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A path planning algorithm Based on A Heuristic Method

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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XGBoost-Based Heuristic path planning algorithm for Large Scale Air-Rail Intermodal Networks

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INVENTIONS 2025年第2期10卷 27-27页

作者： Weng, Shengyuan Shan, Xinghua Bai, Guangdong Wu, Jinfei Zhao, Nan China Acad Railway Sci Postgrad Dept Beijing 100081 Peoples R China China Acad Railway Sci Corp Ltd Inst Comp Technol Beijing 100081 Peoples R China

It is particularly important to develop efficient air-rail intermodal path planning methods for making full use of the advantages of air-rail intermodal networks and providing passengers with richer and more reasonable travel options. A Time-Expanded Graph (TEG) is used to model the timetable information of public transportation providing a theoretical basis for public transportation path planning. However, if the TEG includes a large amount of data such as train stations, airports, train and air schedules, the network scale will become very large, making path planning extremely time-consuming. This study proposes an XGBoost-based heuristic path planning algorithm (XGB-HPPA) for large scale air-rail intermodal networks, which use the XGBoost model to predict transfer stations before path planning, and quickly eliminate unreasonable transfer edges by adding a heuristic factor, reducing the network scale, thus accelerating the computation speed. Comparative results indicate that XGB-HPPA can markedly enhance computational speed within large-scale networks, while obtaining as many valid solutions as possible and approximating the optimal solution.

关键词： path planning algorithm XGBoost intermodal transportation air-rail transportation network heuristics algorithm

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A path planning algorithm for industrial processes under velocity constraints with an application to additive manufacturing

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JOURNAL OF MANUFACTURING SYSTEMS 2017年第Part1期43卷 160-167页

作者： Giberti, Hermes Sbaglia, Luca Urgo, Marcello Univ Pavia Dipartimento Ingn Ind & Informaz Via A Ferrata 5 I-27100 Pavia Italy Univ Parma Ind Engn Dept Via Sci 181-A I-43124 Parma Italy Politecn Milan Mech Dept Via Masa 1 I-20156 Milan Italy

In the operation of a broad range of industrial processes, the uses of robots whose trajectories are constrained by the velocity of the parts actuated (tools, end effectors, joints and the like) more often than not play a significant role. Keeping our focus on systems for material deposition such as painting, glueing, aerosol spraying but nowadays also additive manufacturing techniques like FDM processes, it is noticeable that a key parameter is the control of the flow of material in accordance with the trajectory velocity of the parts being actuated. According to the specific requirements and goals of different technology, it is possible to generate different trajectories. In this paper, we propose an original path planning algorithm based on the use of Bezier curves aimed at assuring regulation of the velocity and a uniform distribution of the extruded material referring to an innovative additive manufacturing technology. In particular, the paper presents a path planning technology developed for an application where it is necessary to maintain a constant velocity along the length of the trajectory aimed at improving the technological processes on the basis of an innovative additive technology. The paper further presents a working application with a machine prototype so as to demonstrate the viability and performance of the work under consideration. (C) 2017 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.

关键词： path planning algorithm Bezier curves Additive manufacturing Constant feed rate Constant extrusion rate

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Energy management strategy of intelligent plug-in split hybrid electric vehicle based on deep reinforcement learning with optimized path planning algorithm

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2021年第14期235卷 3287-3298页

作者： Xiong, Shengguang Zhang, Yishi Wu, Chaozhong Chen, Zhijun Peng, Jiankun Zhang, Mingyang Wuhan Univ Technol Intelligent Transportat Syst Res Ctr 1178 Heping Ave Wuhan 430000 Peoples R China Wuhan Univ Technol Sch Automot Engn Wuhan Peoples R China Wuhan Univ Technol Sch Management Wuhan Peoples R China Southeast Univ Sch Transportat Nanjing Peoples R China Aalto Univ Sch Engn Dept Mech Engn Marine Technol Espoo Finland

