This paper summarizes new aerial robotic manipulation technologies and methods, required for outdoor industrial inspection and maintenance, developed in the AEROARMS project. It presents aerial robotic manipulators with dual arms and multi-directional thrusters. It deals with the control systems, including the control of the interaction forces and the compliance, the teleoperation, which uses passivity to tackle the tradeoff between stability and performance, perception methods for localization, mapping and inspection, and planning methods, including a new control-aware approach for aerial manipulation. Finally, it describes a novel industrial platform with multidirectional thrusters and a new arm design to increase the robustness in industrial contact inspections. The lessons learned in the application to outdoor aerial manipulation for inspection and maintenance are pointed out.

In this paper a novel hierarchical motion control scheme for quadrotor aerial vehicles equipped with a manipulator is proposed. The controller is organized into two layers: in the top layer, an inverse kinematics algorithm computes the motion references for the actuated variables; in the bottom layer, a motion control algorithm is in charge of tracking the motion references computed by the top layer. A simulation case study is developed to demonstrate the effectiveness of the approach in the presence of disturbances and unmodeled dynamics.

In this paper, we present a distributed fault {detection} and isolation (FDI) strategy for a team of networked robots that builds on a distributed controller-observer schema. Remarkably different from other works in literature, the proposed FDI approach makes each robot of the team able to detect and isolate faults occurring on other robots, even if they are not direct neighbors. By means of a local observer, each robot can estimate the overall state of the team and it can use such an estimate to compute its local control input to achieve global tasks. The same information used by the local observers is also used to compute residual vectors, whose aim is to allow the detection and the isolation of actuator faults occurring on any robot of the team. Adaptive thresholds are derived based on the dynamics of the residual vectors by considering the presence of nonzero initial observer estimation errors, and noise terms affecting state measurement and model dynamics. The approach is validated via both numerical simulations and experiments involving four Khepera III mobile robots

In this paper a behavioral control framework is developed to control an unmanned aerial vehicle-manipulator (UAVM) system, composed by a multirotor aerial vehicle equipped with a robotic arm. The goal is to ensure vehicle-arm coordination and manage complex multi-task missions, where different behaviors must be encompassed in a clear and meaningful way. In detail, a control scheme, based on the null space-based behavioral paradigm, is proposed to handle the coordination between the arm and vehicle motion. To this aim, a set of basic functionalities (elementary behaviors) are designed and combined in a given priority order, in order to attain more complex tasks (compound behaviors). A supervisor is in charge of switching between the compound behaviors according to the mission needs and the sensory feedback. The method is validated on a real testbed, consisting of a multirotor aircraft with an attached 6 Degree of Freedoms manipulator, developed within the EU-funded project ARCAS (Aerial Robotics Cooperative Assembly System). At the the best of authors’ knowledge, this is the first time that an UAVM system is experimentally tested in the execution of complex multi-task missions. The results show that, by properly designing a set of compound behaviors and a supervisor, vehicle-arm coordination in complex missions can be effectively managed