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11th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2023

作者： Han, Chengyang Li, Baoying School of Information Science and Engineering Dalian Polytechnic University Liaoning China

ISBN: (纸本)9798350333664

To solve the problems of a∗ algorithm, such as excessive number of redundant nodes, slow search time and sharp turn of path. a new approach is proposed: a five-neighborhood search a∗ algorithm that incorporates dynamic weighting in the heuristic function and utilizes second-order Bezier curve for path smoothing. Through the simulation environment built by PyCharm, it can be seen that the number of redundant nodes and the search time of the a∗ algorithm after dynamic weighting of five neighborhoods are reduced by 86.57% and 82.07% compared with the traditional eight-neighborhood search algorithm, and the cost remains the same in the precision of ten thousand bits. the path obtained after Bezier curve processing has no large angle turning points. After smooth optimization, the continuity of speed and acceleration can be maintained during the driving process, and the driving fluency can be improved. © 2023 IEEE.

关键词： a∗ algorithm dynamic weighting redundant nodes search time second-order Bezier curve

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Research on UAV Path Planning Based on Improved ACO algorithm 11

Research on UAV Path Planning Based on Improved ACO algorith...

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11th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2023

作者： Zheng, Jinyu Sun, Xiyan Ji, Yuanfa Wu, Jianhui Information and Communication School Guilin University of Electronic Technology Guilin China

ISBN: (纸本)9798350333664

Aiming at the shortcomings of traditional ACO algorithm in UAV path planning with more bending times and larger cumulative bending angles, which also has the problems of slow convergence speed and easy to fall into local optimal solutions and deadlock state. This paper proposes an improved ACO algorithm. Firstly, the algorithm adds the valuation function of A ∗ algorithm to the heuristic function and introduces the anti-bending weight coefficient to reduce the number of path bends and the larger cumulative bending angle;Secondly, it proposes to use the pheromone deployment factor to improve the pheromone update rule and enhance the convergence speed and global optimality of the algorithm;Finally, a fallback mechanism plus a pheromone concentration penalty mechanism is introduced to solve the traditional ACO algorithm's tendency to fall into deadlock. The simulation results show that the improved ACO algorithm reduces the number of corners by 73% and the number of iterations by 70% compared with the traditional ACO algorithm in more complex maps. The improved ACO algorithm converges faster and more efficiently, which is more practical guidance for UAV path planning. © 2023 IEEE.

关键词： a∗ algorithm Fallback mechanism Improved ant colony algorithm Pheromone deployment factor UAV path planning

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Dynamic Path Planning of Deep-Sea Mineral Acquisition Vehicle Based on A∗ and DWA algorithm 11

Dynamic Path Planning of Deep-Sea Mineral Acquisition Vehicl...

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11th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2023

作者： Wang, Yiliang Jiangsu Automation Research Institute Jiangsu China

ISBN: (纸本)9798350333664

In order to make deep-sea mineral acquisition vehicle work efficiently in various complex environments, A fusion path planning algorithm is proposed in this paper by combining the improved a∗ algorithm and DWA algorithm. Five kinds of path planning trajectories were built to carry out pathfinding experiments in the simulation environment, including under dense obstacles, 'C' type obstacles, different steering speeds, target points near obstacles, and different weight parameters. The simulation results show that the fusion algorithm can not only ensure the global optimization of the planned path, but also avoid the obstacles in real time when the deep-sea mineral acquisition vehicle meets the unknown obstacles, and meet the requirements of practical applications in complex environment. © 2023 IEEE.

关键词： a∗ algorithm deep-sea mineral acquisition vehicle fusion path planning algorithm real-time obstacle avoidance

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Research on Three-Dimensional Full Coverage Path Planning algorithm for Deep-Sea Mining Vehicles 11

Research on Three-Dimensional Full Coverage Path Planning Al...

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11th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2023

作者： Li, Feng Zhou, Rui Liang, Le Jiangsu Automation Research Institute Lianyungang222061 China

ISBN: (纸本)9798350333664

There are many difficulties for deep-sea mining vehicles to accomplish mining tasks autonomously and efficiently, such as insufficient environmental information, low data processing capabilities of deep-sea mining vehicles, and difficult real-time environmental modeling. This paper proposes a three-dimensional full-coverage path planning algorithm for deep-sea mining vehicles. Firstly, the deep-sea environment information of the mining area is collected by an autonomous underwater robot to construct a three-dimensional static map model. According to the geological type data, a three-dimensional grid model is constructed and the passable and impassable areas are divided. Then, the three-dimensional grid map is divided into multiple flat regions based on the gradient information of the region using the flood fill algorithm, and the minimum transition distance between each flat region is calculated using the Floyd algorithm. Next, a heuristic function is established combining grid status, turning factor, and height information for grid transfer. Considering the problem that mining vehicles will enter dead zones inevitably, the virtual endpoint for leaving the dead zone is found by comprehensively utilizing the distance between grids and the plane minimum transition distance in which the grid is located. To guide the mining vehicle to leave the dead zone and ensure the smallest possible repetition rate, the a∗ algorithm is improved to find the final escape path. Finally, simulation experiments were designed and conducted using Matlab. The results show that the proposed algorithm can ensure a mining coverage rate of 100%, significantly reduce the vertical change of mining vehicles without a significant increase in repetition rate or turning times, reduce energy consumption. The proposed algorithm improves the work efficiency and economic benefits of deep-sea mining vehicles and provides a theoretical basis for underwater path planning of deep-sea mining vehicles. © 2023

关键词： a∗ algorithm deep-sea mining full coverage path planning

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Variable-step-length a∗ algorithm for path planning of mobile robot 29

Variable-step-length A∗ algorithm for path planning of mobi...