Energy management is a fundamental task and challenge of plug-in split hybrid electric vehicle (PSHEV) research field because of the complicated powertrain and variable driving conditions. Motivated by the foresight of intelligent vehicle and the breakthroughs of deep reinforcement learning framework, an energy management strategy of intelligent plug-in split hybrid electric vehicle (IPSHEV) based on optimized Dijkstra's path planning algorithm (ODA) and reinforcement learning Deep-Q-Network (DQN) is proposed to cope with the challenge. Firstly, a gray model is used to predict the traffic congestion of each road and the length of each road calculated in the traditional Dijkstra's algorithm (DA) is modified for path planning. Secondly, on the basis of the predicted velocity of each road, the planned velocity is constrained by the vehicle dynamics to ensure the driving security. Finally, the planning information is inputted to DQN to control the working mode of IPSHEV, so as to achieve energy saving of the vehicle. The simulation results show the optimized path planning algorithm and proposed energy management strategy is feasible and effective.

关键词： Intelligent hybrid electric vehicle reinforcement learning energy management path planning algorithm

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The use of path planning algorithm using edge computing technology in college football training

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INTERNATIONAL JOURNAL OF GRID AND UTILITY COMPUTING 2022年第2-3期13卷 146-153页

作者： Zhou, Jun Zheng, Yingying NingboTech Univ Qixin Coll Ningbo Zhejiang Peoples R China Wenzhou Univ Coll Phys Educ & Hlth Wenzhou Zhejiang Peoples R China

The purpose is to study the role and influence of football robots on the actual football training in the current popularity of football robot competition. The theoretical basis and key technologies of the football robot system are deeply studied. The design of the wireless communication subsystem, vision subsystem, decision subsystem and fuzzy PID (port ID) control system of the football robot is completed. The application of edge computing in wireless communication subsystem is discussed. The Immune algorithm (IA), Particle Swarm Optimisation (PSO) algorithm and Immune PSO (IPSO) algorithm are compared and analysed. IPSO algorithm is used for path planning of football robots. In the comparison of the three algorithms, the convergence stability of the IPSO algorithm is significantly higher than that of IA and PSO algorithm. This research can arouse the common concern and thinking of the scientific and technological circles and the traditional football circles. It is a new field, and a challenge to traditional football. It plays an important role in the research and development of intelligent robot technology and traditional football training, especially the college football team.

关键词： edge computing path planning algorithm football vision system football training

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UGV Optimal path planning algorithm by using 3D Survivability Map

UGV Optimal Path Planning Algorithm by using 3D Survivabilit...

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10th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)

作者： Kim, Min-Ho Lee, Min-Cheol Pusan Natl Univ Pusan South Korea

ISBN: (纸本)9781479911974;9781479911950

UGV has widely used in the battlefield, thus UGV's survivability technique has become one of the main issue on the path planning algorithm. In this study, 3D survivability map is suggested for UGV survivability, and the optimal path planning algorithm on this map is also suggested. 3D survivability map is a grid map on which the 3D terrain data is combined with the battle field data, and each grid node on the map has UGV's survival probability value. The suggested path planning algorithm finds the optimal path by comparing the survival probability value of the grid nodes. At last, the simulation program has been developed, and the results are shown to verify the suggested algorithm.

关键词： UGV 3D Survival Probability path planning algorithm

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Light weight materials based vehicle secure path planning algorithm for multi constrained QoS routing VANETS 12

Light weight materials based vehicle secure path planning al...

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12th National Web Conference on Recent Advancements in Biomedical Engineering (NCRABE)

作者： Dileepkumar, R. Nagasri, B. Saveetha Sch Engn Dept Comp Sci & Engn Chennai Tamil Nadu India Saveetha Sch Engn Dept Informat Technol Chennai Tamil Nadu India

As the population is get increases the lightweight materials based vehicles are also get increases. When the people wants to move from the once place to another place they use the transport. As the number of vehicles increases the accident are happening day to day in different place. So the safety in the road is decreases. This paper proposes the VANET'S method which is the vehicle and hoc routing. This method can sends the information about the traffic congestion, road path etc to the mobile network. By using the routing method the safety is increased. In transmitting the data the traffic may happen in the message passing path. Due to this traffic in the routing system a novel path data planning is implemented. The traffic may affect the QOS (Quality of security). So the message transmission is made within a period of time. And this proposed system the supports security measure over the data path. This system is more helpful to the people and it solves a current problem which is taking place. This system is mainly depends on the social problem. (c) 2021 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the 12th National Conference on Recent Advancements in Biomedical Engineering.

