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Keywords = hierarchical pathfinding

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24 pages, 5536 KB  
Article
Research on Subsea Cluster Layout Optimization Method Considering Three-Dimensional Terrain Constraints
by Weizheng An, Wenze Liu, Xiaohui Song, Yingying Wang, Qiang Ma, Yangqing Lin and Yiyang Xue
J. Mar. Sci. Eng. 2025, 13(12), 2385; https://doi.org/10.3390/jmse13122385 - 16 Dec 2025
Viewed by 271
Abstract
Seabed topography is a key factor affecting the layout of underwater production systems. Developing a more scientific, intelligent, and integrated layout optimization method is the key to optimizing the layout of underwater production systems. To address the challenge of acquiring a more scientific, [...] Read more.
Seabed topography is a key factor affecting the layout of underwater production systems. Developing a more scientific, intelligent, and integrated layout optimization method is the key to optimizing the layout of underwater production systems. To address the challenge of acquiring a more scientific, intelligent, and integrated optimization method, this paper proposes a multi-level integrated optimization model that incorporates three-dimensional seabed topography, obstacle areas, target locations, pipeline paths, and manifold connection relationships, with the primary objective of minimizing total investment cost. A hybrid algorithm combining H-MOPSO (Hierarchical Multi-Objective Particle Swarm Optimization) with K-means-ILP clustering, dynamic programming, and TEWA* pathfinding is raised to collaboratively solve for the global optimal layout, achieving a coupled “target grouping-manifold connection-path optimization” design. Based on the actual oilfield seabed topography and target data, this paper carries out case analysis and algorithm comparison experiments. The results show that the optimization method in this paper can significantly improve the layout economy and cost accuracy under the premise of meeting the engineering constraints. Among them, the PLEM parallel connection method reduces the pipeline laying cost by 25.72% and the overall layout investment cost by 5.39% compared with the traditional manifold series scheme. Full article
(This article belongs to the Section Geological Oceanography)
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30 pages, 470 KB  
Article
Clustered Reverse Resumable A* Algorithm for Warehouse Robot Pathfinding
by Gábor Csányi and László Z. Varga
Machines 2025, 13(12), 1127; https://doi.org/10.3390/machines13121127 - 8 Dec 2025
Viewed by 438
Abstract
Robots are widely used to carry goods in automated warehouses. Planning collision-free paths for multiple robots which are continuously given new goals is called Lifelong Multi-Agent Pathfinding. In a lifelong environment, conflicts may emerge among the robots, and continuous replanning is needed. We [...] Read more.
Robots are widely used to carry goods in automated warehouses. Planning collision-free paths for multiple robots which are continuously given new goals is called Lifelong Multi-Agent Pathfinding. In a lifelong environment, conflicts may emerge among the robots, and continuous replanning is needed. We propose, develop, implement, and evaluate the novel approach called the Clustered Reverse Resumable A* (CRRA*) algorithm to enhance the continuous computation of the shortest path from the changing position of a robot to its goal. The Priority Inheritance with Backtracking (PIBT) algorithm is the currently known most efficient algorithm to handle the pathfinding of thousands of robots in a warehouse. The PIBT algorithm requires that in each step each robot evaluates the distances from its surrounding positions to its goal; therefore, we integrate the CRRA* algorithm with the PIBT algorithm to evaluate CRRA*. The evaluation results show that the CRRA* leads to a significant reduction in computation time, especially in larger warehouses where the obstacles form well-separated spaces. At the same time, the degradation in solution quality is minimal. The CRRA* algorithm is more efficient in larger warehouses than the plain Reverse Resumable A* (RRA*) algorithm. The faster computation of slightly suboptimal paths can be useful in many practical applications, especially in situations where real-time planning is more important than finding the optimal paths. CRRA* can also be used as a heuristic in any multi-agent pathfinding solution to obtain a faster, nearly accurate heuristic. Full article
(This article belongs to the Special Issue Autonomous Navigation of Mobile Robots and UAVs, 2nd Edition)
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19 pages, 614 KB  
Article
Empirical Analysis of Hierarchical Pathfinding in Lifelong Multi-Agent Pathfinding with Turns
by László Z. Varga
Systems 2025, 13(5), 331; https://doi.org/10.3390/systems13050331 - 1 May 2025
Cited by 1 | Viewed by 2609
Abstract
Lifelong multi-agent pathfinding has two interrelated aspects: one is to find conflict-free paths for the agents, and the other is to resolve the conflicts among the agents in the best possible way. We focus on the first aspect by investigating three hierarchical pathfinding [...] Read more.
