A NOVEL PATH PLANNING ALGORITHM OF AUV WITH MODEL PREDICTIVE CONTROL

Zhaoyang Liu, Daqi Zhu, Chenxia Liu, and Simon X. Yang

Keywords

Autonomous underwater vehicle (AUV), path planning, obstacle restraintmodel predictive control (ORMPC), obstacle restraintartificial potential field–model predictive control (ORAPFMPC)

Abstract

An obstacle restraint–model predictive control (OR-MPC) path planning algorithm with obstacle restraints for autonomous underwater vehicles (AUVs) is presented in this paper. To avoid large-volume obstacles safely, model predictive control and obstacle restraints are combined in this paper. As obstacles are set as restricted areas, the underwater environment is divided into feasible areas and prohibited areas. With OR-MPC, speed increments are generated, which are used to generate path points. Determine whether it meets the restraint. In the case where the restraint is satisfied, an angle is generated that enables the AUV to escape the restricted area. Compared with the obstacle restraint–artificial potential field–model predictive control path planning algorithm, the proposed OR-MPC can not only avoid large obstacles but has the best path. The simulation results demonstrate the effectiveness of the proposed control algorithm.

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