  In this article we present a unified framework based on receding horizon
techniques that can be used to design the three tasks (guidance, navigation and
path-planning) which are involved in the autonomy of unmanned vehicles. This
tasks are solved using model predictive control and moving horizon estimation
techniques, which allows us to include physical and dynamical constraints at
the design stage, thus leading to optimal and feasible results. In order to
demonstrate the capabilities of the proposed framework, we have used Gazebo
simulator in order to drive a Jackal unmanned ground vehicle (UGV) along a
desired path computed by the path-planning task. The results we have obtained
are successful as the estimation and guidance errors are small and the Jackal
UGV is able to follow the desired path satisfactorily and it is also capable to
avoid the obstacles which are in its way.
