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34th Chinese Control and Decision Conference (CCDC)

作者： Liu, Jiaji Xi, Bao Chen, Si Gao, Fang Wang, Zhao Long, Yujing Informat Sci Acad China Elect Technol Grp Corp Beijing 100080 Peoples R China

ISBN: (纸本)9781665478960

A method combining modified astar algorithm and genetic algorithm was proposed to search the shortest patrol path of autonomous patrol robot. A simplified method was used to transform GPS longitude and latitude coordinate into planimetric rectangular coordinate, which was converted to grid coordinate later. The shortest patrol path network between any two patrol points was constructed by the search results of astar algorithm. The objective function of multipoint patrol path planning problem was established based on the shortest patrol path network, and the global optimal patrol path was obtained by genetic algorithm. The path searched by astar algorithm was optimized by testing the visibility between two cells and removing the redundant nodes. Simulation results show that this method can effectively eliminate redundant nodes, shorten the path length, improve the smoothness of the path, and plan a better patrol path.

关键词： Patrol path planning astar algorithm Genetic algorithm Environment grid map construction

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Source-seeking multi-robot team simulator as container of nature-inspired metaheuristic algorithms and astar algorithm

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EXPERT SYSTEMS WITH APPLICATIONS 2023年第1期233卷

作者： Li, Hui Chu, Zhaoyi Fang, Yuan Liu, Haitao Zhang, Mengyao Wang, Kunfeng Huang, Jingwen Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing 100029 Peoples R China

One driving application for multi-robots is source seeking, especially in the hazardous environment. It consists of two essential subtasks: source location and path search. Nature inspired meta-heuristic is preferable in addressing the source location subtask which is an inversion problem, while the astar algorithm and its variants are widely used for the path search subtask. In this paper, we present a multi-robot team simulator as a container which contains both algorithms as components. The simulator takes the constraints into consideration, including the size and the speed bound of each robot, the obstacle and collision avoidance. We provide a python implementation and example problems for research and test purposes. The well-structured code with object-oriented design can be conveniently upgraded by adding new excellent nature inspired metaheuristics, or extended to other source seeking problems in various field applications. The python code can be downloaded from the website: https://***/buctlab/source-seeking-multi-robot-team-simulator.

关键词： Source seeking simulation Nature-inspired metaheuristic Robot simulator astar algorithm Multi-source location problems Niching methods

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Intelligent Vehicle Path Optimization Based On astar algorithm 24

Intelligent Vehicle Path Optimization Based On Astar Algorit...

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Proceedings of the 2024 International Conference on Intelligent Driving and Smart Transportation

作者： Yang Yu Changzhao Xu Da Han Daili Wei Shandong Huayu University of Technology Dezhou Shandong China

ISBN: (纸本)9798400710667

This paper focuses on the path optimization problem of intelligent vehicles. After comprehensively comparing the advantages and disadvantages of traditional path planning algorithms, the astar algorithm with better comprehensive performance is selected as the basis of path optimization, and the astar algorithm model is improved and optimized in terms of reducing traversal nodes and optimizing redundant turning points of the path. In order to verify the actual effect of the improved astar algorithm in path optimization, this paper selects urban map and vehicle kinematics model as the application objects of the algorithm, and verifies the effect of global path planning and local path planning respectively. The verification results show that the improved astar algorithm is feasible in the actual path planning, and the path is better, which can provide a theoretical basis for the further research of the subsequent astar algorithm.

关键词： astar algorithm

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Efficient path planning for automated guided vehicles using A* (astar) algorithm incorporating turning costs in search heuristic

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2023年第3期61卷 707-725页

作者： Fransen, Karlijn van Eekelen, Joost Vanderlande Ind BV POB 18 NL-5460 AA Veghel Netherlands Eindhoven Univ Technol Dept Mech Engn Control Syst Technol POB 513 NL-5600 MB Eindhoven Netherlands

