Autonomous Docking: Trajectory planning and dynamic route adaptation for autonomously docking a marine vessel using Model Predictive Control

Sammanfattning

This thesis presents a comprehensive study on the application of Model PredictiveControl (MPC) for the autonomous docking of marine vessels. The research focuseson developing and implementing trajectory planning and dynamic route adaptationalgorithms that enable a vessel to autonomously dock in various maritime environments. The research on autonomous docking is important for its potential to enhancesafety, efficiency, and reliability in maritime operations, particularly in crowded orchallenging docking scenarios. This technology aims to minimize human error andsimplify the docking procedure in busy marine environments. The key challengesaddressed include path planning, collision avoidance, trajectory tracking, and theintegration of real-time dynamic adjustments to account for moving obstacles andenvironmental changes. Our methodology utilizes MPC to continuously predict andoptimize the vessel’s path, thereby ensuring safe and efficient docking maneuvers. Asimulation environment created in Python and real-world simulations created in aUnity-based environment were utilized to validate the effectiveness of the proposedalgorithm. Simulation results demonstrated a functional trajectory planner capableof successfully following a reference path, avoiding obstacles, and docking a marinevessel in narrow spaces, indicating the potential for using MPC to autonomouslydock a boat. Initial tests in a real-world environment were performed to furtherconfirm the potential of the proposed solution. Comparative performance analysishighlights the strengths and limitations of the system during different conditions,demonstrating its potential for real-world application. Future works aim to enhancethe complexity of the maritime scenarios and vessel dynamics handled by the algorithms, as well as additional testing in real-world environments to further validateand refine the system. The presented analysis also demonstrates the potential foradditional features to improve the stability and reliability of the MPC-based system.This includes the integration of various sensor data for extensive environmental mapping providing real-time updates about the surroundings to ensure a safer dockingprocedure.