A ROS-based software architecture for a versatile collaborative dual-armed autonomous mobile robot for the manufacturing industry

The industrial context is changing rapidly due to advancements in technology fueled by the Internet and Information Technology. The fourth industrial revolution counts integration, flexibility, and optimization as its fundamental pillars, and, in this context, Human-Robot Collaboration has become a crucial factor for manufacturing sustainability in Europe. Collaborative robots are appealing to many companies due to their low installation and running costs and high degree of flexibility, making them ideal for reshoring production facilities with a short return on investment. The ROSSINI European project aims to implement a true Human-Robot Collaboration by designing, developing, and demonstrating a modular and scalable platform for integrating human-centred robotic technologies in industrial production environments. The project focuses on safety concerns related to introducing a cobot in a shared working area and aims to lay the groundwork for a new working paradigm at the industrial level. The need for a software architecture suitable to the robotic platform employed in one of three use cases selected to deploy and test the new technology was the main trigger of this Thesis. The chosen application consists of the automatic loading and unloading of raw-material reels to an automatic packaging machine through an Autonomous Mobile Robot composed of an Autonomous Guided Vehicle, two collaborative manipulators, and an eye-on-hand vision system for performing tasks in a partially unstructured environment. The results obtained during the ROSSINI use case development were later used in the SENECA project, which addresses the need for robot-driven automatic cleaning of pharmaceutical bins in a very specific industrial context. The inherent versatility of mobile collaborative robots is evident from their deployment in the two projects with few hardware and software adjustments. The positive impact of Human-Robot Collaboration on diverse production lines is a motivation for future investments in research on this increasingly popular field by the industry.

A multi-instrumental approach to the study of equatorial ionosphere over South America

An extensive study of the morphology and the dynamics of the equatorial ionosphere over South America is presented here. A multi parametric approach is used to describe the physical characteristics of the ionosphere in the regions where the combination of the thermospheric electric field and the horizontal geomagnetic field creates the so-called Equatorial Ionization Anomalies. Ground based measurements from GNSS receivers are used to link the Total Electron Content (TEC), its spatial gradients and the phenomenon known as scintillation that can lead to a GNSS signal degradation or even to a GNSS signal ‘loss of lock’. A new algorithm to highlight the features characterizing the TEC distribution is developed in the framework of this thesis and the results obtained are validated and used to improve the performance of a GNSS positioning technique (long baseline RTK). In addition, the correlation between scintillation and dynamics of the ionospheric irregularities is investigated. By means of a software, here implemented, the velocity of the ionospheric irregularities is evaluated using high sampling rate GNSS measurements. The results highlight the parallel behaviour of the amplitude scintillation index (S4) occurrence and the zonal velocity of the ionospheric irregularities at least during severe scintillations conditions (post-sunset hours). This suggests that scintillations are driven by TEC gradients as well as by the dynamics of the ionospheric plasma. Finally, given the importance of such studies for technological applications (e.g. GNSS high-precision applications), a validation of the NeQuick model (i.e. the model used in the new GALILEO satellites for TEC modelling) is performed. The NeQuick performance dramatically improves when data from HF radar sounding (ionograms) are ingested. A custom designed algorithm, based on the image recognition technique, is developed to properly select the ingested data, leading to further improvement of the NeQuick performance.