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Generating A-star algorithm Admissible Heuristics Using a Dynamic Dataloader on Neural Networks, Enhanced With Genetic algorithms, on a Distributed Architecture

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IEEE ACCESS 2023年 11卷 18356-18373页

作者： Amine, Ouardi Mohammed, Mestari Ecole Normale Super Enseignement Tech ENSET Signals Distributed Syst & Artificial Intelligence Mohammadia 28830 Morocco Hassan II Univ Casablanca Dept Math & Comp Sci Casablanca 20000 Morocco

Heuristic search algorithms are informed search strategies that use heuristics to estimate the minimal cost of the path from the current state to the goal. Using this additional knowledge, this type of algorithms can distinguish non-goal states, and then directs its search towards those that look more promising. This makes these algorithms faster than uninformed search algorithms. The A* algorithm is a well-known example of heuristic-based algorithms that is guaranteed to find the least-cost path to a goal state if the heuristic used is admissible, which means that it never overestimates the real cost from the current state to the goal. In this article, we are going to present a neural network architecture that makes it possible to predict admissible heuristics for a given graph and destination node, then we are going to refine our models using genetic algorithms in order to obtain better results.

关键词： Neural networks genetic algorithms a star algorithm graphs heuristics path finding PyTorch Azure databricks distributed computing

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Multi-UAV avoiding barrier problem based on the improved artificial potential afield nd A-star algorithm 24

Multi-UAV avoiding barrier problem based on the improved art...

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International Conference on algorithms, Software Engineering, and Network Security (ASENS)

作者： Chen, Yixuan Shanxi Normal Univ Taiyuan 041081 Shanxi Peoples R China

ISBN: (纸本)9798400709784

At present, the performance of a single UAV gradually cannot meet the needs of the development of human society. The key to the use of the UAV fleet lies in the technology of collaborative control. Existing uav collaboration technologies, such as group intelligence algorithm, deep reinforcement learning method and artificial potential field method, all have some deficiencies. This paper aims to obtain A collaborative artificial quadrotor UAV group that can effectively avoid obstacles by combining the improved artificial potential field algorithm and A-star algorithm. First, record the UAV obstacle avoidance test data to verify the superiority of the new algorithm. For the traditional artificial potential field function, improve the repulsion field function, introduce the distance between the quadrotor UAV and the target point in the repulsion field function;the artificial potential field algorithm is used for global route planning, the a star algorithm is used to avoid local obstacles, set the dangerous distance between the UAV and obstacles. When the dangerous distance is less than or equal between the two, the map is grid and the a star algorithm is used to avoid obstacles. Finally, a group of drones with efficient obstacle avoidance is obtained in the form of main-following formation.

关键词： Uav group Artificial potential field method a star algorithm Main-from following Obstacle avoidance

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A star Search algorithm for Civil UAV Path Planning with 3G Communication 10

A Star Search Algorithm for Civil UAV Path Planning with 3G ...

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10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP)

作者： Tseng, Fan-Hsun Liang, Tsung-Ta Lee, Cho-Hsuan Chou, Li-Der Chao, Han-Chieh Natl Cent Univ Dept Comp Sci & Informat Engn Taoyuan Taiwan Natl Ilan Univ Dept Elect Engn Ilan Taiwan Natl Ilan Univ Dept Comp Sci & Informat Engn Ilan Taiwan Natl Dong Hwa Univ Dept Elect Engn Hualien Taiwan

ISBN: (纸本)9781479953905

The Unmanned Aerial Vehicle (UAV) has been widely applied to various applications, such as the enemy investigation in war, image transmission of military usage by satellite, and the transmission of control signal and image through radio frequency. The civilian UAV typically uses satellite, Global Positioning System (GPS), Wi-Fi or the third generation of mobile phone mobile communications technology (3G) for communications. However, the transmission range limits the data transmission of civilian UAV. In this paper, we utilize the 3G communications and consider the signal quality of Base Stations (BSs) for path planning. We adopt the well-known A star search algorithm to prevent the dead end of signal during flight, and plan the better flight path for civil UAV. The simulation results show that our proposed method acquires the 2.44 times better communication quality and routes with the 1.56 times longer flight only.

