Obstacle avoidance and trajectory optimisation for an autonomous vessel utilising MILP path planning, computer vision based perception and feedback control

In this study, we investigated autonomous vessel obstacle avoidance using advanced techniques within the Guidance, Navigation, and Control (GNC) framework. We propose a Mixed Integer Linear Programming (MILP) based Guidance system for robust path planning avoiding static and dynamic obstacles. For Navigation, we suggest a multi-modal neural...

Obstacle Avoidance and Trajectory Optimization for an Autonomous Vessel Utilizing MILP Path Planning, Computer Vision based Perception and Feedback Control

The framework of an autonomous vessel is typically composed of three distinct and independent blocks known as the Guidance, Navigation and Control (GNC) system. This paper presents a combination of advanced complementary techniques in the different GNC subsystems to improve upon the current common practices/state of the art in obstacle...

Distributed Leader-Follower Formation Control for Autonomous Vessels based on Model Predictive Control

Formation control of autonomous surface vessels (ASVs) has been studied extensively over the last few years since it offers promising advantages. In this paper, two control methods for distributed leader-follower formation control are proposed: A Nonlinear Model Predictive Control (MPC) method and an MPC method using Feedback Linearization. One...

Model predictive trajectory tracking control and thrust allocation for autonomous vessels

The maneuvering control of autonomous vessels has been under extensive investigations by academic and industrial communities since it is one of the primary steps towards enabling unmanned shipping. In this paper, a model predictive control (MPC) approach is presented for trajectory tracking control of vessels which takes into account the...