关键词： Lightweight materials Multi-constrained path planning algorithm Reliable routing Vehicular ad hoc networks

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A Study of path planning algorithm Based on the Survival Probability

A Study of Path Planning Algorithm Based on the Survival Pro...

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12th International Conference of Intelligent Autonomous Systems

作者： Kim, Min-Ho Noh, Chi-Beom Heo, Jung-Hun Lee, Min-Cheol Pusan Natl Univ Dept Mech Engn Pusan 609735 South Korea

ISBN: (纸本)9783642339257

After the development of fusion technology of mechanics, electronics and IT, there are a lot of researches about the autonomous vehicle. For this kind of vehicle to move automatically, it needs the reference input that the vehicle can follow, and this reference input comes from a path planning algorithm. A* is one of the well-known global path planning algorithm that finds the optimal path on the given map using the heuristic cost function. However, A* algorithm gives the vehicle some reference points on the path not the continuous reference path. And A* may not guarantee the path will not collide the corner of the obstacle. To overcome this problem, in this paper, the hybrid path planning algorithm is suggested using B-spline equation and new heuristic cost function with survival probability. At last, we developed the simulation program and the results are shown.

关键词： autonomous vehicle A* algorithm B-spline curve equation path planning algorithm

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Research on path planning algorithm for Virtual Assembly of Power Battery Packs in New Energy Automobiles

Research on Path Planning Algorithm for Virtual Assembly of ...

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International Conference on Robots & Intelligent System (ICRIS)

作者： Yang Jian-dong Hu Hai-yan Jilin Business & Technol Coll Changchun 130062 Peoples R China Changchun Univ Sci & Technol Coll Mech & Elect Engn Changchun 130062 Peoples R China

ISBN: (纸本)9781509041558

In this paper, based on the existing path planning algorithms for virtual assembly used in other countries, a path planning algorithm for virtual assembly of power battery packs in new energy automobiles based on engineering semantics is put forward in combination with actual characteristics of virtual assembly of power battery packs in new energy automobiles, and such assembly paths for power battery packs can be categorized into linear path, revolving path and mixed path. The path planning algorithm for virtual assembly based on engineering semantic improves planning efficiency for assembly of parts of power battery pack in new energy automobiles.

关键词： Power Battery Pack Virtual Assembly path planning algorithm

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UAV path planning algorithm Based on Improved Rapidly-Exploring Random Tree 3

UAV Path Planning Algorithm Based on Improved Rapidly-Explor...

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3rd International Conference on Electronic Information Engineering and Computer Science, EIECS 2023

作者： Wang, Renjie Yang, Ping Liu, Zejian Zhou, Dezong Li, Wensheng School of Electric Power South China University of Technology Guangdong Key Laboratory of Clean Energy Technology Guangzhou China Shenzhen Huagong Energy Technology Co. Ltd Shenzhen China Southern Offshore Wind Power United Development Co. Ltd Zhuhai China China Southern Power Grid Technology Co. Ltd Guangzhou China

ISBN: (纸本)9798350316674

In this paper, a UAV path planning algorithm based on improved rapidly-exploring random tree(RRT) is proposed to solve the problem of high randomness of sampling points and poor smoothness of planned path in the RRT path planning algorithm. In the process of tree expansion,the detection field is developed to limit the generation range of sampling points, and the generation strategy of sampling points is changed, so that the algorithm has the ability to achieve faster convergence to target and round obstacles. In addition, the improved algorithm also cuts the redundant points of the initial track, and uses the B-spline curve method to improve the smoothness of the track. The simulation results show that the UAV path planning algorithm based on the improved RRT reduces the average path length by 21.75%, the average number of tree nodes by 75.78%, and the average calculation time by 48.04% compared with the traditional RRT UAV path planning algorithm. © 2023 IEEE.

关键词： path planning algorithm rapidly-exploring random tree(RRT) UAV

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