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.