Journal of System Simulation
Abstract
Abstract: In view of the problems of unreachable target areas and easy local minima in traditional artificial potential field methods, an improved artificial potential field method was proposed. The improved algorithm optimized the repulsive field function by introducing obstacle angle factors and distance factors to control the repulsive force magnitude. At the same time, an additional repulsive force towards the target point was added to solve the problem of unreachable target areas in traditional algorithms. When the robot fell into a local minimum, by introducing turning towards obstacles and turning factors to accurately apply escape forces to the robot, the problem of robots easily falling into local minima was effectively solved. Simulation experiments show that in both conventional and complex environments, the improved algorithm can overcome the above problems and plan a smooth path. Compared with other algorithms, the path quality of the improved algorithm is better, and the planning time is shorter.
Recommended Citation
Zhang, Chi and Wei, Wei
(2025)
"Path Planning for Mobile Robots Based on Improved Artificial Potential Field Algorithm,"
Journal of System Simulation: Vol. 37:
Iss.
11, Article 18.
DOI: 10.16182/j.issn1004731x.joss.24-0665
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol37/iss11/18
First Page
2918
Last Page
2926
CLC
TP242
Recommended Citation
Zhang Chi, Wei Wei. Path Planning for Mobile Robots Based on Improved Artificial Potential Field Algorithm[J]. Journal of System Simulation, 2025, 37(11): 2918-2926.
DOI
10.16182/j.issn1004731x.joss.24-0665
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