A Receding Horizon Navigation and Control System for Autonomous Merchant Ships: Reducing Fuel Costs and Carbon Emissions under the Premise of Safety

Abstract

In order to solve the multi-objective planning and trajectory tracking control problem related to maritime autonomous surface ships (MASSs), a new design scheme for autonomous navigation is proposed in this paper, with a receding horizon navigation and control (RHNC) system that contains navigation and control modules. In the navigation module, we designed a superposition field gradient descent local search algorithm based on the cost field, emission field, and guidance field to navigate the MASS reference path, and in the control module, we designed a nonlinear controller that can handle multiple constraints based on the NMPC framework. Under the new scheme, the navigation module completes local path planning to reduce costs and emissions, the control module accomplishes accurate trajectory tracking and real-time collision avoidance, and the information is transmitted in both directions between the two modules to collaboratively complete the MASS navigation and control tasks. We conducted a simulation study of the navigation algorithm and controller and the autonomous navigation system using a Kriso Container ship (KCS). The simulation results demonstrate the effectiveness of the proposed cooperative design scheme in reducing navigation costs and emissions and avoiding autonomous collision avoidances.

Keywords

• navigation and control system
• field theory
• nonlinear model predictive control
• maritime autonomous surface ships