关键词： Unmanned Aerial Vehicle Civil UAV a star algorithm Path Planning 3G Communication

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Minimum dose path planning method for virtual nuclear facilities based on navigation mesh

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ANNALS OF NUCLEAR ENERGY 2024年 195卷

作者： Zheng, Anran Liu, Tiancai Song, Yunpeng Wang, Xuesong Liu, Lili Qi, Lin China Inst Atom Energy Beijing 102413 Peoples R China

The operation, maintenance and decommissioning of nuclear facilities have radiation risks. When workers work in the radiation area, it is necessary to carry out radiation protection through path planning. In order to optimize the dose field path planning algorithm, a virtual verification platform for dose field path planning is established based on the Unreal Engine. The platform includes virtual environment, dose field, and personnel dose assess-ment modules, which can meet the needs of dose field path planning algorithm research and optimization. Considering the complexity and variability of the environment in the operation process, a new dose minimum path planning algorithm based on navigation mesh is designed. Based on this algorithm, the number of grids for path planning in complex or large scenes is significantly reduced, and the calculation time of the algorithm is reduced while ensuring the optimal dose. The simulation results show that the minimum dose path planning method based on navigation mesh can effectively reduce path planning time and ensure the safety of personnel during the decommissioning of nuclear facilities.

关键词： Minimum dose path planning Nuclear facilities Navigation mesh a star algorithm Virtual simulation

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Electrical and thermal tortuosity in powder compacts

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GRANULAR MATTER 2007年第6期9卷 401-406页

作者： Montes, J. M. Cuevas, F. G. Cintas, J. Univ Seville Dept Mech & Mat Engn Escuela Super Ingn Seville 41092 Spain

A simple equation to calculate the effective mean path to be travelled by the heat flow or electrical current in a porous powdered material is proposed. In this equation, the effective mean path is a function of the sample porosity degree and the tap porosity of the original powder. This latter parameter determines to a great extent the compact pore structure, since it depends on the powder particle size, shape and distribution. The proposed equation has been validated using real metallographic images from sintered powders compacts. For measurements, a computer program, based on the Pathfinding A* algorithm, has been developed. Results are in very good agreement with theoretical predictions. The proposed equation can be useful to model the electrical and thermal conductivity of sintered compacts.

关键词： tortuosity modelling pathfinding a star algorithm

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Predicting A* search algortihm heuristics using neural networks

Predicting A* search algortihm heuristics using neural netwo...

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IEEE International Conference on Electrical, Computer, and Energy Technologies (ICECET)

作者： Amine, Ouardi Mohammed, Mestari Hassan II Univ Lab Signals Distributed Syst & Artificial Intelli Ecole Normale Super Enseignement Tech ENSET Casablanca Morocco Hassan II Univ Lab Signals Distributed Syst & Artificial Intelli Ecole Normale Super Enseignement Tech ENSET Artificial Intelligence Res Team Casablanca Morocco

ISBN: (纸本)9781665442312

At the opposite side of the uninformed search algorithms, performing a systematic search, heuristic search algorithms are based on multiple rules leading it to estimate, in a predictive way, the minimal cost of the path from the current state to the goal. In this sense, A* algorithm is an example of heuristics-based algorithms that can guarantee to find a least-cost path to a goal state if this algorithm is using an "admissible heuristic". A heuristic is said to be "admissible" if it never overestimates the real path cost from the current state to the goal. Through this article, the main idea consists of developing a Neural Network that can predict those heuristics to further refine the a star algorithm results. During its learning phase, and as inputs, the neural network will have some representative examples in the form of pairs of several problems (graph and destination node) and heuristics ({P1,h1};{P2,h2} ... {Pn,hn}), to finally be able to calculate the best heuristic regardless of the inputs.

关键词： Neural Networks a star algorithm graphs heuristics path finding

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Search Method of disaster inspection coordinated by Multi-UAV 38

Search Method of disaster inspection coordinated by Multi-UA...

