ALOS-Based USV Path-Following Control with Obstacle Avoidance Strategy

Path following and obstacle avoidances are used in heading control and path replanning for unmanned surface vessels (USVs), which have attracted the interest of many researchers over the years. This paper investigates the path-following and obstacle avoidance problems for USVs. First, on the basis of the current position and desired path, an adaptive line-of-sight (ALOS) algorithm is used to obtain the desired heading angle, and the sideslip angle compensation is considered. Then, to ensure that the USV follows the desired path. Model predictive control (MPC) is used to reduce the lateral error. The event-triggered mechanism (ETM) strategy is utilized to reduce the computational cost of MPC. Moreover, to obtain accurate state quantities in real time, a linear extended state observer (LESO) is used to counteract the effects of external disturbances and the nonlinear term of the model. Furthermore, an improved obstacle avoidance algorithm based on the geometric relationship is proposed. This method can better ensure USV navigation safety and reduce consumption and computation. Lastly, multiple simulation experiments illustrate that the algorithm improves the path-following capability and security and ensures smooth input changes by setting input constraints. Therefore, the designed controller has better feasibility and robustness.

Automated summary

This paper investigates the problems of path following and obstacle avoidance for unmanned surface vessels (USVs). An adaptive line-of-sight algorithm is used to determine the desired heading angle, and a Model Predictive Control method is employed to reduce lateral error. The event-triggered mechanism strategy is utilized to minimize the computational cost, and a linear extended state observer is used to compensate for external disturbances. An improved obstacle avoidance algorithm based on the geometric relationship is proposed. The results of simulation experiments demonstrate the effectiveness of the proposed approach in improving path following capability and security.