The decentralization of formations using onboard sensing is important for multirobot systems, improving the robustness and independence of fleet operations. Bearing measurements (obtainable from embedded cameras) are an attractive choice for use in decentralized formation control, however, this requires that the formation framework be bearing rigid. Rigidity may be checked numerically for a given formation framework, however, it remains difficult to determine the geometric conditions under which otherwise rigid formations become flexible. This article models the sensor and robot constraints in bearing formations of quadrotors as a kinematic mechanism with analogous properties to find geometric conditions for the degeneration of bearing rigidity (singularities) and the resulting uncontrollable motions. A classification of singularities based on graph substructures is developed, and it is shown that arbitrarily large formations may be designed for which all singularities lie within a known set of geometric conditions. An application on how to use the knowledge of all singularity cases in a formation for singularity-free control maintenance is provided.

Formation control of multi-agent systems deals with groups of robots forming specific spatial geometries. Combined with the advancements of unmanned aerial vehicles (UAVs) in the past decade, formation control may potentially be applied to tasks such as search-and-rescue, surveillance, even collaborative manipulation. A key challenge is the decentralization of formation control, where each agent behaves independently using onboard sensors and computation, improving the scaleability and robustness of the system.This paper proposes a decentralized controller based on model predictive control (MPC), for the control of formations of quadrotor UAVs defined by inter-agent bearings. The use of MPC allows the controller to account for attitude kinematics, improving upon the results of existing bearing formation control methods based on rigidity and visual servoing approaches, which typically only consider the quadrotor as a single or double integrator. Furthermore the near-optimality of MPC permits a more optimal use of the quadrotors dynamic capabilities for faster maneuvering. Extensive simulations are performed to demonstrate the improved transient formation convergence and fast maneuvering permitted by this controller. Experiments show that it is indeed a real-time feasible solution for bearing formation control.

Aerial manipulators have great potential in accomplishing a variety of aerial tasks. One class of aerial manipulators, multi-UAV parallel robots, consists of multiple UAVs connected to a payload or an end-effector by passive kinematic chains. The primary limitation of such aerial manipulators is the dependence on motion capture (MOCAP) systems that provide precise and high-rate exteroceptive pose measurements of all bodies in a common inertial frame, but which are impractical in the majority of real applications.This paper proposes a novel methodology of controlling multi-UAV parallel robots, using a Flying Parallel Robot (FPR) as a case study, that could be deployed without a system of external localisation. Intrinsic measurements acquired onboard the UAVs are used to recover a set of robot states that avoid using coordinates derived from a global frame and allow control of the robot by teleoperation. Two decentralized control methods are proposed, based on inter-UAV communicating or non-communicating scenarios. Experiments with intrinsic measurements emulated by MOCAP are carried out to show the performance of the proposed method.

This paper investigates the effect of the robot configuration on the performance of an aerial cable towed system (ACTS) composed of three quadrotors manipulating a point mass payload. The kinematic and dynamic models of the ACTS are derived in a minimal set of geometric coordinates, and a centralized feedback linearization controller is developed. Independent to the payload trajectory, the configuration of the ACTS is controlled and is evaluated using a robustness index named the capacity margin. Experiments are performed with optimal, suboptimal, and wrench infeasible configurations. It is shown that configurations near the point of zero capacity margin allow the ACTS to hover but not to follow dynamic trajectories, and that the ACTS cannot fly with a negative capacity margin. Dynamic tests of the ACTS show the effects of the configuration on the achievable accelerations.

The presence of Type 2 singularities in parallel robots severely affects their performances, mainly because the platform motion control is partially lost. It also leads to a size reduction of the operational workspace. Moreover, the dynamic model of the parallel mechanism degenerates and locally, the robot becomes underactuated in the singularity. It has been proven that it is possible to cross Type 2 singularities by respecting a dynamic criterion. Nevertheless, the controllers designed up to now require a pre-planned optimized trajectory including this criterion, and as a result, this strategy can only be used by qualified users. In order to avoid this drawback and to cross these types of singularities even if the trajectory is not pre-planned, this paper proposes a controller based on virtual constraints. Furthermore, the controller is integrated in a multi-control architecture in order to switch between a classical computed torque control far from the singularity and the virtual-constraint-based control law near to the singularity locus. Experimental results on a five-bar mechanism validated the automatic Type 2 singularity crossing.

Robots in industries are often used for repetitive tasks. Their motions rely on precise virtual model of their environment and they are not able to handle changes or unexpected events. This disqualifies them to perform tasks that would require precision in a non controlled environment such as an assembly task in real world. Visual servoing is a well known tool to control the robot using spatial sensors. It includes real world references at control law level. But, visual servoing and more generally sensor-based control schemes provide kinematic control law and do not consider robot dynamics. As consequences, tracking performances are poor and convergence behavior is hardly predictable. In this paper, we proposed a new control scheme considering second order sensor-based control law and robot dynamics. Our main goal is to enable full trajectory tracking in sensor-space. Additionally, the scheme is compatible with priority-ordered task sequencing and it can be also used within a hybrid control scheme where force control is considered. This new control scheme brings the possibility to make easier the robot task definition, dividing a complex positioning task into small easy-manageable ones. Multi-tasks operation has been validated in simulation by using MSC Adams software [1] and where the robot has to perform an engraving task on a surface.

This paper proposes, through a survey of models of several UAV-structures, a generic nonlinear model for reduced scale aerial robotic vehicles (6 DOF). Dynamics of an aircraft and some VTOL UAV (quadricopter, ducted fan and classical helicopter) are illustrated. This generic model focuses only on the key physical efforts acting on the dynamics in order to be sufficiently simple to design a controller. The small body forces expression which can introduce a zero dynamics is then discussed.

A vision based control design to stabilise a ducted fan UAV equipped with a camera is presented. The proposed algorithm is motivated by recent work in image-based visual servoing control for under-actuated dynamic systems. In this paper, we show that the placement of the camera significantly affects the zero-dynamics of an under-actuated rigid body in a closed-loop image based visual servo control loop. We show that the zero-dynamics due to mechanical coupling of actuator forces can be cancelled in closed-loop by correct placement of the camera. This leads to improved robustness and performance of image based visual servo control design for small flying robots. The results are simulated on a model of ducted fan UAV to demonstrate the potential advantages

An image-based visual servo control design is proposed for a four rotor vertical take-off and landing (VTOL) craft, known as an X4-flyer, accomplishing a trajectory tracking task. The approach taken is an image-based visual servo design that is applicable to under-actuated dynamic systems. The work is an extension of the authors earlier work (2000) to the trajectory tracking problem. Semiglobal stability of the closed loop system is proved for bounded trajectories.

A control design to stabilise a reduced scale autonomous helicopter equipped with a camera is presented. The proposed algorithm is motivated by recent work in image-based visual servoing control for under-actuated dynamic systems. This work is extended by considering models that contain weakly nonminimum phase zero dynamics. This is an important class of systems since an offset between the camera and the centre of mass for a typical 'dynamic' autonomous vehicle will result in zero dynamics occurring in the image dynamics. In this paper we propose a simplified model of dynamics of the helicopter and show that by placing some constraints in the choice of the position of the camera we can minimise the effect of the zero dynamics.