Predictive Path Following and Collision Avoidance of Autonomous Vessels in Narrow Channels

摘要

This paper presents a Nonlinear Model Predictive Control (NMPC) for path-following and collision avoidance of autonomous connected vessels in narrow channels. For each ship, a nonlinear model is used to predict a sequence of the states, using a suitable sampling interval, and then optimize them with respect to a sequence of discretizied control inputs. The objective function of the optimal control problem is to follow the planned path, which is represented by a Bézier curve, with the desired speed. In order to achieve collision avoidance among the networked vessels, an elliptic ship domain is used to represent the geometry of the vessel. A separation condition between each pair of elliptic disks is formulated as time-varying state constraints for the optimization problem. An integrator action is added to the system through the augmentation of the control inputs which facilitate adding constraints on the rate of change of the control inputs. Navigation channels, where the ship is allowed to respect, are represented also by Bézier curves, and are reformulated as nonlinear state constraints to suit the controller algorithm. A real-time C-code is generated using the ACADO toolkit and qpOASES solver with multiple shooting technique for discretization and Gauss-Newton iteration algorithm. This algorithm is computationally efficient, thus enabling real-time implementation of the proposed technique. MATLAB simulations are used to assess the validity of the proposed technique.