Lifelong multi-agent pathfinding has two interrelated aspects: one is to find conflict-free paths for the agents, and the other is to resolve the conflicts among the agents in the best possible way. We focus on the first aspect by investigating three hierarchical pathfinding approaches, while we apply the same conflict resolution method. We formally present the three pathfinding options: map reduction using fixed waypoints, map reduction using dynamic waypoints, and the classic grid region-based approach. We point out the problem of emerging conflicts in lifelong multi-agent pathfinding with turns. We describe how we evaluate the proposed solutions to example scenarios from the League of Robot Runners competition, and we formulate the goals of the empirical analysis. Based on the experimental results, we point out the need to find the sweet spot between response time and throughput. Full article
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14 pages, 3677 KB  
Article
A Pathfinding Algorithm for Large-Scale Complex Terrain Environments in the Field
by Luchao Kui and Xianwen Yu
ISPRS Int. J. Geo-Inf. 2024, 13(7), 251; https://doi.org/10.3390/ijgi13070251 - 12 Jul 2024
Cited by 3 | Viewed by 3737
Abstract
Pathfinding for autonomous vehicles in large-scale complex terrain environments is difficult when aiming to balance efficiency and quality. To solve the problem, this paper proposes Hierarchical Path-Finding A* based on Multi-Scale Rectangle, called RHA*, which achieves efficient pathfinding and high path quality for [...] Read more.
Pathfinding for autonomous vehicles in large-scale complex terrain environments is difficult when aiming to balance efficiency and quality. To solve the problem, this paper proposes Hierarchical Path-Finding A* based on Multi-Scale Rectangle, called RHA*, which achieves efficient pathfinding and high path quality for large-scale unequal-weighted maps. Firstly, the original map grid cells were aggregated into fixed-size clusters. Then, an abstract map was constructed by aggregating equal-weighted clusters into rectangular regions of different sizes and calculating the nodes and edges of the regions in advance. Finally, real-time pathfinding was performed based on the abstract map. The experiment showed that the computation time of real-time pathfinding was reduced by 96.64% compared to A* and 20.38% compared to HPA*. The total cost of the generated path deviated no more than 0.05% compared to A*. The deviation value is reduced by 99.2% compared to HPA*. The generated path can be used for autonomous vehicle traveling in off-road environments. Full article
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25 pages, 18313 KB  
Article
Geostatistical and Remote Sensing Studies to Identify High Metallogenic Potential Regions in the Kivi Area of Iran
by Adel Shirazy, Mansour Ziaii, Ardeshir Hezarkhani and Timofey Timkin
Minerals 2020, 10(10), 869; https://doi.org/10.3390/min10100869 - 30 Sep 2020
Cited by 17 | Viewed by 20712
Abstract
The Kivi area in the East Azerbaijan Province of Iran is one of the country’s highest-potential regions for metal element exploration. The primary goal herein was to process the data obtained from geochemical, geostatistical, and remote sensing tools (in the form of stream [...] Read more.
