Navigation of Autonomous Tug via Evolutionary Algorithms with Radar Plot Fitness Evaluation

This paper presents an innovative route planning method for autonomous port tugs, using an evolutionary algorithm with radar fitness assessment. The proposed solution takes into account the specifics of tug operation in a complex port environment, characterized by the presence of numerous static obstacles (port infrastructure, islands) and dynamic obstacles (other vessels). The presented radar fitness assessment method allows for taking into account many optimization criteria, such as route length, number of turn points or safety margin with respect to obstacles. The algorithm was tested in four different navigation scenarios of varying complexity. The results of the research showed that, compared to the classic genetic algorithm, the radar method generates routes with fewer turn points (reduction by 1–2 points) and significantly reduces the total course change (up to 53.6%). Additionally, the routes generated by the radar algorithm consistently maintained a greater safety margin with respect to obstacles. The algorithm is prepared to take advantage of data interchange according to International Maritime Organization’s e-navigation proposal via its VHF Data Exchange System (VDES) messages, which could improve the safety of proposed routes and their efficiency. This gives a basis to use the proposed solution as an autonomous vessels and/or formation control algorithm in future automated transport systems.