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29th Chinese Control and Decision Conference, CCDC 2017

作者： Da, Ke Xiaoyu, Liu Bi, Zhang School of Information Science and Engineering Wuhan University of Science and Technology Wuhan430081 China

ISBN: (纸本)9781509046560

The path planned by the traditional a∗ algorithm is not the shortest and there are too many steps because of the one grid step length. To overcome the drawbacks, an improved a∗ algorithm based on variable-step-length is presented for path planning of mobile robots. The environment of the mobile robot is modeled by the grid method. Considering that the reachable region of the mobile robot may be larger than one grid in each searching step, a variable-step-length scheme is proposed. The path planned in each cycle can be selected from the lines pointing to every grid in the reachable range surrounding the current grid. For the sake that the line distance between two points is the shortest, the planning indices such as the path distance and the step number are all better than those of the polygonal line planned by the traditional a∗ algorithm. Base on the variable-step-length, the searching direction and the improved cost function are designed for the optimal step. The corresponding obstacle avoidance algorithm is also discussed. The proposed variable-step-length a∗ algorithm make the mobile robot to choose an appropriate step according to the current environment and find a shorter and less steps path. The simulation results show the improved algorithm is more efficient for the path planning of the mobile robot. © 2017 IEEE.

关键词： a∗ algorithm Grid Method Mobile Robot Path Planning Variable-Step-Length

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Artificial Intelligence-Based Autonomous Vehicle for Making Real-Time Decisions, and Navigating Safely

Artificial Intelligence-Based Autonomous Vehicle for Making ...

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2023 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2023

作者： Singh, Amanveer Chitkara University Institute of Engineering and Technology Centre for Interdisciplinary Research in Business and Technology Chitkara University Punjab India

ISBN: (纸本)9798350319200

The integration of Manufactured Insights (AI) into independent vehicles has revolutionized the transportation industry by empowering vehicles to explore complex situations with increased accuracy and security. This paper proposes an imaginative approach to real-time decision-making and a secure route utilizing the A∗ calculation in conjunction with Concurrent Localization and Mapping (Pummel). By combining these two methods, the proposed framework points to improving the vehicle's capacity to explore powerfully changing situations while precisely mapping its environment. The A∗ calculation serves as the spine for proficient pathfinding by utilizing a heuristic look approach, guaranteeing the vehicle can select the foremost ideal course to its goal. This calculation powerfully alters its course arranging based on real-time information, empowering the vehicle to adjust quickly to unforeseen obstacles or changes within the environment. Furthermore, the incorporation of Hammer innovation encourages the concurrent mapping of the vehicle's environment and self-localization inside the mapped environment. This permits the vehicle to construct and upgrade an exact outline of its environment in real-time, upgrading its spatial mindfulness and encouraging educated decision-making en route. Moreover, AI-driven decision-making preparation is improved through the integration of machine learning models trained on broad datasets, empowering the vehicle to create complex choices in real-time based on different natural components and verifiable information. The system's brilliant decision-making capabilities guarantee the vehicle can proactively react to potential dangers, barricades, and energetic activity conditions, in this manner prioritizing security while optimizing route proficiency. Through comprehensive recreations and real-world testing, our proposed AI-based independent vehicle framework illustrates remarkable performance in exploring complex and energetic situations, disp

关键词： Artificial Intelligence Autonomous Vehicles a∗ algorithm etc Pathfinding Real-time Decision-making Simultaneous Localization and Mapping (SLAM)

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A new procedure for automatic path planning in bronchoscopy

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Materials Today: Proceedings 2018年第13期5卷 26513-26518页

作者： C. Ciobirca T. Lango G. Gruionu H.O. Leira L.G. Gruionu S.D. Pastrama University Politehnica Department of Strength of Materials Splaiul Independentei 313 Sector 6 060042 Bucharest Romania SINTEF Technology and Society Department of Medical Technology Olav Kyrres gate 9 Trondheim Norway and St. Olavs hospital Prinsesse Kristinas gate 3 Trondheim Norway Edwin L. Steele Laboratory for Tumor Biology Harvard University 55 Fruit Street Boston MA 02114 USA Departament of Circulation and Medical Imaging Faculty of Medicine Norwegian University of Science and Technology and St. Olavs hospital Prinsesse Kristinas gate 3 Trondheim Norway University of Craiova Department of Mechanics Calea Bucuresti nr. 107 200512 Craiova Dolj County Romania

Virtual bronchoscopy is often used for planning a real bronchoscopy procedure. Software applications are developed for virtual bronchoscopy, involving usually segmentation of the tracheobronchial tree from the medical image scan, which is a difficult operation, both conceptually and from the computer implementation and running time point of view. That is why in this paper, a new method for bronchoscopy procedure planning that does not require such a segmentation is presented. The proposed procedure involves automatic path generation between the starting and ending points, skin removal, an algorithm for detection and resolution of collision with the airways walls and validation of the automatically created path. Results are presented for two datasets – one being the representation of a theoretical lungs model, with six levels of branches and the other one being the image scan of a real patient. Together with a system for tracking the bronchoscope during the real procedure, the proposed method can improve the diagnostic success rate of lung cancer using bronchoscopy and decrease the discomfort perceived by the patient.

关键词： Lungs Path planning Virtual bronchoscopy a∗ algorithm

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