The Kivi area in the East Azerbaijan Province of Iran is one of the country’s highest-potential regions for metal element exploration. The primary goal herein was to process the data obtained from geochemical, geostatistical, and remote sensing tools (in the form of stream sediment samples and satellite images) to identify metallic mineralization anomalies in the region. After correcting the raw stream sediment geochemical data, single-variable statistical processing was performed, and Ti and Zn were identified as the elements with the highest degree of contrast. The relationship among these elements was further investigated using correlation and hierarchical clustering analyses. Principal component analysis was then applied to determine the principal components related to these elements, which were subsequently plotted on a regional geological map. Elements related to Ti and Zn were identified using threshold limits of anomalous samples determined via linear discriminant analysis. Lithological units and alteration patterns were detected through remote sensing investigations on Landsat-8 images. Stream sediment geochemical and remote sensing survey results identified anomalous areas of Ti and Zn in the eastern part of the study region. Our results indicate that Ti and Zn are good pathfinder elements for further exploratory investigation in this area. Full article
(This article belongs to the Section Mineral Deposits)
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20 pages, 1967 KB  
Article
Hierarchical Behavior Model for Multi-Agent System with Evasion Capabilities and Dynamic Memory
by Aydin Cetin and Erhan Bulbul
ISPRS Int. J. Geo-Inf. 2020, 9(4), 279; https://doi.org/10.3390/ijgi9040279 - 23 Apr 2020
Cited by 2 | Viewed by 3485
Abstract
The behavior of an agent may be simple or complex depending on its role. Behavioral simulation using agents can have multiple approaches that have different advantages and disadvantages. By combining different behaviors in a hierarchical model, situational inefficiencies can be compensated. This paper [...] Read more.
The behavior of an agent may be simple or complex depending on its role. Behavioral simulation using agents can have multiple approaches that have different advantages and disadvantages. By combining different behaviors in a hierarchical model, situational inefficiencies can be compensated. This paper proposes a behavioral hierarchy model that combines different mechanisms in behavior plans. The study simulates the social behavior in an office environment during an emergency using collision avoidance, negotiation, conflict solution, and path-planning mechanisms in the same multi-agent model to find their effects and the efficiency of the combinational setups. Independent agents were designed to have memory expansion, pathfinding, and searching capabilities, and the ability to exchange information among themselves and perform evasive actions to find a way out of congestion and conflict. The designed model allows us to modify the behavioral hierarchy and action order of agents during evacuation scenarios. Moreover, each agent behavior can be enabled or disabled separately. The effects of these capabilities on escape performance were measured in terms of time required for evacuation and evacuation ratio. Test results prove that all mechanisms in the proposed model have characteristics that fit each other well in situations where different hierarchies are needed. Dynamic memory management (DMM), together with a hierarchical behavior plan, achieved a performance improvement of 23.14% in escape time without providing agents with any initial environmental information. Full article
(This article belongs to the Special Issue Geospatial Methods in Social and Behavioral Sciences)
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19 pages, 579 KB  
Article
Using the Hierarchical Pathfinding A* Algorithm in GIS to Find Paths through Rasters with Nonuniform Traversal Cost
by Harri Antikainen
ISPRS Int. J. Geo-Inf. 2013, 2(4), 996-1014; https://doi.org/10.3390/ijgi2040996 - 17 Oct 2013
Cited by 17 | Viewed by 12861
Abstract
A fair amount of research has been carried out on pathfinding problems in the context of transportation networks, whereas pathfinding in off-network space has received far less interest. In geographic information systems (GIS), the latter is usually associated with the cost surface method, [...] Read more.
A fair amount of research has been carried out on pathfinding problems in the context of transportation networks, whereas pathfinding in off-network space has received far less interest. In geographic information systems (GIS), the latter is usually associated with the cost surface method, which allows optimum paths to be calculated through rasters in which the value of each cell depicts the cost of traversal through that cell. One of the problems with this method is computational expense, which may be very high with large rasters. In this study, a pathfinding method called Hierarchical Pathfinding A* (HPA*), based on an abstraction strategy, is investigated as an alternative to the traditional approach. The aim of this study is to enhance the method to make it more suitable for calculating paths over cost rasters with nonuniform traversal cost. The method is implemented in GIS and tested with actual data. The results indicate that by taking into account the information embedded in the cost raster, paths of relatively good quality can be calculated while effecting significant savings in computational effort compared to the traditional, nonhierarchical approach. Full article
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