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...

A Stereovision-based Navigation System for Autonomous Vessels

Sustainability goals have reignited interest in more fuel efficient modalities for urban freight transportation. The autonomous inland vessel has the potential to enable a modality shift to the waterway, however economically-conscious solutions to the technological challenges are lacking. This paper explores the potential role of stereovision...

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...