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3rd International Conference on Creative Communication and Innovative Technology, ICCIT 2024

作者： Felix Yodianto, Wilsen Warnars, Harco Leslie Hendric Spits Warnars, Leonel Leslie Heny Spits Ramadhan, Arief Siswanto, Teddy Bina Nusantara University Department of Computer Science Jakarta11480 Indonesia Bina Nusantara University Department of Architecture Jakarta11480 Indonesia Telkom University School of Computing Bandung40257 Indonesia Systems Trisakti University Department of Information Jakarta11440 Indonesia

ISBN: (纸本)9798350367492

The rapid development of smart cities requires the integration of advanced technologies to maintain efficiency in urban areas. One critical aspect is the implementation of effective route-finding methods to ensure smooth traffic flow and enhance the quality of life for residents. This paper explores the application of the A-star (A*) Search algorithm within the context of Indonesia's planned new capital in Kalimantan. The study employs the a-star algorithm, incorporating various heuristic distance measures such as Euclidean, Manhattan, and Chebyshev distances. The methodology involves creating graphs and trees from input data to optimize route planning for both public and private vehicles. The study aims to design a flexible and efficient routing system that can accommodate the diverse driving styles and conditions specific to Indonesia, particularly for the proposed new capital city, which aims to be a hub of smart city innovations. The findings reveal that the algorithm's flexibility allows it to adapt effectively to real-time traffic data and various environmental conditions. In conclusion, integrating the a-star algorithm into intelligent city infrastructure presents a promising solution for managing traffic and transportation in Indonesia's new capital. By leveraging IoT and real-time data, the algorithm can enhance the efficiency and safety of urban mobility, contributing to the overall success of innovative city initiatives in Indonesia. This study's novelty lies in its adaptation of the a-star algorithm to Indonesia's unique cultural and environmental conditions, providing a customized solution for the country's new capital city. © 2024 IEEE.

关键词： a-star algorithm Routing Searching

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Dynamic Obstacle Avoidance and Path Planning for Mobile Robots Integrating Improved Rapidly-Exploring Random Tree-star and Improved Dynamic Window Approach Dynamic Obstacle Avoidance and Path Planning

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2025年第3期16卷 803-812页

作者： Wei, Xianyong Si, Hongying Shangqiu Polytech Shangqiu 476000 Peoples R China Shangqiu Normal Univ Sch Math & Stat Shangqiu 476000 Peoples R China

With the application and popularization of artificial intelligence and intelligent robots in daily life, the autonomous navigation and flexible operation capabilities of mobile robots have become particularly critical. Mobile robots perform well in regular environments, but face problems such as low accuracy in dynamic obstacle avoidance and weak adaptability to complex terrains. This study proposes to enhance the adaptability of the Rapidly-exploring Random Tree star algorithm and integrate it with the a-star algorithm, the Dynamic Window Approach, and visual sensor to construct an obstacle avoidance model. The objective is to enable the improved model to recognize various terrain features and enhance the accuracy of the path planning algorithm. The proposed model performed well in obstacle avoidance, with a success rate of 95.78% after ten training epochs and no more than four collisions within 4 minutes. In the experiment, as the obstacle increased every minute, the response speed of the proposed model remained below 25 seconds. The above results indicate that the quality of the planned path is higher than that of the other three models. The path optimization improvement combined with the A* algorithm is effective and has high real-time and accuracy, which can make mobile robots widely used in industries such as services, navigation, and logistics.

关键词： Rapidly-exploring random tree-star dynamic window approach a-star algorithm dynamic obstacle avoidance path planning mobile robot

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Optimal Design of Water Transmission Pipelines Using a Metaheuristic algorithm and Geoprocessing Techniques

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WATER RESOURCES MANAGEMENT 2025年 1-16页

作者： Duarte, Armando Dias Cirilo, Jose Almir Vasconcelos, Rochele Sheila Tahimi, Abdeladhim Sarmento, Francisco Jacome Bezerra, Saulo de Tarso Marques Univ Fed Oeste Bahia Dept Prod Engn Luiz Eduardo Magalhaes BA Brazil Univ Fed Pernambuco Dept Technol Ave Marielle FrancoS-NBairro Nova Caruaru BR-55014593 Caruaru PE Brazil Univ Estadual Santa Cruz Dept Agr Sci & Environm Ilheus BA Brazil Univ Fed Alagoas Dept Math Maceio AL Brazil Univ Fed Paraiba Dept Civil & Environm Engn Joao Pessoa PB Brazil

