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Tilted hexarotors embody a technology that remains partially unexploited in terms of its potential, especially concerning precise and concurrent position and attitude control. Focusing on these aerial platforms, we propose two control architectures that can tackle the trajectory tracking task, ensuring also the attitude regulation: one is designed resting on the differential flatness property of the system, which is investigated in the paper, and the other is a hierarchical nonlinear controller. We comparatively discuss the performance of the two control schemes, in terms of the accuracy of both the tracking control action and the attitude regulation, the input effort, and the robustness in the presence of disturbances. Numerical results reveal both the robustness of the hierarchical approach in the case of external disturbance and the accuracy of the differential flatness-based controller in unwindy conditions.

Nowadays, aerial formations are frequently employed in outdoor scenarios to cooperatively explore and monitor wide areas of interest. In these applications, the vehicles are often exposed to relevant security vulnerabilities, as, for instance, the alteration of navigation signals from an attacker with map counterfeiting (if not even hijacking) purposes. In this work, we focus on an Unmanned Aerial Vehicle (UAV) formation that monitors an area, wherein navigation spoofing attacks may occur. Letting the UAVs cooperate and exploiting the redundancy in the available sensing information, a distributed procedure is proposed to i) detect spoofing attacks, and ii) support the navigation in adverse conditions. The validity of the designed approach is confirmed by numerical results. Aerial vehicles for outdoor operation are generally endowed with inertial measurements, relative ranging, and GNSS sensing capability. In this work, two cascaded estimation algorithms for concurrent GNSS spoofing detection and localization in a multi-UAV scenario is proposed, to attain robust navigation in areas subject to GNSS spoofing attacks. The attack detection leverages on information theoretic tools to provide a practical threshold test by checking the multimodal measurement consistency. The localization procedures exploit a decision logic relying on measurement reliability to combine information sources that are different in nature, for UAV self-localization in both safe and under-attack conditions.

This work focuses on bearing rigidity theory, namely the branch of knowledge investigating the structural properties necessary for multi-element systems to preserve the inter-unit bearings under deformations. The contributions of this work are twofold. The first one consists in the development of a general framework for the statement of the principal definitions and properties of bearing rigidity. We show that this approach encompasses results existing in the literature, and also provides a systematic approach for studying bearing rigidity on any differential manifold in SE(3)^n, where n is the number of agents.The second contribution is the derivation of a general form of the rigidity matrix, a central construct in the study of rigidity theory. We provide a necessary and sufficient condition for the infinitesimal rigidity of a bearing framework as a property of the rank of the rigidity matrix. Finally, we present two examples of multi-agent systems not encountered in the literature and we study their rigidity properties using the developed methods

This work proposes a formation control law for multi-agent systems whose components are heterogeneous in terms of actuation capabilities, but at the same time are all able to retrieve bearing information w.r.t. some neighbors in the group. The designed controller exploits the results of the bearing rigidity theory deriving from the modeling of heterogeneous formations as generalized frameworks. The outlined solution is compared with a leader-follower combination of existing rigidity based homogeneous formation controllers in order to highlight the easy tuning, the flexibility w.r.t. the formation composition, and the increased efficiency of the new proposed control approach. A sufficient condition ensuring the convergence of the designed controller is also given.

Cooperative robotics is a trending topic nowadays as it makes possible a number of tasks that cannot be performed by individual robots, such as heavy payload transportation and agile manipulation. In this work, we address the problem of cooperative transportation by heterogeneous, manipulatorendowed robots. Specifically, we consider a generic number of robotic agents simultaneously grasping an object, which is to be transported to a prescribed set point while avoiding obstacles. The procedure is based on a decentralized leader-follower Model Predictive Control scheme, where a designated leader agent is responsible for generating a trajectory compatible with its dynamics, and the followers must compute a trajectory for their own manipulators that aims at minimizing the internal forces and torques that might be applied to the object by the different grippers. The Model Predictive Control approach appears to be well suited to solve such a problem, because it provides both a control law and a technique to generate trajectories, which can be shared among the agents. The proposed algorithm is implemented using a system comprised of a ground and an aerial robot, both in the robotic Gazebo simulator as well as in experiments with real robots, where the methodological approach is assessed and the controller design is shown to be effective for the cooperative transportation task.

