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

This paper presents a novel paradigm for physical interactive tasks in aerial robotics allowing reliability to be increased and weight and costs to be reduced compared with state-of-the-art approaches. By exploiting its tilted propeller actuation, the robot is able to control the full 6D pose (position and orientation independently) and to exert a full-wrench (force and torque independently) with a rigidly attached end-effector. Interaction is achieved by means of an admittance control scheme in which an outer loop control governs the desired admittance behavior (i.e., interaction compliance/stiffness, damping, and mass) and an inner loop based on inverse dynamics ensures full 6D pose tracking. The interaction forces are estimated by an inertial measurement unit (IMU)-enhanced momentum-based observer. An extensive experimental campaign is performed and four case studies are reported: a hard touch and slide on a wooden surface, called the sliding surface task; a tilted peg-in-hole task, i.e., the insertion of the end-effector in a tilted funnel; an admittance shaping experiment in which it is shown how the stiffness, damping, and apparent mass can be modulated at will; and, finally, the fourth experiment is to show the effectiveness of the approach also in the presence of time-varying interaction forces.

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 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 paper presents a three-layer control architecture for coordinated control of multiple aerial manipulators (UAVMs): the centralized top layer plans the end-effector desired trajectories of each UAVM; the middle layer, local to each vehicle, computes the corresponding motion references; the bottom layer is a low level dynamic motion controller, which tracks the motion references. At second layer, the overall mission is hierarchically decomposed in a set of elementary behaviors, which are combined together, via the Null Space-based Behavioral approach, into more complex compound behaviors. For each UAVM, the suitable compound behavior to be executed is selected by a supervisor. The proposed framework has been tested through an experimental campaign.