In recent years, the number of robotic applications in public spaces has been growing. Decades of research have given rise to various methods of human-aware robotic navigation. There are a lot of different navigation solutions to guide a robot in presence of humans. Despite multiple surveys comparing existing navigation solutions, few of them take social criteria into account. In this sense, it is difficult to evaluate existing methods and select the one that performs better in a given context. In this article, we first provide a thorough classification of state-of-the-art solutions regarding human-aware robotic navigation solutions. Then, we select a set of measurable criteria to evaluate both the efficiency and the social-compliance of navigation solutions. Using these criteria, we finally compare representative off-the-shelf navigation solutions using the SEAN Simulator to identify the most suitable for human-aware navigation.