The paper presents a multiple task-priority inverse kinematics algorithm for a dual-arm aerial manipulator. Both tasks defined as equality constraints and inequality constraints are handled by means of a singularity robust method based on the Null-Space based Behavioral control. The proposed schema is constituted by the inverse kinematics control, that receives the desired behavior of the system and outputs the reference values for the motion variables, i.e. the UAV pose and the arm joints position, and a motion control, that computes the vehicle thrusts and the joint torques. The method has been experimentally validated on a system composed by an underactuated aerial hexarotor vehicle equipped with two lightweight 4-DOF manipulators, involved in operations requiring the coordination of the two arms and the vehicle.

This paper presents the design, control, and experimental validation of a novel fully-actuated aerial robot for physically interactive tasks, named Tilt-Hex. We show how the Tilt-Hex, a tilted-propeller hexarotor is able to control the full pose (position and orientation independently) using a geometric control, and to exert a full-wrench (force and torque independently) with a rigidly attached end-effector using an admittance control paradigm. An outer loop control governs the desired admittance behavior and an inner loop based on geometric control ensures pose tracking. The interaction forces are estimated by a momentum based observer. Control and observation are made possible by a precise control and measurement of the speed of each propeller. An extensive experimental campaign shows that the Tilt-Hex is able to outperform the classical underactuated multi-rotors in terms of stability, accuracy and dexterity and represent one of the best choice at date for tasks requiring aerial physical interaction.

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.

In this paper, an impedance control scheme for aerial robotic manipulators is proposed, with the aim of reducing the end-effector interaction forces with the environment. The proposed control has a multi-level architecture, in detail the outer loop is composed by a trajectory generator and an impedance filter that modifies the trajectory to achieve a complaint behaviour in the end-effector space; a middle loop is used to generate the joint space variables through an inverse kinematic algorithm; finally the inner loop is aimed at ensuring the motion tracking. The proposed control architecture has been experimentally tested.

In this paper, an adaptive trajectory tracking controller for quadrotor MAVs is presented. The controller exploits the common assumption of a faster orientation dynamics w.r.t. the translational one, and is able to asymptotically compensate for parametric uncertainties (e.g., displaced center of mass), as well as external disturbances (e.g., wind). The good performance of the proposed controller is then demonstrated by means of an extensive experimental evaluation performed with a commercially-available quadrotor MAV.