Obstacle avoidance and MPC trajectory tracking&nbsp;of unmanned surface vehicle formation based on&nbsp; improved DWA&nbsp;

SHENG Jinliang, DONG Zaopeng, KUANG Wenqi, LI Zhihao, SUN Pengbo

doi:10.16411/j.cnki.issn1006-7736.2024.04.002

Journal of Dalian Maritime University >

2024 , Vol. 50 >Issue 4: 12 - 21

DOI: https://doi.org/10.16411/j.cnki.issn1006-7736.2024.04.002

Obstacle avoidance and MPC trajectory tracking of unmanned surface vehicle formation based on improved DWA

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(1. School of Naval Architecture, Ocean and Energy Power Engineering, Wuhan University of Technology, Wuhan 430063, China;2. Chinese Shipbuilding Corporation Limited Comprehensive Technical and Economic Research Institute,Beijing 100081,China)

Online published: 2024-06-05

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Abstract

A self-following dual-mode obstacle avoidance model predictive control method based on improved dynamic window method was proposed for the trajectory tracking control problem of unmanned surface vehicle (USV) formation under the influence of sudden obstacles. Firstly, the longitudinal velocity and bow angular velocity oscillation constraints were introduced to reduce the jitter of the velocity and bow angle in the design of the evaluation function of the dynamic window algorithm so as to achieve better integration of obstacle avoidance planning and control. A strategy of calculating the steering azimuth based on intermediate distance was proposed to reduce the sharp turns in the obstacle avoidance process of the USV, while an evaluation term based on the deviation of the predicted and the expected position ending was designed. Meanwhile, the formation keeping information was combined to correct the obstacle avoidance endpoint and reduce the deviation of the USV formation. Secondly, based on the linearized Taylor expansion principle, a prediction model for USV formation was designed. The prediction value of the model was corrected by the prediction error between the system output measurement and the model prediction values. At the same time, a rolling finite time domain iterative online optimization strategy was adopted to propose a trajectory tracking model prediction control method for USV formation that integrated autonomous following dual-mode obstacle avoidance strategy. Finally, a nonlinear disturbance observer was designed to compensate the environmental disturbances, while the Lyapunov function was constructed to prove the stability of the system by combining with the terminal penalty theory. Eventually, the effectiveness and reliability of the proposed USV formation obstacle avoidance and trajectory tracking control algorithm were verified by simulation experiments.

Key words： unmanned surface vehicle (USV) formation; obstacle avoidance planning; trajectory tracking; model predictive control; dynamic window algorithm

Cite this article

SHENG Jinliang, DONG Zaopeng, KUANG Wenqi, LI Zhihao, SUN Pengbo . Obstacle avoidance and MPC trajectory tracking of unmanned surface vehicle formation based on improved DWA [J]. Journal of Dalian Maritime University, 2024 , 50(4) : 12 -21 . DOI: 10.16411/j.cnki.issn1006-7736.2024.04.002

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