155 research outputs found

    Natural Motion for Energy Saving in Robotic and Mechatronic Systems

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    Energy saving in robotic and mechatronic systems is becoming an evermore important topic in both industry and academia. One strategy to reduce the energy consumption, especially for cyclic tasks, is exploiting natural motion. We define natural motion as the system response caused by the conversion of potential elastic energy into kinetic energy. This motion can be both a forced response assisted by a motor or a free response. The application of the natural motion concepts allows for energy saving in tasks characterized by repetitive or cyclic motion. This review paper proposes a classification of several approaches to natural motion, starting from the compliant elements and the actuators needed for its implementation. Then several approaches to natural motion are discussed based on the trajectory followed by the system, providing useful information to the researchers dealing with natural motion

    Optimal Control for Articulated Soft Robots

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    Soft robots can execute tasks with safer interactions. However, control techniques that can effectively exploit the systems' capabilities are still missing. Differential dynamic programming (DDP) has emerged as a promising tool for achieving highly dynamic tasks. But most of the literature deals with applying DDP to articulated soft robots by using numerical differentiation, in addition to using pure feed-forward control to perform explosive tasks. Further, underactuated compliant robots are known to be difficult to control and the use of DDP-based algorithms to control them is not yet addressed. We propose an efficient DDP-based algorithm for trajectory optimization of articulated soft robots that can optimize the state trajectory, input torques, and stiffness profile. We provide an efficient method to compute the forward dynamics and the analytical derivatives of series elastic actuators (SEA)/variable stiffness actuators (VSA) and underactuated compliant robots. We present a state-feedback controller that uses locally optimal feedback policies obtained from DDP. We show through simulations and experiments that the use of feedback is crucial in improving the performance and stabilization properties of various tasks. We also show that the proposed method can be used to plan and control underactuated compliant robots, with varying degrees of underactuation effectively.Comment: 14 pages, 15 figures, IEEE Transaction on Robotics (TRO

    Study and Development of Mechatronic Devices and Machine Learning Schemes for Industrial Applications

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    Obiettivo del presente progetto di dottorato è lo studio e sviluppo di sistemi meccatronici e di modelli machine learning per macchine operatrici e celle robotizzate al fine di incrementarne le prestazioni operative e gestionali. Le pressanti esigenze del mercato hanno imposto lavorazioni con livelli di accuratezza sempre più elevati, tempi di risposta e di produzione ridotti e a costi contenuti. In questo contesto nasce il progetto di dottorato, focalizzato su applicazioni di lavorazioni meccaniche (e.g. fresatura), che includono sistemi complessi quali, ad esempio, macchine a 5 assi e, tipicamente, robot industriali, il cui utilizzo varia a seconda dell’impiego. Oltre alle specifiche problematiche delle lavorazioni, si deve anche considerare l’interazione macchina-robot per permettere un’efficiente capacità e gestione dell’intero impianto. La complessità di questo scenario può evidenziare sia specifiche problematiche inerenti alle lavorazioni (e.g. vibrazioni) sia inefficienze più generali che riguardano l’impianto produttivo (e.g. asservimento delle macchine con robot, consumo energetico). Vista la vastità della tematica, il progetto si è suddiviso in due parti, lo studio e sviluppo di due specifici dispositivi meccatronici, basati sull’impiego di attuatori piezoelettrici, che puntano principalmente alla compensazione di vibrazioni indotte dal processo di lavorazione, e l’integrazione di robot per l’asservimento di macchine utensili in celle robotizzate, impiegando modelli di machine learning per definire le traiettorie ed i punti di raggiungibilità del robot, al fine di migliorarne l’accuratezza del posizionamento del pezzo in diverse condizioni. In conclusione, la presente tesi vuole proporre soluzioni meccatroniche e di machine learning per incrementare le prestazioni di macchine e sistemi robotizzati convenzionali. I sistemi studiati possono essere integrati in celle robotizzate, focalizzandosi sia su problematiche specifiche delle lavorazioni in macchine operatrici sia su problematiche a livello di impianto robot-macchina. Le ricerche hanno riguardato un’approfondita valutazione dello stato dell’arte, la definizione dei modelli teorici, la progettazione funzionale e l’identificazione delle criticità del design dei prototipi, la realizzazione delle simulazioni e delle prove sperimentali e l’analisi dei risultati.The aim of this Ph.D. project is the study and development of mechatronic systems and machine learning models for machine tools and robotic applications to improve their performances. The industrial demands have imposed an ever-increasing accuracy and efficiency requirement whilst constraining the cost. In this context, this project focuses on machining processes (e.g. milling) that include complex systems such as 5-axes machine tool and industrial robots, employed for various applications. Beside the issues related to the machining process itself, the interaction between the machining centre and the robot must be considered for the complete industrial plant’s improvement. This scenario´s complexity depicts both specific machining problematics (e.g. vibrations) and more general issues related to the complete plant, such as machine tending with an industrial robot and energy consumption. Regarding the immensity of this area, this project is divided in two parts, the study and development of two mechatronic devices, based on piezoelectric stack actuators, for the active vibration control during the machining process, and the robot machine tending within the robotic cell, employing machine learning schemes for the trajectory definition and robot reachability to improve the corresponding positioning accuracy. In conclusion, this thesis aims to provide a set of solutions, based on mechatronic devices and machine learning schemes, to improve the conventional machining centre and the robotic systems performances. The studied systems can be integrated within a robotic cell, focusing on issues related to the specific machining process and to the interaction between robot-machining centre. This research required a thorough study of the state-of-the-art, the formulation of theoretical models, the functional design development, the identification of the critical aspects in the prototype designs, the simulation and experimental campaigns, and the analysis of the obtained results

    Proceedings of the ECCOMAS Thematic Conference on Multibody Dynamics 2015

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    This volume contains the full papers accepted for presentation at the ECCOMAS Thematic Conference on Multibody Dynamics 2015 held in the Barcelona School of Industrial Engineering, Universitat Politècnica de Catalunya, on June 29 - July 2, 2015. The ECCOMAS Thematic Conference on Multibody Dynamics is an international meeting held once every two years in a European country. