Chinese Journal of Ship Research, Volume. 16, Issue 1, 89(2021)

Trajectory planning and automatic obstacle avoidance algorithm for unmanned surface vehicle based on exact penalty function

Qingliang LI1, Bin LI2, Guohao SUN2, Xing CUI3, and Xintao MAO3
Author Affiliations
  • 1College of Electrical Engineering, Sichuan University, Chengdu 610065, China
  • 2School of Aeronautics and Astronautics, Sichuan University, Chengdu 610065, China
  • 3Beijing SunWise Space Technology Co., Ltd., Beijing 100194, China
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    Figures & Tables(11)
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    • Table 1. Simulated data

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      Table 1. Simulated data

      术语名称数值及内容
      最大加速度amax/(m·s−2)2
      最大角速度γmax/(rad·s−1)0.1
      安全阈值ρ/m8
      圆形禁航区1/m$\left( {{x_1},{y_1}} \right) = \left( {452,436} \right),{R_1} = 34\;$
      圆形禁航区2/m$\left( {{x_2},{y_2}} \right) = \left( {88,120} \right),{R_2} = 26\;$
      圆形禁航区3/m$ \left({x}_{3},{y}_{3}\right)=\left(358,78\right),{R}_{3}=34\;$
      圆形禁航区4/m$\left( {{x_4},{y_4}} \right) = \left( {497,306} \right),{R_4} = 45$
      圆形禁航区5/m$\left( {{x_5},{y_5}} \right) = \left( {524,155} \right),{R_5} = 53\;$
      凸四边形禁航区1/m$ \begin{array}{l}\left({k}_{1,1},{k}_{1,2},{k}_{1,3},{k}_{1,4}\right)=\left(-0.35,-0.30,0.79,1.90\right)\\ \left({b}_{1,1},{b}_{1,2},{b}_{1,3},{b}_{1,4}\right)=\left(310.37,469.00,71.86,143.13\right)\end{array}$
      凸四边形禁航区2/m$\begin{array}{l}\left({k}_{2,1},{k}_{2,2},{k}_{2,3},{k}_{2,4}\right)=\left(-0.56,-0.15,0.69,1.52\right)\\ \left({b}_{2,1},{b}_{2,2},{b}_{2,3},{b}_{2,4}\right)=\left(162.00,248.88,-83.99,-158.95\right)\end{array}$
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    Qingliang LI, Bin LI, Guohao SUN, Xing CUI, Xintao MAO. Trajectory planning and automatic obstacle avoidance algorithm for unmanned surface vehicle based on exact penalty function[J]. Chinese Journal of Ship Research, 2021, 16(1): 89

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    Paper Information

    Category: Intelligent Navigation

    Received: Nov. 30, 2020

    Accepted: --

    Published Online: Mar. 27, 2025

    The Author Email:

    DOI:10.19693/j.issn.1673-3185.02209

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