The path planned for an automated guided vehicle in, for example, a production facility is often the lowest-cost path in a (weighted) geometric graph. The weights in the graph may represent a distance or travel time. Sometimes turning costs are taken into account;turns (and decelerations before and accelerations after turning) take time, so it is desirable to minimise turns in the path. Several well-known algorithms can be used to find the lowest-cost path in a geometric graph. In this paper, we focus on the A* algorithm, which uses an (internal) search heuristic to find the lowest-cost path. In the current literature, generally, either turning costs are not taken into account in the heuristic or the heuristic can only be used for specific graph structures. We propose an improved heuristic for the A* algorithm that can be used to find the lowest-cost path in a geometric graph with turning costs. Our heuristic is proven to be monotone and admissible. Moreover, our heuristic provides a higher lower bound estimate for the actual costs compared to other heuristics found in the literature, causing the lowest-cost path to be found faster (i.e. with less iterations). We validate this through an extensive comparative study.

关键词： Automated guided vehicle path planning A* algorithm astar algorithm turning costs search heuristic

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Path Planning based on astar algorithm in Automatic Driving 22

Path Planning based on Astar Algorithm in Automatic Driving

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Proceedings of the 6th International Conference on algorithms, Computing and Systems

作者： Yunxiang Liu Jianlin Zhu Xubo Liu Xinxin Yuan Computer Science Institute Shanghai Institute of Technology China Automatic driving Division Yingche Technology (Shanghai) Co. Ltd. China

ISBN: (纸本)9781450397407

With the rise of automatic driving technology, it needs to be studied more and more problems, path planning is this paper needs to study, at present, the existing algorithms are mainly some traditional algorithms and some improved algorithms on the traditional algorithms, for example, we are familiar with the automatic driving in the path planning algorithm mainly used astar algorithm, Dijkstra algorithm and in the astar algorithm derived on the basis of the DSTARLITE algorithm, and weight astar algorithm, these traditional algorithms have different shortcomings, some calculations are complex, some convergence speed is slow, so comprehensive reading of the literature, this paper puts forward the study of path planning based on astar algorithm, the Path planning based on astar algorithm can exactly plan the shortest path for the self-driving vehicle in the shortest time.

关键词： Autopilot astar algorithm path planning

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The Path Planning Study of Autonomous Patrol Robot based on Modified astar algorithm and Genetic algorithm

The Path Planning Study of Autonomous Patrol Robot based on ...

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第34届中国控制与决策会议

作者： Jiaji Liu Bao Xi Si Chen Fang Gao Zhao Wang Yujing Long Information Science Academy of China Electronics Technology Group Corporation

A method combining modified astar algorithm and genetic algorithm was proposed to search the shortest patrol path of autonomous patrol robot.A simplified method was used to transform GPS longitude and latitude coordinate into planimetric rectangular coordinate,which was converted to grid coordinate *** shortest patrol path network between any two patrol points was constructed by the search results of astar *** objective function of multipoint patrol path planning problem was established based on the shortest patrol path network,and the global optimal patrol path was obtained by genetic *** path searched by astar algorithm was optimized by testing the visibility between two cells and removing the redundant *** results show that this method can effectively eliminate redundant nodes,shorten the path length,improve the smoothness of the path,and plan a better patrol path.

关键词： Patrol path planning astar algorithm Genetic algorithm Environment grid map construction

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An improved joint space astar algorithm for a 6-DOF manipulator with pre-planning strategy

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Scientific reports 2025年第1期15卷 18164页

作者： Chuangxin He Shuaikai Lian Qian Shi Zhonghua Miao School of Mechatronic Engineering and Automation Shanghai University Shanghai 200444 China. School of Mechatronic Engineering and Automation Shanghai University Shanghai 200444 China. qianshi@***.

Efficiency in manipulator path planning and obstacle avoidance represents a crucial technological challenge in manipulator research. Traditional path planning methods have certain limitations when dealing with the obstacle avoidance for links of manipulator, such as large calculational amount or unstable planned paths. To address this, this paper presents an improved joint space astar algorithm for a 6 degree of freedom (DOF) manipulator with a pre-planning strategy. Firstly, we propose a pre-planning strategy that can refresh start positions and target positions to reduce computational load. Next, we perform a three-dimensional astar path planning method in joint space, which avoids numerous inverse kinematics computations and singularities, and reduces the amount of high-dimensional calculations. In addition to the obstacle avoidance for manipulator end-effector, we also realize the obstacle avoidance for manipulator link. In simulation and experiments, the effectiveness of the proposed path planning algorithm is validated and the path tends to be optimal compared to the conventional astar, RRT and Dijkstra algorithms.

