Path planning method for UUV homing and docking in movement disorders environment

Area of Science:

• Robotics
• Artificial Intelligence
• Marine Engineering

Background:

• Unmanned Underwater Vehicles (UUVs) require efficient path planning for autonomous operations.
• Docking in complex environments presents significant challenges due to dynamic obstacles and environmental uncertainties.

Purpose of the Study:

• To propose a novel path planning method for UUV homing and docking.
• To enhance the efficiency and safety of UUV navigation in challenging environments.

Main Methods:

• Development of a cost function for path planning.
• Application of a novel particle swarm optimization (NPSO) algorithm to find optimal waypoints.
• Introduction of a fixed-angle docking strategy for UUVs.
• Comparative analysis of NPSO against BPSO, LWPSO, EPSO, and TVAC algorithms using test functions.

Main Results:

• NPSO demonstrated superior searching accuracy and stability for unimodal functions compared to other algorithms.
• NPSO's performance on multimodal functions was comparable to the time-varying acceleration coefficient (TVAC) method.
• Simulations confirmed that the proposed strategy enables UUVs to effectively dodge obstacles and threats, identifying efficient paths.

Conclusions:

• The proposed NPSO algorithm and docking strategy offer a robust solution for UUV path planning and autonomous docking.
• This method improves UUV navigation capabilities, ensuring safe and efficient operations in complex underwater environments.