore identification method for pervious concrete. The residual module and mixed loss functions were introduced to the original UNet network to obtain the improved UNet. CT scanning was conducted on the six groups of pervious concrete samples with different aggregate sizes to obtain the initial dataset. The initial dataset was marked and enhanced, and then the pore recognition model was trained. The influence of image brightness and contrast on pore identification was analyzed. The fusion algorithm was used to improve the robustness of the model. The results show that during model training, R-UNet began to converge 20 epochs earlier than UNet and the loss value was smaller. Moreover, the maximum increase of mIoU and mDice was 10.3% and 11.7% respectively, and the maximum decrease of mHD was 14.1%. The fusion algorithm could improve the segmentation accuracy of pores in brightness anomaly images. Compared with threshold segmentation method, the method proposed in this paper could improve the accuracy of pore edge segmentation and the "fine pores" identification, and reduced the pore identification defects. The value of mHD was decreased by 48.7%-72.4%, and the efficiency of pore identification was greatly improved.

关键词： Pervious concrete Pore identification Deep learning UNet fusion algorithm

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