Robotic motion planning have been, and still is, a very intense research

field. Many problems have been already solved and even real-time, optimal motion

planning algorithms have been proposed and successfully tested in real-world scenarios.

However, other problems are not satisfactory solved yet and also new motion

planning subproblems are appearing. In this chapter we detail our proposed solution

for two of these problems with the same underlying method: non-holonomic planning

and outdoor motion planning. The first is characterized by the fact that many

vehicles cannot move in any direction at any time (car-like robots). Therefore, kinematic

constrains need to be taken into account when planning a new path. Outoor

motion planning focuses on the problem that has to be faced when a robot is going to

work in scenarios with non-flat ground, with different floor types (grass, sand, etc.).

In this case the path computed should take into account the capabilities of the robot

to properly model the environment. In order to solve these problems we are using

the FastMarching Square method, which has proved to be robust and efficient in the

recent past when applied to other robot motion planning subproblems.