Path planning and collision avoidance for autonomous surface vehicles II: a comparative study of algorithms

Abstract Artificial intelligence is an enabling technology for autonomous surface vehicles, with methods such as evolutionary algorithms, artificial potential fields, fast marching methods, and many others becoming increasingly popular solving problems path planning collision avoidance. However, there currently no unified way to evaluate the performance of different example regard safety or risk. This paper a step in that direction offers comparative study current state-of-the art avoidance algorithms vehicles. Across 45 selected papers, we compare important properties proposed related vessel environment it operating in. We also analyse how incorporated, what components constitute objective function these algorithms. Finally, focus on comparing advantages limitations analysed papers. A key finding need platform evaluating under large set possible real-world scenarios.