Study of Robot Path Planning with Improved A* And DWA Algorithm Fusion

Authors

  • Jiayi Chen
  • Josef Cheng

DOI:

https://doi.org/10.54097/vkb7a649

Keywords:

Mobile robot; Path planning; Improved A* algorithm; DWA algorithm; Floyd algorithm; Algorithm fusion.

Abstract

For some problems of the traditional A* algorithm in robot path planning, such as inefficient search, many and complex inflection points in the designed and realized paths, as well as the inability to complete real-time dynamic path planning for obstacle avoidance, this paper proposes an improved A algorithm and combines it with Floyd for path rounding, and finally with DWA (Dynamic Window Approach) algorithm to be Fusion. In the improved A* algorithm, a carefully normalized random obstacle environment is used and the search process is optimized by reducing the search direction and redundant nodes. Meanwhile, the evaluation function is adjusted to achieve the optimal global design solution, and path optimization and obstacle avoidance are performed by the DWA algorithm. The experimental results finally show that when the robot is in a complex environment, the fusion algorithm can ensure the completion of the globally optimal route while avoiding obstacles in a timely and effective manner, which realizes more efficient path planning.

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References

Yang W.H. A review of AGV technology development[J]. Logistics Technology and Application,2015,20(11):93-95

JIAOZ,MAK,RONGY,etal.A path planning method using adaptive polymorphic ant colony algorithm for smart wheelchairs[J].Journal of Computational Science,2018(25):50-57.

Yifan Lin, Yanjie Chen, Bingwei He, et al. Motion planning method for mobile robots without collision detection RT*[J]. Journal of Instrumentation, 2020,41(10):257-267.

DOOPALAM T,BYAMBAA D,DEOK J L.Hybridmotion planning method for autonomous robots usingkinect based sensorfusion and virtual plane approach in dynamic environments [J].Journal ofSensors ,2015(5):1-13.

X. Zhang, S. Cheng, X. Hao, et al. A dynamic path planning algorithm for robots that balances global and local characteristics[J]. Journal of Surveying and Mapping Science and Technology, 2018,(3):315-320.

LI Zhiyin,HUANG Yiquing,XU Yuqiong. Improved variable step size ant colony algorithm for mobile robot path planning[J]. Journal of Electronic Measurement and Instrumentation, 2020, 34(8): 15-21.

Zhao Xiao, Wang Zheng, Huang Chengkan, et al. Mobile robot path planning based on improved A* algorithm[J]. Robotics, 2018, 40(6): 903-910.

WU Yi, OU Mingmin, DUAN Liwei. Research on robot path planning based on improved A* algorithm and dynamic window method[J]. Industrial Control Computer, 2020,33(10) 67-70.

CHENG Legend, HAO Xiangyang, LI Jiansheng, et al. Global dynamic path planning by integrating improved A* algorithm and dynamic window method[J]. Journal of Xi'an Jiaotong University, 2017,51(11):137-143.

Y. X. Wang, Y. Y. Tian, X. Li, et al. Adaptive DWA algorithm for traversing dense obstacles[J]. Control and Decision Making, 2019, 34(5): 927-936.

WANG Zhongyu,ZENG Guohui,HUANG Bo,et al. Improved A~* algorithm for robot global optimal path planning[J]. Computer Applications,2019,39(9):2517-2522.

LAO Cailian,LI Peng,FENG Yu. Path planning for greenhouse robots based on the fusion of improved A~* and DWA algorithms[J]. Journal of Agricultural Machinery, 2021, 52(1): 14-22.

WU Feilong,GUO Shiyong. Fusion of improved A* and dynamic window method for AGV dynamic path planning[J]. Science, Technology and Engineering, 2020,20(30):12452-12459.

Chi X, Li H, Fei JY. Research on random obstacle avoidance method for robots based on the fusion of improved A* algorithm and dynamic window method[J]. Journal of Instrumentation, 2021,42(3):132-140.

Geng H. F., Shen J. J. Improvement and validation of A* algorithm on robot path planning[J]. Computer Applications and Software, 2022,39(1): 282-286.

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Published

23-02-2024

Issue

Section

Articles

How to Cite

Chen, J., & Cheng, J. (2024). Study of Robot Path Planning with Improved A* And DWA Algorithm Fusion. Academic Journal of Science and Technology, 9(2), 77-82. https://doi.org/10.54097/vkb7a649