Optimized Path Planning and Control for Autonomous Surface Vehicles using B-Splines and Nonlinear Model Predictive Control

In this paper, B-splines are used to solve the problem of online path planning for Autonomous Surface Vehicles (ASVs). The proposed approach is based on bi-directional B-spline curves that takes into account path curvature and involves defining a cost function that minimizes the overall curvature of the path, while ensuring that the final point of the path at each time step is as close as possible to the final goal. Path curvature is especially critical for vehicles that lack high maneuverability, such as some ASVs. The proposed method determines a temporary path using B-spline curves and constrained optimization. The path is updated at each time step based on range sensor data and with constraints defined to avoid discontinuity in the first and second derivatives of the path with respect to time and thus, making the path feasible to track. To integrate the generated path with the ASV, Nonlinear Model Predictive Control (NMPC) is used to ensure path tracking. To evaluate the performance of the proposed approach, simulation experiments are provided which demonstrate the effectiveness and robustness of the integrated path planning and control algorithm in generating feasible paths and accurately controlling the ASV for successful trajectory tracking.