Paolo Robuffo Giordano

TL;DR: The additional set of four control inputs actuating the propeller tilting angles is shown to yield full actuation to the quadrotor position/orientation in space, thus allowing it to behave as a fully actuated flying vehicle.

TL;DR: This paper proposes a novel actuation concept in which the quadrotor propellers are allowed to tilt about their axes w.r.t. the main Quadrotor body, and proposes a nonlinear trajectory tracking controller based on dynamic feedback linearization techniques.

Abstract: Robustness and flexibility constitute the main advantages of multiple-robot systems with respect to single-robot ones as per the recent literature. The use of multiple unmanned aerial vehicles (UAVs) combines these benefits with the agility and pervasiveness of aerial platforms [1], [2]. The degree of autonomy of the multi-UAV system should be tuned according to the specificities of the situation under consideration. For regular missions, fully autonomous UAV systems are often appropriate, but, in general, the use of semiautonomous groups of UAVs, supervised or partially controlled by one or more human operators, is the only viable solution to deal with the complexity and unpredictability of real-world scenarios as in, e.g., the case of search and rescue missions or exploration of large/cluttered environments [3]. In addition, the human presence is also mandatory for taking the responsibility of critical decisions in high-risk situations [4].

TL;DR: A rigorous analysis of the system stability and steady-state characteristics and validate performance through human/hardware-in-the-loop simulations by considering a heterogeneous fleet of unmanned aerial vehicles (UAVs) and unmanned ground vehicles as a case study and provides an experimental validation with four quadrotor UAVs.

TL;DR: In this paper, a semiautonomous haptic teleoperation control architecture for multiple UAVs is proposed, consisting of three control layers: 1) UAV control layer, where each UAV is abstracted by, and is controlled to follow the trajectory of its own kinematic Cartesian virtual point (VP); 2) VP controller layer, which modulates each VP's motion according to the teleoperation commands and local artificial potentials (VP-VP/VP-obstacle collision avoidance and VP-VP connectivity preservation); and 3) teleoperation layer, through which