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An Improved A-star Path Planning algorithm Based on Mobile Robots in Medical Testing Laboratories

SENSORS 2024年第6期24卷 1784页

作者： Yin, Chengpeng Tan, Chunyu Wang, Chongqin Shen, Feng Harbin Engn Univ Sch Mech & Elect Engn Harbin 150001 Peoples R China Harbin Engn Univ Sch Intelligent Sci & Engn Harbin 150001 Peoples R China Harbin Univ Sci & Technol Sch Elect & Elect Engn Dept Elect Engn Harbin 264300 Peoples R China Harbin Inst Technol Sch Instrumentat Sci & Engn Harbin 150001 Peoples R China

In the blood sample management pipeline environment, we have innovatively improved the traditional a-star algorithm to enhance the efficiency of mobile robots. This study employs a grid environmental modeling approach to accurately simulate medical testing laboratories. On the grid map, we utilize an 8-neighbor search method for path planning to accommodate the complex structure within the laboratory. By introducing an improved evaluation function and a bidirectional search strategy, we have successfully reduced the number of search nodes and significantly improved path search efficiency. Additionally, we eliminate redundant nodes in the path, smooth the path using cubic uniform B-spline curves, remove unnecessary inflection points, and further optimize the motion trajectory of the robot. The experimental results of the path planning simulation under different scenarios and specifications show that the improved a-star algorithm has higher search efficiency and traverses fewer nodes compared to the traditional a-star algorithm and the bidirectional a-star algorithm. Overall, the simulation experiments verify the feasibility of the improved a-star algorithm, which can better meet the needs of actual mobile robots in real medical testing laboratories.

关键词： a-star algorithm path planning bi-directional search path smoothing

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Autonomous land vehicle path planning algorithm based on improved heuristic function of A-star

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INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS 2021年第5期18卷

作者： Zhang, Jing Wu, Jun Shen, Xiao Li, Yunsong Xidian Univ State Key Lab Integrated Serv Networks 2South Taibai Rd Xian 710071 Shaanxi Peoples R China

The path planning of autonomous land vehicle has become a research hotspot in recent years. In this article, we present a novel path planning algorithm for an autonomous land vehicle. According to the characteristics of autonomous movement towards the autonomous land vehicle, an improved A-star path planning algorithm is designed. The disadvantages of using the a-star algorithm for path planning are that the path planned by the a-star algorithm contains many unnecessary turning points and is not smooth enough. Autonomous land vehicle needs to adjust its posture at each turning point, which will greatly waste time and also will not be conducive to the motion control of autonomous land vehicle. In view of these shortcomings, this article proposes a new heuristic function combined with the artificial potential field method, which contains both distance information and obstacle information. Our proposed algorithm shows excellent performance in improving the execution efficiency and reducing the number of turning points. The simulation results show that the proposed algorithm, compared with the traditional a-star algorithm, makes the path smoother and makes the autonomous land vehicle easier to control.

关键词： Autonomous land vehicle path planning algorithm a-star algorithm artificial potential field heuristic function

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IBAS: Index Based A-star

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IEEE ACCESS 2018年 6卷 11707-11715页

作者： Li, Yan Zhang, Hongyan Zhu, Huaizhong Li, Jianwei Yan, Wenjie Wu, Youxi Hebei Univ Technol Sch Econ & Management Tianjin 300401 Peoples R China Hebei Univ Technol Sch Comp Sci & Engn Tianjin 300401 Peoples R China Hebei Prov Key Lab Big Data Calculat Tianjin 300401 Peoples R China