Traditionally, the various components of water supply systems have been designed using trial-and-error techniques guided by designers' experience. While these conventional methods can be effective in certain cases, they often lead to suboptimal solutions. Advances in computational modeling have enabled the development of more accurate and cost-effective solutions by integrating geospatial data, hydraulic constraints, and economic factors into the decision-making process. This study proposes a metaheuristic technique for optimizing pipeline routes, enhancing the traditional a-star algorithm. The developed method, named Modified A-star for Pipeline Routing (MAPR), operates within a specific search space, considering key variables that influence the determination of the optimal route. MAPR minimizes total costs associated with construction and energy consumption by incorporating a multiplier coefficient that adjusts the relative importance of different trajectories. This adjustment accelerates convergence to the water delivery point while accounting for cost variations. Simulation results demonstrate MAPR's effectiveness in generating cost-efficient layouts across different terrains and pipeline configurations. Notably, the best simulation results were achieved when the Destiny Way coefficient, which balances the importance of displacement toward the destination against the costs, was set to 1.0. At this value, an equilibrium is achieved, ensuring that no cost component is disproportionately prioritized. MAPR proves to be a valuable tool for the automatic determination of optimal pipeline routes, reducing subjectivity in design while minimizing both implementation and operational costs. These characteristics make it a promising approach for the design of real-world water supply systems.

关键词： Water supply Optimal pipelines routes a-star algorithm Optimization

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A Path Planning algorithm Based on A Heuristic Method

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JOURNAL OF INTERNET TECHNOLOGY 2025年第2期26卷 183-198页

作者： Yan, Xiao-Zhen Zhou, Xin-Yue Ding, Ruo-Chen Luo, Qing-Hua Ju, Chun-Yu Harbin Inst Technol WeiHai Sch Informat Sci & Engn Weihai Peoples R China Shandong Inst Shipbldg Technol Jinan Peoples R China

The path planning algorithm plays a pivotal role in the field of intelligent robotics. However, in certain scenarios, the a-star algorithm exhibits drawbacks such as excessive redundant nodes and prolonged path lengths. Consequently, this paper introduces a path planning algorithm employing a heuristic approach, which will be briefly elucidated in the subsequent sections. If the straight-line path from the starting point to the destination is unobstructed, iterative calculations for path planning are unnecessary. Should the straight-line path intersect obstacles, the proposed heuristic algorithm is employed for local path planning to circumvent obstacles, and the obtained path is subsequently integrated with the overall trajectory. In the same context, we compare this algorithm with other path planning algorithms, revealing that the enhanced algorithm presented in this paper achieves a reduction in path length this study.

关键词： a-star algorithm Path planning algorithm Adaptive obstacle size Heuristic method

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A Dynamic Fusion Pathfinding algorithm Using Delaunay Triangulation and Improved A-star for Mobile Robots

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IEEE ACCESS 2021年 9卷 20602-20621页

作者： Liu, Zhihai Liu, Hanbin Lu, Zhenguo Zeng, Qingliang Shandong Univ Sci & Technol Coll Transportat Qingdao 266590 Peoples R China Shandong Univ Sci & Technol Coll Mech & Elect Engn Qingdao 266590 Peoples R China Shandong Normal Univ Coll Informat Sci & Engn Jinan 250358 Peoples R China