In aerial robotics, path following constitutes a popular
      task requiring a vehicle to pursue a given trajectory.
      Resting upon the fulfillment of a desired time law,
      trajectory tracking techniques often turn out to be
      ineffective in presence of external disturbances, favoring
      the adoption of maneuver regulation strategies wherein the
      desired trajectory is parameterized in terms of the
      path-variable. In this scenario, this work proposes a new
      delay-compensating maneuver regulation controller for fully
      actuated aerial vehicles, whose aim is to guarantee the
      perfect tracking of a given path in the shortest time
      interval. The innovative aspect of such a solution relies
      on the introduction of a recovery term that compensates for
      possible delays in
      the task execution. In addition, the dual-quaternion
      formalism is adopted to model the dynamics of the aerial
      platforms allowing feedback linearize the whole system,
      including both position and attitude, with a single
      controller. The tests conducted in Gazebo physic simulator
      show that the proposed controller outperforms the popular
      trajectory tracking PID regulators.

The number of applications involving unmanned aerial vehicles (UAVs) grew dramatically during the last decade. Despite such incredible success, the use of drones is still quite limited in GNSS denied environment: indeed, the availability of a reliable GNSS estimates of the drone position is still fundamental in order to enable most of the UAV applications. Given such motivations, in this paper an alternative positioning system for UAVs, based on low cost ultra-wideband band (UWB) is considered. More specifically, this work aims at assessing the positioning accuracy of UWB-based positioning thanks to the comparison with positions provided by a motion capture (MoCap) system. Since the MoCap accuracy is much higher than that of the UWB system, it can be safely used as a reference trajectory for the validation of UWB estimates. In the considered experiment the UWB system allowed to obtain a root mean square error of 39.4?cm in 3D positioning based on the use of an adaptive extended Kalman filter, where the measurement noise covariance was adaptively estimated.

The use of unmanned vehicles to perform tiring, hazardous, repetitive tasks, is becoming a reality out of the academy laboratories, getting more and more interest for several application fields from the industrial, to the civil, to the military contexts. In particular, these technologies appear quite promising when they employ several low-cost resource-constrained vehicles leveraging their coordination to perform complex tasks with efficiency, flexibility, and adaptation that are superior to those of a single agent (even if more instrumented). In this work, we study one of said applications, namely the visual tracking of an evader (target) by means of a fleet of autonomous aerial vehicles, with the specific aim of focusing on the target so as to perform an accurate position estimation while concurrently allowing a wide coverage over the monitored area so as to limit the probability of losing the target itself. These clearly conflicting objectives call for an optimization approach that is here developed: by considering both aforementioned aspects and the cooperative capabilities of the fleet, the designed algorithm allows controling in real time the single fields of view so as to counteract evasion maneuvers and maximize an overall performance index. The proposed strategy is discussed and finally assessed through the realistic Gazebo-ROS simulation framework.

In this paper, we shed light on two fundamental actuation capabilities of multirotors. The first is the degree of coupling between the total force and total moment generated by the propellers. The second is the ability to robustly fly completely still in place after the loss of one or more propellers, in the case of mono-directional propellers. These are formalized through the definition of some algebraic conditions on the control allocation matrices. The theory is valid for any multirotor, with arbitrary number, position, and orientation of the propellers. As a show case for the general theory, we demonstrate that standard star-shaped hexarotors with collinear propellers are not able to robustly fly completely still at a constant spot using only five of their six propellers. To deeply understand this counterintuitive result, it is enough to apply our theory, which clarifies the role of the tilt angles and locations of the propellers. The theory is also able to explain why, on the contrary, both the tilted star-shaped and the Y-shaped hexarotors can fly with only five out of six propellers. The analysis is validated with both simulations and extensive experimental results showing recovery control after rotor losses.

Standard hexarotors are often mistakenly considered ‘by definition’ fail-safe multi-rotor platforms because of the two additional propellers when compared to quadrotors. However this is not true, in fact, a standard hexarotor cannot statically hover with ‘only’ five propellers. In this paper we provide a set of new general algebraic conditions to ensure static hover for any multi-rotor platform with any number of generically oriented rotors. These are elegantly formulated as the full-rankness of the control moment input matrix, and the non-orthogonality between its null-space and the row space of the control force input matrix. Input saturations and safety margins are also taken into account with an additional condition on the null-space of control moment input matrix. A deep analysis on the hoverability properties is then carried out focusing on the propeller loss in a hexarotor platform. Leveraging our general results we explain why a standard hexarotor is not robust and how it can be made robust thanks to a particular tilt of the rotors. We finally propose a novel cascaded controller based on a preferential direction in the null-space of the control moment input matrix for the large class of statically hoverable multi-rotors, which goes far beyond standard platforms, and we apply this controller to the case of failed tilted hexarotor.