Zhongguo Jianchuan Yanjiu (Feb 2021)

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

  • Qingliang LI,
  • Bin LI,
  • Guohao SUN,
  • Xing CUI,
  • Xintao MAO

DOI
https://doi.org/10.19693/j.issn.1673-3185.02209
Journal volume & issue
Vol. 16, no. 1
pp. 89 – 95

Abstract

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ObjectivesCurrently, how to plan the safe and efficient movement trajectory of an unmanned surface vehicle (USV) in local waters with multiple known obstacle positions is a research hotspot.MethodsFirst, the obstacle areas are treated with simple and effective circular and convex quadrilateral envelopes, and the obstacle avoidance problem is transformed into the state inequality constraint of a time optimal control problem. The time optimal control problem is then transformed into an optimal parameter selection problem by control parameterization and time scale transformation. Finally, for multiple continuous state inequality constraints caused by multiple obstacles, the exact penalty function method is used to append all state constraints to the cost function. The final form of the problem is suitable for solving any effective optimization technique as a nonlinear optimization problem.ResultsThe numerical simulation results show that the planned trajectory successfully avoids the obstacles in the water and conforms to the motion characteristics of USVs.ConclusionsThe results of this study can provide valuable references for the obstacle avoidance problem in USV trajectory planning.

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