The a-star algorithm is an efficient classical algorithm for solving the shortest path problem. The efficiency of the algorithm depends on the evaluation function, which is used to estimate the heuristic value of the shortest path from the current vertex to the target. When the vertex coordinates are known, the heuristic value of the shortest path is usually generated by the distance. In this paper, we present an Index Based a-star algorithm (IBAS), which aims to solve the shortest path problem in a weighted directed acyclic graph with unknown vertex coordinates. This paper constructs three indexes for each vertex, i.e., the earliest arrival index, reverse earliest arrival index, and latest arrival index. We can compute the lower bound and the upper bound of the shortest distance from the source vertex to the target based on the three indexes and prune the intermediate vertices which are not in shortest path according to the lower and upper bounds. The IBAS algorithm not only makes use of the earliest arrival index to construct the evaluation function of the a-star algorithm but also utilizes the three indexes to prune useless vertices, so as to improve the performance of the algorithm. Compared with the a-star algorithm, the additional time complexity and space complexity of the IBAS algorithm are O(vertical bar V vertical bar + vertical bar E vertical bar) and O(vertical bar V vertical bar), respectively. A real road network and benchmark datasets with large-scale network are selected to verify the performance of IBAS. Experimental results verify the effectiveness of the proposed algorithm.

关键词： Shortest path a-star algorithm pruning strategy index

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Genetic Adaptive A-star Approach for Ttrain Trip Profile Optimization Problems

Genetic Adaptive A-Star Approach for Ttrain Trip Profile Opt...

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IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS)

作者： Huang, Jin Sun, Lei Du, Fangyu Wan, Hai Zhao, Xibin Tsinghua Univ KLISS TNLIST Sch Software Beijing 100084 Peoples R China Tianjin Univ Coll Precis Instrument & Optoelect Engn Tianjin 300072 Peoples R China

ISBN: (纸本)9781479944972

Genetic adaptive A-star searching algorithm for optimizing the running profile of a train in a trip under certain constraints is studied. The train trip profile optimization problem is formulated as a multi-constraints nonlinear optimization problem, and the corresponding use of A-star searching algorithm is introduced. NSGA-II is employed for the adaptive parameters selection of A-star searching algorithm. A main structure with the cooperation of NSGA-II and a-star algorithm is proposed. A practical train trip optimization problem is employed for illustrating how the proposed approach works.

关键词： Train Trip Profile optimization a-star algorithm genetic adaptive

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Research on Path and Sequence Planning for Multi-Cabin Onboard Transportation of Large Cruise Ships

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APPLIED SCIENCES-BASEL 2025年第8期15卷 4406-4406页

作者： Ju, Liyang Wu, Xiaoyuan Zhao, Yixi Liu, Jianfeng Liu, Kun Shanghai Jiao Tong Univ Sch Mech Engn Shanghai 201109 Peoples R China Shanghai Waigaoqiao Shipbldg Co Ltd Shanghai 200137 Peoples R China Jiangsu Univ Sci & Technol Sch Naval Architecture & Ocean Engn Zhenjiang 212100 Peoples R China

The utilization of PMCUs (Prefabricated Modular Cabin Units) is a key strategy for enhancing the efficiency and reducing the costs of large cruise ship construction. Effective transportation planning for multiple PMCU cabins, including the paths and sequence, is vital to ensure smooth and timely installation. However, traditional a-star algorithms for path planning face limitations when it comes to accounting for boundary obstacles, and existing routine sequence planning methods can hardly tackle multi-cabin coupled blocking effects. To address these challenges, an enhanced a-star algorithm is introduced and designed to handle both grid-based and boundary obstacles in the path planning process for cabin transportation onboard. Additionally, a novel reverse planning strategy is further proposed that addresses the coupling effects arising from inter-cabin mutual blocking by determining the optimal collision-free installation sequence. Integrated with the enhanced a-star algorithm, this reverse planning strategy effectively eliminates interference between cabin transportation sequences and transportation paths, significantly improving operational efficiency. A comparative analysis across various scenarios further substantiates the practicality and effectiveness of the proposed method, highlighting its potential for real-world application in large-scale cruise ship construction.

