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In order to solve the problem of intelligent obstacle avoidance when an unmanned surface vehicle navigates autonomously in a complex marine environment, the obstacle avoidance is divided into stationary obstacle avoidance and dynamic obstacle avoidance. Based on the ant colony algorithm, the local path planning of the simplified model of the unmanned surface vehicles is carried out to achieve the static collision avoidance. And in accordance with the Convention on the International Regulations for Preventing Collisions at Sea (COLREGS), a dynamic obstacle model is established and calculated to obtain the changes of the speed and course of the unmanned surface vehicles under different encounters. It is shown through the simulations that the proposed approach considering multiple factors can achieve the automatic collision avoidance.

Because the hydrodynamic coefficients of the unmanned surface vessel (USV) change with the speed during navigation, it is difficult to use a PID controller with constant parameters to control the course since of the model uncertainty. This paper proposes a method to design a gain scheduling PID controller to adapt to different speed navigation. It identifies the maneuvering model parameters in different speed at first. With the accurate model parameters, it designs the PID controller based on the pole placement method. In order to get smooth gain scheduling performance, it uses the interpolation algorithm to calculate the controller parameters between the definite pair of controller parameters. With the USV speed changing, the controller adjusts its parameters according to the design rule. The simulation results show that the gain scheduling PID controller has obvious advantages over the fixed parameter PID controller.