Research on path planning of material transmission platform based on A* and dynamic window method
Papers and Reports|更新时间:2024-04-07
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Research on path planning of material transmission platform based on A* and dynamic window method
Chinese Journal of Intelligent Science and TechnologyVol. 5, Issue 4, Pages: 515-524(2023)
作者机构:
江苏科技大学机械工程学院,江苏 镇江 212100
作者简介:
基金信息:
Jiangsu Key R&D Plan Foundation of China(BE2016009);The Special Experimental Equipment Research Project of Jiangsu University of Science and Technology(210813102001)
TANG Wei, TAN Xiao, SUN Yu, et al. Research on path planning of material transmission platform based on A* and dynamic window method[J]. Chinese Journal of Intelligent Science and Technology, 2023, 5(4): 515-524.
DOI:
TANG Wei, TAN Xiao, SUN Yu, et al. Research on path planning of material transmission platform based on A* and dynamic window method[J]. Chinese Journal of Intelligent Science and Technology, 2023, 5(4): 515-524. DOI: 10.11959/j.issn.2096-6652.202304.
Research on path planning of material transmission platform based on A* and dynamic window method
Due to the problems of traditional material transfer equipment such as single working mode and inflexible adjustment of transfer path
intelligent material transfer system has gradually become a research hotspot in the field of logistics transmission. A path planning algorithm based on A* and dynamic window method was proposed for the modular material transmission platform
in order to improve its obstacle avoidance ability during the transfer process by flexibly adjusting the material transfer path. In the global path planning
the smoothness and static obstacle avoidance of the transmission path were realized by improving the A* weight function and integrating the Bezier curve and matrix interference theory. And by introducing the dynamic window method and extracting the global path key points as transition points for local path guidance of the transmission target
dynamic obstacle avoidance was realized when the path falling into local optimization was avoided. The research results showed that the path planning algorithm based on A* and dynamic window method could reduce the total global path length by 4.6% and the total path turning angle by 42.3%
while the dynamic obstacles could be effectively avoided in the local planning
which verified the rationality of the path planning algorithm.
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references
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