Journal of System Simulation
Abstract
Abstract: There are problems in the traditional RRT* algorithm using a uniform sampling strategy applied in constrained programming problems, such as inaccurate turning guidance of sampling points and unnecessary node cost comparisons, which lead to an increase in additional time costs. To address these issues, an improved RRT* algorithm was proposed. This algorithm leveraged a heuristic function cost of the projected sampling points to make an ellipse prior judgment on the sampling points. Based on the ellipse prior, the sampling points were judged to determine whether they could optimize the path and shorten the programming time. The geodesics were used to further estimate the current cost of the projected sampling points. Simulation results show that the planned path by the improved RRT* algorithm has an average time cost reduction of 73.27% compared to that by the traditional RRT* algorithm and an average path cost reduction of 4.49% compared to the RRT* algorithm that directly incorporates the ellipse prior.
Recommended Citation
Yang, Zhen; Su, Li; and Cheng, Zhiyu
(2025)
"Research on Constrained Programming of Manipulator Using RRT* Algorithm and Ellipse Prior,"
Journal of System Simulation: Vol. 37:
Iss.
10, Article 17.
DOI: 10.16182/j.issn1004731x.joss.24-0545
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol37/iss10/17
First Page
2643
Last Page
2651
CLC
TP391.9
Recommended Citation
Yang Zhen, Su Li, Cheng Zhiyu. Research on Constrained Programming of Manipulator Using RRT* Algorithm and Ellipse Prior[J]. Journal of System Simulation, 2025, 37(10): 2643-2651.
DOI
10.16182/j.issn1004731x.joss.24-0545
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