关键词： cabin transportation path planning sequence planning a-star algorithm

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Spot-welding path planning method for the curved surface workpiece of body-in-white based on a memetic algorithm

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2021年第9-10期117卷 3083-3100页

作者： Zhao, Hang Zhang, Bangcheng Sun, Jianwei Yang, Lei Yu, Haiyue Changchun Univ Technol Coll Mech & Elect Engn Changchun 130012 Peoples R China AW Tooling Die Mfg CO LTD Welding & Assembly Dev Dept Changchun 130013 Peoples R China

Aiming at the problem of complex path planning in the processing of curved surface workpieces of body-in-white, a hybrid path planning method based on a memetic algorithm is proposed. The method is divided into two parts: welding sequence planning and welding path planning between weld points. By establishing the kinematic model of a spot welding robot based on the pipper criterion and z-y-z Euler angle solution method, the motion constraints of path optimization are analyzed. Under the framework of the memetic algorithm, the improved a-star algorithm with redundant node deletion and a post-smoothing process is used to obtain the smooth collision-free optimal path set between weld points and to construct the objective function of travelling all weld points with the shortest path length and highest smoothness. The multiobjective elitist-simulated annealing genetic algorithm (MESAGA) is used to achieve the welding sequence planning of all weld points. The variable neighborhood search method improves the mutation operator;the elitist strategy is introduced to improve the probability of elitist individual crossover and mutation operation, and a simulated annealing algorithm is used to jump out of local search to obtain the global optimal solution. According to the motion constraints, the joint space path is obtained by the optimal path in Cartesian space. Simulation analysis results demonstrate that the hybrid path planning method based on the memetic algorithm can effectively optimize the path of spot welding robots and lay the foundation for control and trajectory planning during welding processes.

关键词： Welding robot Welding path planning Memetic algorithm Genetic algorithm a-star algorithm

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Application of the tortuous surface method to stochastic analysis of bimslope stability

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BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT 2020年第10期79卷 5329-5340页

作者： Montoya-Araque, Exneyder A. Suarez-Burgoa, Ludger O. Medley, Edmund W. Univ Nacl Colombia Grp Invest Geotecnia Fac Minas Medellin Colombia Terraphase Engn Oakland CA 94612 USA

This article presents a summary of the research on the novel tortuous surface method to stochastically analyze the stability of two-dimensional bimslopes, which are slopes composed of bimrocks or bimsoils. Tortuous failure surfaces (TFSs) are slip surfaces that develop around blocks when bimslopes fail. The method was automated through an algorithm that locates a slip surface passing around the blocks as if it were the solution of a "maze puzzle." Slope stability analyses were performed using the limit equilibrium method (LEM). To compare many different models, the normalized factor of safety of a TFS (f(n)*) was computed. f(n)* is obtained by dividing the f(s) from the 11S by the f(s) from the surface potentially produced when there are no blocks (the critical circular surface or the matrix-only surface (MOS)). Two groups of analyses were performed. First, two tortuosity parameters, the tortuous length ratio (TLR) and the average tortuous width (ATW), were analyzed through the evaluation of a hypothetical slope of 10 m height and 35 degrees inclination with varying block proportions. Second, similar hypothetical models were developed with three different values of the slope height, slope inclination, and ratio of the unit weight of the blocks to the unit weight of the matrix;then, the behavior of f(n)* for different values of both the cohesion and friction angle of the matrix was presented in a sensitivity analysis. A prime conclusion of the research is that for prudent geotechnical design, stochastically based stability analyses of bimslopes are far preferable to deterministic analyses.

关键词： Bimrocks and bimsoils Bimslopes Tortuous failure surface Slope stability assessment Sensitivity analyses a-star algorithm

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Development of a numerical marine weather routing system for coastal and marginal seas using regional oceanic and atmospheric simulations

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OCEAN ENGINEERING 2020年第0期195卷 106706-000页

作者： Kurosawa, Kenta Uchiyama, Yusuke Kosako, Taichi RIKEN Ctr Computat Sci Kobe Hyogo Japan Univ Maryland Dept Atmospher & Ocean Sci College Pk MD 20742 USA Kobe Univ Dept Civil Engn Kobe Hyogo Japan Port & Airport Res Inst Coastal & Estuarine Environm Dept Yokosuka Kanagawa Japan

