The advancement of autonomous cargo ships requires dependable anchoring operations, which present significant challenges stemming from reduced maneuverability at low speeds and vulnerability to anchorage disturbances. This study systematically investigates these operational constraints by developing anchoring decision-making methodologies. Safety anchorage areas were quantitatively defined through integration of ship specifications and environmental parameters. An available anchor position identification method based on grid theory, integrated with an anchorage allocation mechanism to determine optimal anchorage selection, was employed. A multi-level guided anchoring trajectory planning algorithm was developed through practical anchoring. This algorithm was designed to facilitate the scientific calculation of turning and stopping guidance points, with the objective of guiding a cargo ship to navigate towards the designated anchorage while maintaining specified orientation. An integrated autonomous anchoring system was established, encompassing perception, decision-making, planning, and control modules. System validation through digital simulations demonstrated robust performance under complex sea conditions. This study establishes theoretical foundations and technical frameworks for enhancing autonomous decision-making and safety control capabilities of intelligent ships during anchoring operations.
Zhu et al. (Mon,) studied this question.