Path planning and obstacle avoidance control of UUV based on an enhanced A* algorithm and MPC in dynamic environment

Abstract

Addressing the challenges of suboptimal path planning and insufficient dynamic obstacle avoidance for Unmanned Underwater Vehicles (UUVs), this paper presents a composite strategy that merges an enhanced A* path planning algorithm with Model Predictive Control (MPC). This dual-faceted approach synthesizes path planning and trajectory tracking control. Firstly, the six-degree-of-freedom kinematic and dynamic model of the UUV is established based on the modeling method of underwater vehicles. Secondly, an enhanced A* algorithm is implemented to generate an optimal reference path for the UUV within a three-dimensional environment. Subsequently, MPC is employed for trajectory tracking control. When encountering unforeseen dynamic obstacles on the reference path, the system initiates a real-time dynamic re-planning process, modifying the trajectory to circumvent obstacles while optimizing the objective function to guarantee the UUV's safe passage and accurate arrival at the intended destination. The simulation results prove the efficacy of this integrated method, demonstrating notable enhancements in the UUV's capacity for dynamic obstacle avoidance and the execution of real-time path planning.