Robot Path Planning Based on Improved A* Algorithm 
and Artificial Potential Field Method

Xiancheng Fan; Xinyu Ling; Hongbin Huang

Robot Path Planning Based on Improved A* Algorithm and Artificial Potential Field Method

Xiancheng Fan, Xinyu Ling, Hongbin Huang

Abstract

In response to the problems of long planning paths, large turning angles, and inability to avoid dynamic obstacles in traditional A*
algorithm robot path planning, this paper proposes a path planning algorithm that combines improved A* algorithm with artificial potential
field method. Firstly, the improved A* algorithm searches the neighborhood and heuristic function. Compared with some algorithms, the
improved A* algorithm reduces the optimal path distance, search nodes, simulation time, and turning angles by 22.78%, 80.65%, 69.84%,
and 50% respectively. The improved A* algorithm is further optimized by removing redundant nodes and smoothing the path, reducing the
optimal path, simulation time, and turning angles by 2.08%, 9.1%, and 36.36% respectively compared to the first optimization. For local path
planning using artificial potential field, the artificial potential field function and adaptive step size are improved. Simulation results show that
the improved algorithm can overcome the problems of local minima and unreachable targets. Finally, the integrated algorithm simulation
shows that it can solve the problem of A* algorithms inability to avoid dynamic obstacles and guide the robot to move along the optimal path.

Keywords

A* algorithm; Robot; Path planning; Artificial potential field; Dynamic obstacles

Full Text:

PDF

Included Database

References

[1] Miyombo Ernest Miyombo, Yong-kuo Liu, Chishinga Milton Mulenga, et al.Optimal path planning in a real-world radioactive environment: A comparative study of A-star and Dijkstra algorithms[J].Nuclear Engineering and Design, 2024, 420(1): 113039.

[2] Chi Xu, Li Hua, Fei Jiyou.Research on Robot Random Obstacle Avoidance Method Based on the Fusion of Improved A * Algorithm and

Dynamic Window Method [J].Journal of Instrumentation, 2021, 42(3):132-140.

[3] Kai Dong, Dewei Yang, Jinbao Sheng, et al. Dynamic planning method of evacuation route in dam-break flood scenario based on the

ACO-GA hybrid algorithm[J].International Journal of Disaster Risk Reduction, 2024, 100(1):104219.

[4] Mohd Nadhir Ab Wahab, Amril Nazir, Ashraf Khalil, et al.Improved genetic algorithm for mobile robot path planning in static

environments[J].2024, 249(1): 123762.

[5] Bodong Tao, Jae-Hoon Kim. Mobile robot path planning based on bi-population particle swarm optimization with random perturbation

strategy[J].Journal of King Saud University - Computer and Information Sciences, 2024, 36(2):101974.

[6] R. Szczepanski.Safe Artificial Potential Field - Novel Local Path Planning Algorithm Maintaining Safe Distance From

Obstacles[J].2023, 8(8):4823-4830.

[7] Yin X, Cai P, Zhao K, Zhang Y, et al. Dynamic path planning of AGV based on kinematical constraint A* algorithm and following DWA

fusionalgorithms[J].Sensors, 2023, 23(8):4102.

[8] II-kyu Ha.Improved A-Star Search Algorithm for Probabilistic Air Pollution Detection Using UAVs[J].sensors, 2024, 24(4):1141.

[9] Raihan Kabir, Yutaka Watanobe, Md Rashedul Islam, et al. Enhanced Robot Motion Block of A-Star Algorithm for Robotic Path

Planning[J].Sensors 2024, 24(5):1422.

[10] Eugene Auh, Juhwak Kim, Younghwan Joo, et al.Unloading sequence planning for autonomous robotic container-unloading system using A-star search algorithm[J]. Engineering Science and Technology, an International Journal, 2024, 50(1):101610.

[11] Tiangen Chang, Guofu Tian.Hybrid A-Star Path Planning Method Based on Hierarchical Clustering and Trichotomy[J].Appl. Sci. 2024,

14(13):5582.

[12] Antonios Chatzisavvas, Michael Dossis, Minas Dasygenis.Optimizing Mobile Robot Navigation Based on A-Star Algorithm for Obstacle Avoidance in Smart Agriculture[J].Electronics 2024, 13(11):2057.

[13] Ju Gao; Xiangrong Xu; Quancheng Pu, et al.A Hybrid Path Planning Method Based on Improved A* and CSA-APF Algorithms[J].

IEEE Access, 2024, 12(1):39139-39151.

[14] Cao, R, Guo, Y, Zhang, Zet al. Global path conflict detection algorithm of multiple agricultural machinery cooperation based on topographic map and time window[J].Comput. Electron. Agric. 2023, 208:107773.

[15] Yuheng Wei, Xinguo Wei, Hao Liu.A Star Identification Graph Algorithm Based on Angular Distance Matching Score Transfer[J].2024,

24(5):6539-6547.

[16] Tao WANG, Gangyi WANG, Xinguo WEI, et al.A star identification algorithm for rolling shutter exposure based on Hough transform[J].

Chinese Journal of Aeronautics, 2024, 37(6):319-330.

Refbacks

There are currently no refbacks.