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.