In this paper a three layer control architecture for multiple aerial robotic manipulators is presented. The top layer, on the basis of the desired mission, determines the end-effector desired trajectory for each manipulator, while the middle layer is in charge of computing the motion references in order to track such end-effectors trajectories coming from the upper layer. Finally the bottom layer is a low level motion controller, which tracks the motion references. The overall mission is decomposed in a set of elementary behaviors which are combined together, through the Null Space-based Behavioral (NSB) approach, into more complex compounds behaviors. The proposed framework has been tested conducting an experimental campaign.

This work tackles the problem of controlling an Unmanned Aerial Vehicle equipped with a robotic Manipulator and it has been developed within the framework of the EU-funded ARCAS (Aerial Robotics Cooperative Assembly System) project. A behavioral control, based on the Null Space-based Behavioral (NSB) paradigm, is proposed to tackle the coordination between the arm and vehicle motions. To this aim, a set of basic functionalities (called elementary behaviors) are designed and combined in a priority order to attain complex tasks (called compound behaviors). The proposed controller has been experimentally validated on a multirotor aircraft with an attached 6 Degree of Freedoms manipulator. Two experimental case studies, involving several compound behaviors, have been reported and the results show the effectiveness of the approach.

In this paper, an impedance control scheme for cooperative quadrotors with robotic arms is proposed in order to limit both the contact forces, due to the object/environment interaction, and the internal forces, due to the manipulators/ object interaction. To this aim, two impedance filters are used to determine the reference trajectories for manipulator end effectors: the first is aimed at conferring a compliant behavior at the object level (external impedance), while the second filter, is aimed at avoiding large internal loading of the object (internal impedance). Such trajectories are fed to a motion controller including an inverse kinematics algorithm and a PD controller with gravity compensation. The effectiveness of the proposed approach is then verified in simulation.