关键词： 6-DOF manipulator astar algorithm Joint space Path planning

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Application of Improved astar algorithm in Global Path Planning of Unmanned Vehicles

Application of Improved Astar Algorithm in Global Path Plann...

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Chinese Automation Congress (CAC)

作者： Xu, Zhe Liu, Xin Chen, Qianglong Beijing Univ Technol Beijing 100124 Peoples R China

ISBN: (纸本)9781728140940

Path planning is a key part of ensuring that smart vehicles are safe and fast to reach their destination. Currently, global path planning mainly uses astar algorithm for search planning. astar algorithm is a heuristic search algorithm, which has been widely used in path planning, but it has many disadvantages, such as: low search efficiency, poor real-time performance, and there are no constraints in search. In view of the shortcomings of astar algorithm, this paper presents Bidirectional search-Binary tree astar algorithm(BBastar), BB-astar algorithm has following improvements: First, binary tree data structure is added to the open table of astar algorithm to optimize the efficiency of the algorithm;Second, use bidirectional search strategy to further improve the efficiency of the algorithm;Thirdly, two kinds of constraint conditions, which must pass through a certain node and a certain road section, are set in the algorithm to make the algorithm more practical. Simulation results show that the search efficiency of the BB-astar algorithm is better than classic astar algorithm, and the search with constraints can be completed.

关键词： Path planning astar algorithm Binary tree bidirectional search strategy

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Improved astar algorithm for path planning of marine robot 37

Improved Astar algorithm for path planning of marine robot

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37th Chinese Control Conference (CCC)

作者： Wang, Zhao Xiang, Xianbo Huazhong Univ Sci & Technol Sch Naval Architecture & Ocean Engn 1037 Luoyu Rd Wuhan 430074 Hubei Peoples R China Shenzhen Huazhong Univ Sci & Technol Res Inst Shenzhen 518057 Peoples R China

ISBN: (纸本)9789881563958

Marine robot plays an important role in the marine research due to its good application prospects. Path planning provides the necessary information for marine robot to accomplish missions, and classic methods for path planning can be roughly divided into pre-planning and realtime planning, in wich astar is an algorithm widely applied in path pre-planning of mobile robot. Classic astar only generates a series of way-points for robots in formation of Descartes coordinate point which is based on a two-value grid map. The result has approximately optimal distance, however, the path does not conform with the motion constraint of robot. This paper proposes an improved algorithm in consideration of the orientation constraint of marine robot for astar algorithm, and introduces related work about environment modeling. Path generated via this proposed method is more appropriate than classic astar's in practical application.

关键词： Marine robot path planning astar algorithm environment modeling

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Improved astar algorithm for path planning of marine robot

Improved Astar algorithm for path planning of marine robot

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第37届中国控制会议

作者： Zhao Wang Xianbo Xiang School of Naval Architecture and Ocean Engineering Huazhong University of Science and Technology Shenzhen Huazhong University of Science and Technology Research Institute

Marine robot plays an important role in the marine research due to its good application *** planning provides the necessary information for marine robot to accomplish missions,and classic methods for path planning can be roughly divided into pre-planning and realtime planning,in wich astar is an algorithm widely applied in path pre-planning of mobile *** astar only generates a series of way-points for robots in formation of Descartes coordinate point which is based on a two-value grid *** result has approximately optimal distance,however,the path does not conform with the motion constraint of *** paper proposes an improved algorithm in consideration of the orientation constraint of marine robot for astar algorithm,and introduces related work about environment *** generated via this proposed method is more appropriate than classic astar’s in practical application.

关键词： Marine robot path planning astar algorithm environment modeling

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