In the multiple fields covered by Artificial Intelligence (AI), path planning is undoubtedly one of the issues that cover a wide range of research lines. To be able to find an optimal solution, which allows one or several vehicles to establish a safe and effective way to reach a final state from an initial state, is a challenge that continues to be studied today. The increasingly widespread use of autonomous vehicles, both aerial and ground-based, make path planning an essential aspect for incorporating these systems into an endless number of applications. Besides, in recent years, the use of Multi-Robot Systems (MRS) has spread, consisting of both Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs), gaining versatility and robustness in their operation. The possibility of using heterogeneous robotic teams allows tackling, autonomously, and simultaneously, a wide range of tasks with different characteristics in the same environment. For this purpose, path planning becomes a crucial aspect and, for this reason, this work aims to offer a general vision of trajectory planning, to establish a comparison between the methods and algorithms present in the literature for the resolution of this problem within MRS, and finally, to show the applicability of these methods in different areas, together with the importance of these methods for achieving autonomous and safe navigation of different types of vehicles. This work was supported also by the Comunidad de Madrid Government through the Industrial Doctorates Grants (GRANT IND2017/TIC-7834). Publicado