Although many studies exist on mobile robot path planning, the disadvantages of complex algorithms and many path nodes in logistics warehouses and manufacturing workshops are obvious, mainly due to the inconsistency of map environment construction and pathfinding strategies. In this study, to improve the efficiency of mobile robot path planning, the Delaunay triangulation algorithm was used to process complex obstacles and generate Voronoi points as pathfinding priority nodes. The concept of the grid was used to extract obstacle edges to provide obstacle avoidance strategies for robot pathfinding. Subsequently, the search for priority and regular path nodes used the improved A-star (A*) algorithm. The dynamic fusion pathfinding algorithm (DFPA), based on Delaunay triangulation and improved A*, was designed, which realizes the path planning of mobile robots. MATLAB 2016a was used as the simulation software, to firstly verify the correctness of the DFPA, and then to compare the algorithm with other methods. The results show that under the experimental environment with the same start point, goal point, and number of obstacles, the map construction method and pathfinding strategy proposed in this paper reduce the planned path length of the mobile robot, the number of path nodes, and the cost of overall turn consumption, and increase the success rate of obtaining a path. The new dynamic map construction method and pathfinding strategy have important reference significance for processing chaotic maps, promoting intelligent navigation, and site selection planning.

关键词： Heuristic algorithms Path planning Mobile robots Collision avoidance Genetic algorithms Planning Classification algorithms Delaunay triangulation a-star algorithm mobile robot map modeling path planning

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Path Planning Based on A-star and Dynamic Window Approach algorithm for Wild Environment

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Journal of Shanghai Jiaotong university(Science) 2024年第4期29卷 725-736页

作者： DONG Dejin DONG Shiyin ZHANG Lulu CAI Yunze Department of Automation Shanghai Jiao Tong UniversityShanghai200240China Key Laboratory of System Control and Information Processing Ministry of EducationShanghai200240China Shanghai Electro-Mechanical Engineering Institute Shanghai201109China

The path planning problem of complex wild environment with multiple elements still poses *** paper designs an algorithm that integrates global and local planning to apply to the wild environmental path *** modeling process of wild environment map is *** optimization strategies are designed to improve the A-star in overcoming the problems of touching the edge of obstacles,redundant nodes and twisting paths.A new weighted cost function is designed to achieve different planning ***,the improved dynamic window approach(DWA)is designed to avoid local optimality and improve time efficiency compared to traditional *** the necessary path re-planning of wild environment,the improved A-star is integrated with the improved DWA to solve re-planning problem of unknown and moving obstacles in wild environment with multiple *** improved fusion algorithm effectively solves problems and consumes less time,and the simulation results verify the effectiveness of improved algorithms above.

关键词： path planning path re-planning wild environment a-star algorithm dynamic window approach

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An Improved Reconfiguration algorithm for VLSI Arrays with A-star 16th

An Improved Reconfiguration Algorithm for VLSI Arrays with A...

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16th International Conference on Computational Science and Its Applications (ICCSA)

作者： Qian, Junyan Zhou, Zhide Zhao, Lingzhong Gu, Tianlong Guilin Univ Elect Technol Guangxi Key Lab Trusted Software Guilin 541004 Peoples R China

ISBN: (纸本)9783319421087

This paper describes a novel technique to speed up the reconfiguration for the VLSI arrays. We propose an efficient algorithm based on a-star algorithm for accelerating reconfiguration of the power efficient VLSI processor subarrays to meet the real-time constraints and lower power consumption of the embedded systems. The proposed algorithm treats the problem of constructing a local optimal logical column that has the minimum number of long interconnects as a shortest path problem. Then the local optimal column can be constructed by utilizing a-star algorithm with appropriate heuristic strategy. The proposed algorithm greatly reduces the number of visits to the fault-free PEs for constructing a local optimal logical column and effectively decreases the reconfiguration running time. Experimental results show that the computation time can be improved by more than 38.64% for a 128 x 128 host array with fault density of 20 %, without loss of harvest.

关键词： Reconfiguration VLSI array Shortest path a-star algorithm

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ASA-routing: A-star Adaptive Routing algorithm for Network-on-Chips 18th

ASA-routing: A-Star Adaptive Routing Algorithm for Network-o...