The primary objective of this study is to develop a new weather routing system for vessel navigation in coastal and marginal seas based on the a-star algorithm. The cost function inherent in the original a-star algorithm is modified to account for oceanic and atmospheric conditions around the vessel of interest. Three options are introduced to search for optimal paths with the shortest travel distance, shortest travel time, and minimal fuel consumption. An avoidance algorithm for unsafe conditions is further incorporated to exempt any arbitrary area from the navigation solution. Furthermore, a compact ocean circulation model based on the Regional Ocean Modeling System executable on typical laptop PCs is configured for a vessel-borne weather routing system;the system is successfully applied to evaluate the optimal vessel paths in the Seto Inland Sea, where high-frequency tidal currents modified by complex topography make it essential to alter the vessel's speed.

关键词： Weather routing a-star algorithm ROMS Kuroshio Optimal route Numerical simulations

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A Novel Real-Time Penetration Path Planning algorithm for Stealth UAV in 3D Complex Dynamic Environment

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IEEE ACCESS 2020年 8卷 122757-122771页

作者： Zhang, Zhe Wu, Jian Dai, Jiyang He, Cheng Nanchang Hangkong Univ Sch Informat Engn Nanchang 330063 Jiangxi Peoples R China Beihang Univ Sch Reliabil & Syst Engn Beijing 100191 Peoples R China

In recent years, stealth aircraft penetration path planning has been a significant research subject in the field of low altitude combat. However, previous works have mainly concentrated on the path planning for stealth unmanned aerial vehicle(UAV) in 2D static environment. In contrast, this paper addresses a novel real-time path planning algorithm for stealth UAV to realize the rapid penetration, which aims to devise a route penetration strategy based on the improved a-star algorithm to address the problems of replanning for stealth UAV in 3D complex dynamic environment. The proposed method introduces the kinematic model of stealth UAV and detection performance of netted radar in the process of low altitude penetration. Additionally, POP-UP threats are adopted into three different threat scenarios, which is closer to the real combat environment. Moreover, further combined with the prediction technique and route planning algorithm, the multi-step search strategy is developed for stealth UAV to deal with POP-UP threats and complete the replanning of the route in different scenarios. Furthermore, the attitude angle information is integrated into the improved a-star algorithm, which reflects the characteristics of the dynamic radar cross section(RCS) and conforms to the actual flight requirements for the stealth UAV. Finally, the improved a-star algorithm, the sparse A-star search (SAS), and the dynamic a-star algorithm(D-star) are respectively adopted to address the problem of penetration route planning for stealth UAV in three different threat scenarios. Numerical simulations are performed to illustrate that the proposed approach can achieve rapid penetration route planning for stealth UAV in a dynamic threat scenario, and verify the validity of the improved a-star algorithm which is compared to the other two algorithms

关键词： Stealth unmanned aerial vehicle dynamic radar cross-section netted radar real-time path planning a-star algorithm

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Automatic generation of tortuous failure surfaces in block-in-matrix materials for 2D slope stability assessments

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COMPUTERS AND GEOTECHNICS 2019年第Aug.期112卷 17-22页

作者： Montoya-Araque, Exneyder A. Suarez-Burgoa, Ludger O. Univ Nacl Colombia Dept Ingn Civil Grp Invest Geotecnia Medellin Colombia

We present an initial criterion-based methodology to automatically generate tortuous failure surfaces that can be used for different geotechnical applications, such as slope stability assessments of block-in-matrix materials. The methodology consists of two main steps: firstly, the structure of the material must be represented as a grid graph and, secondly, the optimal pathfinding algorithm A* is applied to the graph;both steps are described in detail. The proposed formulation is validated by comparing the outcome with a direct shear test assembly modeled through the finite-element method and, in the end, we present an example of the methodology applied to a slope.

关键词： a-star algorithm Grid graph Tortuous failure surface Slip surface Blocks-in-matrix materials Bimrocks and bimsoils

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