Identificazione, controllo e sfruttamento delle vibrazioni meccaniche nei robot

Mechanical vibrations occur in various systems due to dynamic interactions between components, structural flexibility, and external forces. These vibrations can negatively affect performance, leading to reduced precision, increased wear, and unwanted noise. In precision machinery and high-speed applications, controlling vibrations is essential to maintaining accuracy and extending the lifespan of the system. Understanding the sources of vibrations, such as material stiffness and compliance, enables the development of strategies to minimize their impact. In some cases, vibrations can be harnessed as a useful resource, such as in energy harvesting applications, where they are converted into electrical energy for powering small devices. This dissertation presents novel approaches to the identification, control, and exploitation of mechanical vibrations in robotic systems, focusing on industrial and underactuated robots, as well as energy harvesting applications. First, the modal approach is extended to identify the stiffness of key joints and the compliance of the first link in an industrial robot, enhancing the robot’s dynamic model by incorporating an additional degree of freedom. Mozzi’s axis is used to identify the compliance axis of the first link, enriching the accuracy of the mechanical model. In the second part, the control of mechanical vibrations is addressed through the design of a dynamically balanced 5-DOF serial robot, optimized for variable payloads and high-speed motion. Additionally, the dynamic modeling and control of underactuated differentially flat robots are investigated, focusing on minimizing unwanted oscillations due to the neglect of damping of the passive joint during the motion using open-loop control techniques. The dissertation also explores trajectory planning in underactuated robots by considering system dynamics and analyzing the impact of joint stiffness, motion duration, and compliance. A major contribution is the extension of differential flatness theory to spatial robots, with mass distribution requirements identified and validated through experimental testing on a custom-built prototype. The third part of the research explores the exploitation of mechanical vibrations through energy harvesting in robotics. A novel frequency-domain identification method for piezoelectric materials is proposed, allowing for efficient characterization of piezoelectric harvesters. The relationship between trajectory-induced vibrations and energy conversion efficiency is examined, offering potential applications in powering small sensors. Finally, a hybrid energy harvester is developed to collect energy from both road-induced and wind-induced vibrations, particularly for use in light vehicles such as rovers. The harvester design incorporates a modified tip mass to enhance performance under varying excitation conditions, demonstrating the feasibility of vibration-based energy harvesting in mobile systems.