An AUV Path Planning Algorithm Based on Model Predictive Control and Obstacle Restraint

被引:1
|
作者
Liu, Zhaoyang [1 ]
Zhu, Daqi [1 ]
Yan, Mingzhong [1 ]
机构
[1] Shanghai Maritime Univ, Shanghai Engn Res Ctr Intelligent Maritime Search, Haigang Ave 1550, Shanghai 201306, Peoples R China
来源
INTELLIGENT ROBOTICS AND APPLICATIONS, ICIRA 2021, PT IV | 2021年 / 13016卷
关键词
Autonomous underwater vehicle (AUV); Path planning; Obstacle Restraint Model predictive control (OR-MPC); Artificial potential field (APF); Quantum particle swarm optimization (QPSO); ARTIFICIAL POTENTIAL-FIELD;
D O I
10.1007/978-3-030-89092-6_56
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
An Obstacle Restraint Model predictive control (OR-MPC) path planning algorithm with obstacle restraints for Autonomous underwater vehicle (AUV) is presented in this paper. In order 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 waypoint. 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 artificial potential field (APF) path planning algorithm, the proposed OR-MPC can not only avoid large obstacles, but has the best path. Compared with MPC path planning, the proposed OR-MPC algorithm solves the collision problem. The simulation results demonstrate the effectiveness of the proposed control algorithm.
引用
收藏
页码:617 / 627
页数:11
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