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18th International Conference on algorithms and Architectures for Parallel Processing (ICA3PP)

作者： Cai, Yuan Ji, Xiang Tsinghua Univ Sch Software Beijing 100084 Peoples R China

ISBN: (纸本)9783030050542;9783030050535

Network congestion is not an uncommon occurrence even when a routing algorithm is well-designed, especially under the condition of a high injection rate. Moreover, it strongly affects the network's overall performance as a result of increased packet latency. However, the majority of existing congestion avoidance methods either utilize local information or are incredibly complicated. The a-star algorithm is characterized as a heuristic algorithm typically used for the purpose of obtaining an optimal path. In this paper, we propose a novel route selection strategy for network-on-chips is proposed. This strategy is based on the a-star algorithm called ASA-routing. This selection method can be coupled with any deadlock-free adaptive routing algorithm. The ASA-routing utilizes routing table information in order to select as non-congested as possible of output channels for forwarding packets. The congestion information should be dynamically updated according to previously routed packets' transmission latency. Based on experimental results for different traffic patterns and network loads, the manner in which our method can be applied to the repetitive turn model routing and the odd-even turn routing is outlined, improving both the average latency and the throughput.

关键词： Network-on-chip Adaptive routing a-star algorithm Congestion Selection function

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Path Planning for Mobile Robots With an A-star and Artificial Potential Field Fusion algorithm

Path Planning for Mobile Robots With an A-star and Artificia...

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2024 IEEE International Conference on Unmanned Systems, ICUS 2024

作者： Liu, Yanqing Xing, Hongjun Chen, Jinbao Xu, Yuzhe Xie, Yuyan Wang, Chen National Key Laboratory of Aerospace Mechanism Nanjing University of Aeronautics and Astronautics Nanjing China Key Laboratory of Exploration Mechanism of the Deep Space Planet Surface Ministry of Industry and Information Technology Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (纸本)9798350384185

With the rapid advancement of artificial intelligence, path planning has emerged as a crucial technology in the deployment of mobile robots. In order to optimize the path of a mobile robot, aiming at the problem that the traditional A* algorithm has many turns in path planning and the artificial potential field method is easy to fall into the local optimum, this paper proposes a fusion algorithm combining the A* algorithm and the artificial potential field method. The algorithm aims to avoid static obstacles on the ground such as desks and tables, and reach the target mission point safely and efficiently. A* algorithm is used to generate the optimal safe path from the starting point to the end point in the raster map. According to the optimal path generated by A* algorithm, a global path segmentation method is designed, and local path planning based on the artificial potential field method is carried out. Compared with the conventional A* algorithm, the proposed fusion algorithm generates a shorter motion path with fewer turning times, and the artificial potential field algorithm is added for local obstacle avoidance, which greatly improves the safety of the wheeled mobile robot's movement. Finally, simulations have been conducted to prove the effectiveness of the proposed method. © 2024 IEEE.

关键词： a-star algorithm Artificial potential field method Fusion algorithm Path planning

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Research on Path and Sequence Planning for Multi-Cabin Onboard Transportation of Large Cruise Ships

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APPLIED SCIENCES-BASEL 2025年第8期15卷 4406-4406页

作者： Ju, Liyang Wu, Xiaoyuan Zhao, Yixi Liu, Jianfeng Liu, Kun Shanghai Jiao Tong Univ Sch Mech Engn Shanghai 201109 Peoples R China Shanghai Waigaoqiao Shipbldg Co Ltd Shanghai 200137 Peoples R China Jiangsu Univ Sci & Technol Sch Naval Architecture & Ocean Engn Zhenjiang 212100 Peoples R China

The utilization of PMCUs (Prefabricated Modular Cabin Units) is a key strategy for enhancing the efficiency and reducing the costs of large cruise ship construction. Effective transportation planning for multiple PMCU cabins, including the paths and sequence, is vital to ensure smooth and timely installation. However, traditional a-star algorithms for path planning face limitations when it comes to accounting for boundary obstacles, and existing routine sequence planning methods can hardly tackle multi-cabin coupled blocking effects. To address these challenges, an enhanced a-star algorithm is introduced and designed to handle both grid-based and boundary obstacles in the path planning process for cabin transportation onboard. Additionally, a novel reverse planning strategy is further proposed that addresses the coupling effects arising from inter-cabin mutual blocking by determining the optimal collision-free installation sequence. Integrated with the enhanced a-star algorithm, this reverse planning strategy effectively eliminates interference between cabin transportation sequences and transportation paths, significantly improving operational efficiency. A comparative analysis across various scenarios further substantiates the practicality and effectiveness of the proposed method, highlighting its potential for real-world application in large-scale cruise ship construction.

关键词： cabin transportation path planning sequence planning a-star algorithm

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