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38th Chinese Control Conference (CCC)

作者： ZheZhang JianWu ChengHe Nanchang Hangkong Univ Nanchang 330063 Jiangxi Peoples R China Hongdu Aviat Ind Grp 650 Res Inst Nanchang 330024 Jiangxi Peoples R China

ISBN: (纸本)9789881563972

The use of unmanned aerial vehicle(UAV) for timely and efficient disaster inspection is an important measure to reduce earthquake *** at the problem that complicated terrain of the disaster area and the urgent time of disaster relief, this paper puts forward a multi-UAV collaborative disaster inspection search method, gets the optimal scheme of inspection under the primary disaster and secondary *** such as terrain, inspection time, search area coverage and number of drones are fully taken into account, and the multi-machine cooperative flight model under primary disaster and secondary disaster is established *** with the fastest descent method and the a star algorithm, a route plan is obtained to complete the maximum coverage search in a specified time with *** whole area search route under secondary disaster is obtained by using taboo search algorithm. The simulation results show that the route is reasonable and the maneuverability is strong.

关键词： UAV Gradient Method Disaster inspection Coverage a star algorithm

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An algorithm Applying To NPC Path Planning Of Web Games

An Algorithm Applying To NPC Path Planning Of Web Games

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International Conference on Mechatronics Engineering and Computing Technology (ICMECT)

作者： Zhang Cheng Zhang Kun Zhang Yingqian He Dan Dalian Univ Technol City Inst Dalian Liaoning 116600 Peoples R China Dalian Univ Finance & Econ Dalian 116622 Peoples R China

ISBN: (纸本)9783038351153

Path planning is the core issues in the artificial intelligence field of games, and how to establish an effective method of path planning is still focused on. A new algorithm based on both the benefits of global path planner methods and local path planner methods and those of a star algorithm and improved artificial potential field method is proposed for NPC path planning in web games. Its feasibleness and effectiveness are also demonstrated by simulation results.

关键词： a star algorithm artificial potential field method path planning artificial intelligence

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Research on optimized multiple robots path planning and task allocation approach

Research on optimized multiple robots path planning and task...

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IEEE International Conference on Robotics and Biomimetics (ROBIO 2006)

作者： Zheng, Taixiong Zhao, Xiangyang Chongqing Univ Posts & Telecommun Dept Automat Chongqing Peoples R China

ISBN: (纸本)9781424405701

In order to minimize the processing time for multiple robots to finish lots of tasks, an optimized multiple robots task allocation and path planning approach is proposed. In this approach, the optimized task sequence is first schemed on the assumption that all the tasks are processed by one robot. While scheming the task sequence, a star algorithm is employed to plan paths and calculate the path cost. Then, according to the number of the robots, the task sequence has been randomly divided into several task segments that will be assigned to robots. At last, the task number of each task segments are averaged according to the time each robot used, so that the optimized task allocation scheme is got. In this approach, not only multiple robot task allocation, but also the optimized path planning is realized to ensure that the robots can finish all the tasks in the shortest time. The experiments and simulation are provided to validate the effectiveness of the approach. The results show that the proposed approach can scheme optimized multiple robots task allocation and path planning scheme.

关键词： task allocation and path planning task allocation path planning a star algorithm

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A SIMULATION MODEL FOR ANALYSING UNMANNED AERIAL VEHICLE FLIGHT PATHS

A SIMULATION MODEL FOR ANALYSING UNMANNED AERIAL VEHICLE FLI...

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24th European Modeling and Simulation Symposium (EMSS)

作者： Cicibas, Halil Demir, Kadir Alpaslan Gunal, Murat M. Arica, Nafiz Turkish Naval Acad Tuzla Dept Comp Engn Istanbul Turkey Turkish Naval Acad Tuzla Dept Ind Engn Istanbul Turkey

ISBN: (纸本)9788897999010;9788897999096

Unmanned Aerial Vehicles (UAVs) are used in a variety of operations in civilian and military domains including search and rescue, surveillance, monitoring, cadastral surveys, and package transportation. Although technological achievements in UAVs made them more intelligent than they were in the past, there is still human factor affecting their operations. Particularly in path planning, operators can improve effectiveness and efficiency of the mission by controlling static and dynamic criteria before the flight and during the flight. However, existence of multiple criteria has made the path planning a difficult task that operators can hardly achieve an optimal path for an UAV. In this paper, we propose a simulation model which can help UAV operators and planners achieve optimal paths. Our model considers environmental factors, performance limitations, basic aviation rules and UAV user requirements.

关键词： Unmanned Aerial Vehicles (UAV) path planning a star algorithm

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