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A Hybrid Path Planning Method Based on Articulated Vehicle Model

Zhongping Chen1, Dong Wang1, *, Gang Chen2, Yanxi Ren3, Danjie Du4

1 School of Instrument Science and Engineering, Southeast University, Nanjing, 210096, China.
2 School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, 210096, China.
3 32184 PLA Troops, Beijing, 100093, China. 4 North Carolina State University, Raleigh, NC, USA.

* Corresponding Author: Dong Wang. Email: email.

Computers, Materials & Continua 2020, 65(2), 1781-1793.


Due to the unique steering mechanism and driving characteristics of the articulated vehicle, a hybrid path planning method based on the articulated vehicle model is proposed to meet the demand of obstacle avoidance and searching the path back and forth of the articulated vehicle. First, Support Vector Machine (SVM) theory is used to obtain the two-dimensional optimal zero potential curve and the maximum margin, and then, several key points are selected from the optimal zero potential curves by using Longest Accessible Path (LAP) method. Next, the Cubic Bezier (CB) curve is adopted to connect the curve that satisfies the curvature constraint of the articulated vehicle between every two key points. Finally, Back and Forth Rapidly-exploring Random Tree with Course Correction (BFRRT-CC) is designed to connect paths that do not meet articulated vehicle curvature requirements. Simulation results show that the proposed hybrid path planning method can search a feasible path with a 90-degree turn, which meets the demand for obstacle avoidance and articulated vehicle back-and-forth movement.


Cite This Article

Z. Chen, D. Wang, G. Chen, Y. Ren and D. Du, "A hybrid path planning method based on articulated vehicle model," Computers, Materials & Continua, vol. 65, no.2, pp. 1781–1793, 2020.


cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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