Autonomous Scanning and Cleanliness Classification of Pharmaceutical Bins Through Artificial Intelligence and Robotics

In the pharmaceutical industry, bins need to be cleaned up to a critical level because the products that they contain are often incompatible with each other, and their mixture can facilitate the formation of bacterial fauna. In this work, a strategy is presented to fully automatize the procedure of cleanliness quality inspection of a pharmaceutical bin through a robotic arm and the use of both traditional and artificial-intelligence-based computer-vision techniques. An autonomous mobile robot is used to mimic the approach of a manipulator to a bin inserted in a washing cabin with an uncertain position. The manipulator is equipped with an eye-on-hand color camera and it carries out the binary classification of the bin surface status (e.g. clean vs dirty) through a convolutional neural network based on ResNet. The viewpoints from which the images are taken are the result of an optimization that, starting from the digital three-dimensional model of the bin and exploiting a virtual-twin-based planning scene, minimizes their number while maximizing the visible area of the bin from the current location of the robot. The results of this optimization are used to set up a pipeline that is entirely bin-independent. The same procedure may also be employed to generate the best washing trajectories to be performed by the cleaning robot, by simply replacing the inspection camera mounted on the robot end-effector with a washing nozzle. Though a complete tuning session is still required, preliminary experimental results are very promising, reaching a classifier accuracy (namely a capability of distinguishing clean and dirty surfaces) of 98% on conditioned data, showing that this work has the potential of becoming an effective and versatile industrial product

Vision-Based Robotic Grasping of Reels for Automatic Packaging Machines

In this work, we present a vision system particularly suited to the automatic recognition of reels in the field of automatic packaging machines. The output of the vision system is used to guide the autonomous grasping of the reels by a robot for a subsequent manipulation task. The proposed solution is built around three different methods to solve the ellipse-detection problem in an image. Such methods leverage standard image processing and mathematical algorithms, which are tailored to the targeted application. An experimental campaign demonstrates the efficacy of the proposed approach, even in the presence of low computational power and limited hardware resources, as in the use-case at hand

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

Gini’s concentration measure: observations on the calculation formulas and Dalton’s Principle of Population. Proposal of a factor correction

En la primera parte del presente trabajo se investigan diferentes formas de cálculo de la razón de concentración conocida como Coeficiente o Índice de Gini, y el no cumplimiento del axioma conocido como de “invariancia a la replicación” o “Principio de Población de Dalton” en algunas de ellas. El alcance de las conclusiones se limita al comportamiento de las fórmulas sometidas a prueba (se encuentran entre las más conocidas) cuando son aplicadas a distribuciones de datos desagregados. En la segunda parte se propone un factor de corrección para las fórmulas de cálculo analizadas, de manera que satisfagan el Principio de Población.The first section of this paper will examine different calculations of the ratio of concentration known as Gini’s coefficient or index and the non-observance of the axiom known as "replication invariance" or "Dalton population principle" by someone of them. The reach of the conclusions is limited to the behavior of such formulas when applied to distributions of disaggregated data. The second part proposes a correction factor for the Gini coeffcient formulas analysed in order for them to fulfill the Dalton population principle.Instituto de Investigaciones en Humanidades y Ciencias Sociales (IdIHCS

Mobile cobots for autonomous raw-material feeding of automatic packaging machines

Human-robot collaboration has become a key driver for manufacturing sustainability in Europe. Thanks to the many advantages that a fenceless, shared working environment offers, industry has recently grown a particular interest in collaborative robotics, thus sustaining the transition from academy to factories of this technology. In this work, we present a robotic solution integrating a serial manipulator and a mobile platform, both characterized by collaborative features, for feeding raw material to a packaging automatic machine. The goal is to provide an overview of such a complex system from different points of view, including hardware and software architecture, trajectory planning, computer-vision strategies, customized mechanical design, and field validation. We will describe the obtained results and the lessons learned, and provide an outlook for future evolution

