skip to main content
10.1145/3517077.3517114acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicmipConference Proceedingsconference-collections
research-article

Based on adaptive improved genetic algorithm of optimal path planning

Published: 22 May 2022 Publication History

Abstract

Aiming at the problem that simple genetic algorithm is easy to fall into local optimum when solving the path planning of mobile robots, an improved adaptive genetic algorithm is proposed for robot path planning. First, use the discontinuous continuity method to initialize the population, and introduce the elitist replacement strategy, so that the individual has a better gene structure and excellent characteristics, and ensure the global optimization; introduce an adaptive adjustment strategy for the crossover and mutation operators to improve the convergence speed of the algorithm. After the mutation operation, the mutation high-quality operator is proposed to keep the mutated individual always optimal; the smoothness index is added to the fitness function, and the penalty factor is introduced to make the planned path more smooth and efficient. Finally, the algorithm is compared with the traditional genetic algorithm. Experimental results show that the improved algorithm has higher search efficiency and can obtain better path planning results.

References

[1]
CONTRERAS-CRUZ MA, AYALA-RAMIREZ V,HERNANDEZ-BELMONTE UH. Mobile robot path planning using artificial bee colony andevolutionary programming[J]. Applied Soft Computing 2015; 30:319-328.
[2]
Wang Chunying, Liu Ping, Qin Hongzheng. A review of intelligent path planning algorithms for mobile robots[J]. Sensors and Microsystems, 2018, 37(08): 5-8.
[3]
Yuan Fulong, Zhu Jianping. Optimal path planning for mobile robots based on improved ant colony algorithm[J]. Modern Manufacturing Engineering, 2021(07): 38-47+65.
[4]
Lin Hanxi, Xiang Dan, Ouyang Jian, Lan Xiaodong. Research review of path planning algorithms for mobile robots [J]. Computer Engineering and Applications, 2021, 57(18): 38-48.
[5]
Xu Mengying, Wang Jiaojiao, Liu Bao, Ma Liang, Chai Linjie, Xiang Li, Zhou Jie. Robot path planning based on improved genetic algorithm[J]. Journal of Shihezi University (Natural Science Edition), 2021,39(03):391- 396.
[6]
Wei Tong, Long Chen. Mobile robot path planning based on improved genetic algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(04): 703-711.
[7]
Kang Yuxiang, Jiang Chunying, Qin Yunhai, Ye Changlong. Robot path planning and experiment based on improved PSO algorithm [J]. Robot, 2020, 42(01): 71-78.
[8]
Vahid Jamshidi and Vahab Nekoukar and Mohammad Hossein Refan. Analysis of Parallel Genetic Algorithm and Parallel Particle Swarm Optimization Algorithm UAV Path Planning on Controller Area Network[J]. Journal of Control, Automation and Electrical Systems: formerly CONTROLE & AUTOMAÇÃO, 2020, 31(1–3): 129-140.
[9]
Sun Bo, Jiang Ping, Zhou Genrong, Lu Yitian. Application of improved genetic algorithm in mobile robot path planning[J]. Computer Engineering and Applications, 2019, 55(17): 162-168.
[10]
Li Shaobo, Song Qisong, Li Zhiang, Zhang Xingxing, Zhe Longxuan. Research review of genetic algorithm in robot path planning[J]. Science Technology and Engineering, 2020, 20(02): 423-431.
[11]
Ge Jike, Qiu Yuhui, Wu Chunming, Pu Guolin. A review of genetic algorithm research[J]. Computer Application Research, 2008(10):2911-2916.
[12]
LAMINI C, BENHLIMA S, ELBEKRI A. Genetic algorithm based approach for autonomous mobile robot path planning[J]. Procedia Computer Science, 2018, 127: 180-189.
[13]
Xi Yugeng, Chai Tianyou, Yun Weimin. A review of genetic algorithms[J]. Control Theory and Applications, 1996(06):697-708.

Cited By

View all
  • (2024)Genetic Algorithm for Mobile Robot Global Path Planning ApplicationProceedings of the 13th National Technical Seminar on Unmanned System Technology 2023—Volume 110.1007/978-981-97-2007-1_14(169-185)Online publication date: 22-Sep-2024
  • (2022)A DDQN-Based Path Planning Method for Multi-UAVs in a 3D Indoor Environment2022 4th International Conference on Control and Robotics (ICCR)10.1109/ICCR55715.2022.10053884(476-480)Online publication date: 2-Dec-2022
  • (2022)Path Planning of Mobile Robot Based on an Improved Genetic Algorithm2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI)10.1109/DTPI55838.2022.9998894(1-6)Online publication date: 24-Oct-2022

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
ICMIP '22: Proceedings of the 2022 7th International Conference on Multimedia and Image Processing
January 2022
250 pages
ISBN:9781450387408
DOI:10.1145/3517077
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]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 May 2022

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. adaptive adjustment strategy
  2. improved genetic algorithm
  3. path planning
  4. smoothing

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Conference

ICMIP 2022

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)7
  • Downloads (Last 6 weeks)1
Reflects downloads up to 20 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2024)Genetic Algorithm for Mobile Robot Global Path Planning ApplicationProceedings of the 13th National Technical Seminar on Unmanned System Technology 2023—Volume 110.1007/978-981-97-2007-1_14(169-185)Online publication date: 22-Sep-2024
  • (2022)A DDQN-Based Path Planning Method for Multi-UAVs in a 3D Indoor Environment2022 4th International Conference on Control and Robotics (ICCR)10.1109/ICCR55715.2022.10053884(476-480)Online publication date: 2-Dec-2022
  • (2022)Path Planning of Mobile Robot Based on an Improved Genetic Algorithm2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI)10.1109/DTPI55838.2022.9998894(1-6)Online publication date: 24-Oct-2022

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format.

HTML Format

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media