research-article

Path planning of mobile robots based on an improved A*algorithm

Authors:

Xiaoyan ChenAuthors Info & Claims

HPCCT & BDAI '20: Proceedings of the 2020 4th High Performance Computing and Cluster Technologies Conference & 2020 3rd International Conference on Big Data and Artificial Intelligence

Pages 49 - 53

https://doi.org/10.1145/3409501.3409524

Published: 25 August 2020 Publication History

Abstract

When an AGV (Automated Guided Vehicle) performs navigation tasks, it needs to run the path planning algorithm to obtain an optimal path in a current environment. In this paper, Dijkstra algorithm and A*algorithm with different heuristic functions are applied to static environment modeling with various types of obstacles. To solve the problem that there are many redundant points and inflection points in the search process of the A*algorithm, an improved A*algorithm with Manhattan distance as a heuristic function is selected as the path planning algorithm. In addition, a calculation method of optimizing a past cost function is proposed, and the weight of heuristic function is optimized simultaneously. Simulation results show that the improved algorithm has a higher efficiency and less path inflection points than the traditional A*algorithm has.

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Cited By

Reda MOnsy AHaikal AGhanbari A(2025)A novel reinforcement learning-based multi-operator differential evolution with cubic spline for the path planning problemArtificial Intelligence Review10.1007/s10462-025-11129-658:5Online publication date: 24-Feb-2025
https://doi.org/10.1007/s10462-025-11129-6
Jeyabal SSachinthana WSamarakoon SElara MSheu B(2024)Hard-to-Detect Obstacle Mapping by Fusing LIDAR and Depth CameraIEEE Sensors Journal10.1109/JSEN.2024.340962324:15(24690-24698)Online publication date: 1-Aug-2024
https://doi.org/10.1109/JSEN.2024.3409623
Vally DBhardwaj V(2024)An Effective Path Planning Optimization in Cellular Networking Based on Key Performance Indicator: A Review2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT61001.2024.10725247(1-11)Online publication date: 24-Jun-2024
https://doi.org/10.1109/ICCCNT61001.2024.10725247
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Index Terms

Path planning of mobile robots based on an improved A*algorithm
1. Networks
  1. Network algorithms
    1. Control path algorithms
      1. Network design and planning algorithms
    2. Network economics

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HPCCT & BDAI '20: Proceedings of the 2020 4th High Performance Computing and Cluster Technologies Conference & 2020 3rd International Conference on Big Data and Artificial Intelligence

July 2020

276 pages

ISBN:9781450375603

DOI:10.1145/3409501

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Xi'an Jiaotong-Liverpool University: Xi'an Jiaotong-Liverpool University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 August 2020

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Funding Sources

Inner Mongolia Natural Science Foundation
National Natural Science Foundation of China
the Program for Scientific Research Projects of Institutions of Higher Learning in Inner Mongolia Autonomous Region
Inner Mongolia Science and technology achievements transformation project

Conference

HPCCT & BDAI 2020

HPCCT & BDAI 2020: 2020 4th High Performance Computing and Cluster Technologies Conference & 2020 3rd International Conference on Big Data and Artificial Intelligence

July 3 - 6, 2020

Qingdao, China

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Cited By

Reda MOnsy AHaikal AGhanbari A(2025)A novel reinforcement learning-based multi-operator differential evolution with cubic spline for the path planning problemArtificial Intelligence Review10.1007/s10462-025-11129-658:5Online publication date: 24-Feb-2025
https://doi.org/10.1007/s10462-025-11129-6
Jeyabal SSachinthana WSamarakoon SElara MSheu B(2024)Hard-to-Detect Obstacle Mapping by Fusing LIDAR and Depth CameraIEEE Sensors Journal10.1109/JSEN.2024.340962324:15(24690-24698)Online publication date: 1-Aug-2024
https://doi.org/10.1109/JSEN.2024.3409623
Vally DBhardwaj V(2024)An Effective Path Planning Optimization in Cellular Networking Based on Key Performance Indicator: A Review2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT61001.2024.10725247(1-11)Online publication date: 24-Jun-2024
https://doi.org/10.1109/ICCCNT61001.2024.10725247
Dong LZhang RWang JLi JWang SWang X(2024)Research on the path planning algorithm and obstacle-crossing motion planning strategy for a cable trench inspection robotRobotica10.1017/S0263574724001930(1-16)Online publication date: 10-Dec-2024
https://doi.org/10.1017/S0263574724001930
Lu HLu CWang HGong JZhu MYang H(2024)Scenario-level knowledge transfer for motion planning of autonomous driving via successor representationTransportation Research Part C: Emerging Technologies10.1016/j.trc.2024.104899169(104899)Online publication date: Dec-2024
https://doi.org/10.1016/j.trc.2024.104899
Ru JNiu QXu H(2024)Global Path Planning for AUV Based on the IACO AlgorithmProceedings of 3rd 2023 International Conference on Autonomous Unmanned Systems (3rd ICAUS 2023)10.1007/978-981-97-1087-4_25(259-268)Online publication date: 23-Apr-2024
https://doi.org/10.1007/978-981-97-1087-4_25
Khlif NKhraief NBelghith S(2024)Comparative Study of Modified Dynamic A-Star Programming and A-Star for Mobile Robot Path PlanningRobotics and Mechatronics10.1007/978-3-031-59888-3_23(251-262)Online publication date: 25-Sep-2024
https://doi.org/10.1007/978-3-031-59888-3_23
Sun YYang JZhao DShu YZhang ZWang S(2023)A Global Trajectory Planning Framework Based on Minimizing the Risk IndexActuators10.3390/act1207027012:7(270)Online publication date: 30-Jun-2023
https://doi.org/10.3390/act12070270
Guo QQiu K(2023) A 2 OP: an A* Algorithm OPtimizer with the Heuristic Function for PCB Automatic Routing 2023 24th International Symposium on Quality Electronic Design (ISQED)10.1109/ISQED57927.2023.10129358(1-1)Online publication date: 5-Apr-2023
https://doi.org/10.1109/ISQED57927.2023.10129358
Utomo DAurelia MTanasia SNurhasanah Handoyo A(2023)Implementation of Dijkstra Algorithm in Vehicle Routing to Improve Traffic Issues in Urban Areas2023 3rd International Conference on Smart Cities, Automation & Intelligent Computing Systems (ICON-SONICS)10.1109/ICON-SONICS59898.2023.10435225(73-78)Online publication date: 6-Dec-2023
https://doi.org/10.1109/ICON-SONICS59898.2023.10435225
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