A Comparative Analysis of Computational Intelligence Methods for Autonomous Navigation of Smart Ships

This paper presents the author’s approaches based on computational intelligence methods for application in the Autonomous Navigation System (ANS) of a smart ship. The considered task is collision avoidance, which is one of the vital functions of the ANS. The proposed methods, applying the Ant Colony Optimization and the Firefly Algorithm, were compared with other artificial intelligence approaches introduced in the recent literature, e.g., evolutionary algorithms and machine learning. The advantages and disadvantages of different algorithms are formulated. Results of simulation experiments carried out with the use of the developed algorithms are presented and discussed. Future trends and challenges of presented smart technologies are also stated.