Medida de concentración de Gini: observaciones sobre las fórmulas de cálculo y el Principio de Población de Dalton. Propuesta de un factor de corrección

The first section of this paper will examine different calculations of the ratio of concentration known as Gini’s coefficient or index and the non-observance of the axiom known as "replication invariance" or "Dalton population principle" by someone of them. The reach of the conclusions is limited to the behavior of such formulas when applied to distributions of disaggregated data. The second part proposes a correction factor for the Gini coeffcient formulas analysed in order for them to fulfill the Dalton population principleEn la primera parte del presente trabajo se investigan diferentes formas de cálculo de la razón de concentración conocida como Coeficiente o Índice de Gini, y el no cumplimiento del axioma conocido como de “invariancia a la replicación” o “Principio de Población de Dalton” en algunas de ellas. El alcance de las conclusiones se limita al comportamiento de las fórmulas sometidas a prueba (se encuentran entre las más conocidas) cuando son aplicadas a distribuciones de datos desagregados. En la segunda parte se propone un factor de corrección para las fórmulas de cálculo analizadas, de manera que satisfagan el Principio de Població

Medida de concentración de Gini: observaciones sobre las fórmulas de cálculo y el Principio de Población de Dalton. Propuesta de un factor de corrección

The first section of this paper will examine different calculations of the ratio of concentration known as Gini’s coefficient or index and the non-observance of the axiom known as "replication invariance" or "Dalton population principle" by someone of them. The reach of the conclusions is limited to the behavior of such formulas when applied to distributions of disaggregated data. The second part proposes a correction factor for the Gini coeffcient formulas analysed in order for them to fulfill the Dalton population principleEn la primera parte del presente trabajo se investigan diferentes formas de cálculo de la razón de concentración conocida como Coeficiente o Índice de Gini, y el no cumplimiento del axioma conocido como de “invariancia a la replicación” o “Principio de Población de Dalton” en algunas de ellas. El alcance de las conclusiones se limita al comportamiento de las fórmulas sometidas a prueba (se encuentran entre las más conocidas) cuando son aplicadas a distribuciones de datos desagregados. En la segunda parte se propone un factor de corrección para las fórmulas de cálculo analizadas, de manera que satisfagan el Principio de Població

Gini's concentration measure : Observations on the calculation formulas and Dalton's Principle of Population. Proposal of a factor correction

En la primera parte del presente trabajo se investigan diferentes formas de cálculo de la razón de concentración conocida como Coeficiente o Índice de Gini, y el no cumplimiento del axioma conocido como de "invariancia a la replicación" o "Principio de Población de Dalton" en algunas de ellas. El alcance de las conclusiones se limita al comportamiento de las fórmulas sometidas a prueba (se encuentran entre las más conocidas) cuando son aplicadas a distribuciones de datos desagregados. En la segunda parte se propone un factor de corrección para las fórmulas de cálculo analizadas, de manera que satisfagan el Principio de Población.The first section of this paper will examine different calculations of the ratio of concentration known as Gini's coefficient or index and the non-observance of the axiom known as "replication invariance" or "Dalton population principle" by someone of them. The reach of the conclusions is limited to the behavior of such formulas when applied to distributions of disaggregated data. The second part proposes a correction factor for the Gini coeffcient formulas analysed in order for them to fulfill the Dalton population principle

Vision-Based Robotic Grasping of Reels for Automatic Packaging Machines

In this work, we present a vision system particularly suited to the automatic recognition of reels in the field of automatic packaging machines. The output of the vision system is used to guide the autonomous grasping of the reels by a robot for a subsequent manipulation task. The proposed solution is built around three different methods to solve the ellipse-detection problem in an image. Such methods leverage standard image processing and mathematical algorithms, which are tailored to the targeted application. An experimental campaign demonstrates the efficacy of the proposed approach, even in the presence of low computational power and limited hardware resources, as in the use-case at hand