There is a strong demand in the oil and gas industry to develop alternatives to manual inspection. This paper presents AeroX, a novel aerial robotic manipulator that provides physical contact inspection with unprecedented capabilities. AeroX has a semi-autonomous operation, which provides interesting advantages in contact inspection. In the free-flight mode, the pilot guides the robot until performing contact with its end-effector on the surface to be inspected. During contact, AeroX is in its fully-autonomous global navigation satellite system (GNSS)-free contact–flight mode, in which the robot keeps its relative position w.r.t. the surface contact point using only its internal sensors. During autonomous flight, the inspector can move—with uninterrupted contact—the end-effector on the surface for accurately selecting the points where to perform A-scan measurements or continuous B-scan or C-scan inspections. AeroX adopts an eight-tilted rotor configuration and a simple and efficient design, which provides high stability, maneuverability, and robustness to rotor failure. It can perform contact inspection on surfaces at any orientation, including vertical, inclined, horizontal-top or horizontal-bottom, and its operation can be easily integrated into current maintenance operations in many industries. It has been extensively validated in outdoor experiments including a refinery and has been awarded the EU Innovation Radar Prize 2017.

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.

The inspection of public infrastructure, such as viaducts and bridges, is crucial for their proper maintenance given the heavy use of many of them. Current inspection techniques are very costly and manual, requiring highly qualified personnel and involving many risks. This article presents a novel solution for the detailed inspection of viaducts using aerial robotic platforms. The system provides a highly automated visual inspection platform that does not rely on GPS and could even fly underneath the infrastructure. Unlike commercially available solutions, our system automatically references the inspection to a global coordinate system usable throughout the lifespan of the infrastructure. In addition, the system includes another aerial platform with a robotic arm to make contact inspections of detected defects, thus providing information that cannot be obtained only with images. Both aerial robotic platforms feature flexibility in the choice of camera or contact measurement sensors as the situation requires. The system was validated by performing inspection flights on real viaducts.

Coaxial multirotors, characterized by overlapping rotors, represent a common solution to increasing payload capacity while maintaining a compact platform size. However, the overlap between motors generates airflow disturbances that, if not taken into account properly, may decrease the system’s overall performance. In this paper, aerodynamic interactions for coaxial multirotors are analyzed and characterized. Two rotor models are introduced, which account for the aerodynamic interaction between the upper and the lower rotor. Each model is accompanied by its corresponding mixer design and analyzed with respect to the state-of-the-art mixer solution for classical multirotor systems. The proposed approaches are tested through rotor stand experiments, simulations, and implementation on an actual coaxial platform. The results demonstrate the effectiveness of these models in mitigating the adverse aerodynamic effects, thereby improving the performance and efficiency of coaxial multirotor systems.

This work describes the methodology for detecting pipes and their pose in refineries inspection using Unmanned Aerial Vehicles (UAV s) for remote Ultrasonic Testing (UT). Segmentation techniques such as the Hough Transform and its variations, and Random Sample Consensus have been widely used. This paper is therefore focused on the development of an efficient computer vision algorithm to detect the position and orientation of the pipes in order to land on them autonomously to perform the inspection, by using 3D point cloud information from depth cameras. Applying a methodology based on Random Sample Consensus and point cloud pre-processing to fasten the algorithm performance has led to robust estimations of the pipes and their poses in an indoor testbed using a realistic environment, allowing the autonomous landing and the subsequent inspection.