Autonomous Ground Vehicle Solutions for Industry 4.0

This dissertation presents the research and development of innovative solutions for industrial Autonomous Ground Vehicles (AGVs), with a focus on a case study involving Techmo Car S.p.A.'s prototype for a primary aluminum production plant. The project begins by modeling the vehicle and robotic arm, accounting for both hydraulic and electric actuation systems through kinematic and dynamic models. At first this work will focus on robotic manipulators due to their essential role in automating repetitive tasks in industrial settings. In the aluminum industry, for example, manipulators mounted on vehicles, traditionally controlled by human operators, feed potcells with fluoride to enhance metal production. To minimize human exposure to hazardous environments, this work proposes an automated solution using non-singular terminal sliding mode control, compared against classical sliding mode control. The proposed method proves efficient, robust, and capable of handling non-measurable mass variations in the manipulator's links, as demonstrated through multibody simulations. Moreover, this research transforms a conventional human-operated vehicle into a fully autonomous system tailored to the aluminum industry's needs. By integrating advanced sensors, control algorithms, and communication systems, the study addresses challenges of autonomy, safety, and efficiency in hazardous industrial environments. Detailed analyses of system requirements, hardware, software, and performance evaluations are presented, offering insights into improving safety and productivity through automation. Lastly, this work explores the integration of electric vehicles (EVs) and AGVs in industrial settings. While EVs provide environmental benefits, challenges like high costs and limited range persist. Similarly, AGVs enhance material handling but face issues with technology integration and reliability. This study develops a fleet management tool for coordinating electric AGVs, with simulations assessing their performance in aluminum plants. The findings contribute to the advancement of sustainable and efficient industrial transportation solutions.