The fusion of different technologies is the base of the fourth industrial revolution. Companies are encouraged to integrate new tools in their production processes in order to improve working conditions and increase productivity and production quality. The integration between information, communication technologies and industrial automation can create highly flexible production models for products and services that can be customized through real-time interactions between consumer, production and machinery throughout the production process. The future of production, therefore, depends on increasingly intelligent machinery through the use of digital systems. The key elements for future integrated devices are intelligent systems and machines, based on human–machine interaction and information sharing. To do so, the implementation of shared languages that allow different systems to dialogue in a simple way is necessary. In this perspective, the use of advanced prototyping tools like Open-Source programming systems, the development of more detailed multibody models through the use of CAD software and the use of self-learning techniques will allow for developing a new class of machines capable of revolutionizing our companies. The purpose of this paper is to present a waypoint navigation activity of a custom Wheeled Mobile Robot (WMR) in an available simulated 3D indoor environment by using the Gazebo simulator. Gazebo was developed in 2002 at the University of Southern California. The idea was to create a high-fidelity simulator that gave the possibility to simulate robots in outdoor environments under various conditions. In particular, we wanted to test the high-performance physics Open Dynamics Engine (ODE) and the sensors feature present in Gazebo for prototype development activities. This choice was made for the possibility of emulating not only the system under analysis, but also the world in which the robot will operate. Furthermore, the integration tools available with Solidworks and Matlab-Simulink, well known commercial platforms of modelling and robotics control respectively, are also explored.

Artificial intelligence is the ability of a computer to perform the functions and reasoning typical of the human mind. In its purely informatic aspect, it includes the theory and techniques for the development of algorithms that allow machines to show an intelligent ability and/or perform an intelligent activity, at least in specific areas. In particular, there are automatic learning algorithms based on the same mechanisms that are thought to be the basis of all the cognitive processes developed by the human brain. Such a powerful tool has already started to produce a new class of self-driving vehicles. With the projections of population growth that will increase until the year 2100 up to 11.2 billion, research on innovating agricultural techniques must be continued. In order to improve the efficiency regarding precision agriculture, the use of autonomous agricultural machines must become an important issue. For this reason, it was decided to test the use of the “Neural Network Toolbox” tool already present in MATLAB to design an artificial neural network with supervised learning suitable for classification and pattern recognition by using data collected by an ultrasonic sensor. The idea is to use such a protocol to retrofit kits for agricultural machines already present on the market.

In this paper, we analyze the behavior of a single pad system in the presence of dry friction. The goal is to investigate the path that leads a stable mechanical system to unstable behavior. In doing so, we studied the behavior of a discrete three DOF model, a continuous model and a finite element model of the pad. The numerical results are consistent with the experimental investigation conducted on a brake disk for railway application.

This paper deals with the development of an open-loop controller implemented in the Arduino platform in order to reuse an existing CNC machine for performing simple manufacturing operations. The CNC machine considered in this study is an Objet Quadra Tempo 3D printer. The goal of this work is, therefore, to convert the machine, considered obsolete due to high maintenance costs, by using low-cost off-the-shelf components and by using open source software in order to reduce the amount of electronic and industrial wastes by means of simple retrofitting operations. To control the drivers of the stepper motors of the machine, an ArduinoMega 2560 microcontroller was used. The Arduino micro-controller allows for controlling analog and digital devices in a straightforward manner. All retrofitting operations were conducted in order to carry out additive manufacturing and subtractive manufacturing operations. For the activity reported in this paper, an electro-spindle for machining products in wood and polycarbonate was installed. The use of low-cost components allowed the transformation of the 3D printer into a CNC milling machine capable of working materials such as wood and polycarbonate.

The purpose of this analysis is to evaluate the effectiveness of different modeling techniques for a COMAU six-axis robot arm. The robot manipulator represents one of the most used robots in the mechanical industry. For robots, with a high number of degrees of freedom, to obtain a kinematic model, Denavit-Hartemberg parameters allow representing geometric transformations in the Euclidean space through the minimum number of parameters. Furthermore, the use of detailed multibody models and the use of sophisticated tools like the Robotics Toolbox System, allow performing, in a very efficient way, inverse kinematic analysis and trajectory planning to control the robot move from one configuration to another.

The agricultural sector is constantly evolving. The rise in the world’s population generates an increasingly growing demand for food, resulting in the need for the agroindustry to meet this demand. Tractors are the vehicles that have made a real difference in agriculture’s development throughout history, lowering costs in soil tillage and facilitating activities and operations for workers. This study aims to successfully design and build an autonomous, electric agricultural tractor that can autonomously perform recurring tasks in open-field and greenhouse applications. This project is fully part of the new industrial and agronomic revolution, known as Factory 4.0 and Agriculture 4.0. The predetermined functional requirements for the vehicle are its lightweight, accessible price, the easy availability of its spare parts, and its simple, ordinary maintenance. In this first study, the preliminary phases of sizing and conceptual design of the rover are reported before subsequently proceeding to the dynamical analysis. To optimize the design of the various versions of the automated vehicle, it is decided that a standard chassis would be built based on a robot operating inside a greenhouse on soft and flat terrains. The SimScape multi-body environment is used to model the kinematics of the non-back-drivable screw jack mechanism for the hitch-lifting arms. The control unit for the force exerted is designed and analyzed by means of an inverse dynamics simulation to evaluate the force and electric power consumed by the actuators. The results obtained from the analysis are essential for the final design of the autonomous electric tractor.