In order to optimize the control direction of ship obstacle avoidance trajectory, improve the stability and safety of ship maneuvering, a high-precision simulation model of ship obstacle avoidance trajectory motion based on improved particle swarm optimization algorithm is proposed. The parameter model and kinematic model of ship obstacle avoidance trajectory motion are constructed, considering various constraint conditions such as obstacle avoidance, energy consumption minimization, and time efficiency optimization. The constraint function of ship obstacle avoidance trajectory motion planning is constructed, and the improved particle swarm optimization algorithm is used to achieve the optimal parameter regression analysis and solution of ship obstacle avoidance. PSO with rotating surface transformation is adopted Algorithm monitors the current optimal function value of each particle, and when it falls into a local minimum, collision avoidance is achieved through the artificial potential field method that jumps out of ship dynamic targets and static obstacles. The target point position factor is introduced to improve the gravitational potential field function, achieving high-precision planning and design of ship obstacle avoidance trajectory motion. The simulation results show that using this method for ship obstacle avoidance trajectory simulation can guide the target to avoid obstacles, with the characteristics of low computational complexity and strong real-time performance, improving the efficiency of data, and increasing the accuracy of ship collision avoidance from 82.5% before improvement to 92.5%.

Sha Depeng, Chang Yunlong, Xie Jinpeng. High precision simulation of ship obstacle avoidance trajectory motion based on improved particle swarm optimization algorithm. Academic Journal of Computing & Information Science (2026), Vol. 9, Issue 8: 98-106. https://doi.org/10.25236/AJCIS.2026.090812.

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