Development of an Energy Model-Based A-Star Algorithm for Energy Efficient Path Planning of Underwater Robots in Ship Hull Cleaning

Abstract

This study presents the development of an energy-based A-Star algorithm for efficient path planning of underwater robots used in ship hull cleaning, motivated by the growing need for energy-efficient autonomous systems operating under complex hydrodynamic conditions such as fluid drag, pressure, and varying underwater currents. The proposed method integrates a physical energy consumption model into the conventional A-Star cost function and is evaluated through numerical simulations in a two-dimensional grid environment representing a ship hull surface, where key parameters including travel distance, drag force, and directional changes are considered to estimate total energy usage. The simulation results demonstrate that the proposed algorithm successfully generates collision-free paths with smoother and more stable trajectories compared to the conventional approach, with recorded energy consumption ranging from 88.73 to 115.99 joules across five scenarios and an average computation time of approximately 0.02 seconds. These findings indicate that incorporating hydrodynamic considerations significantly improves navigation performance while maintaining computational efficiency. In conclusion, the study confirms that the shortest geometric path is not always the most energy-efficient in underwater environments, and the proposed energy-based A-Star algorithm provides a realistic and practical framework for enhancing the sustainability and effectiveness of future autonomous ship hull cleaning systems.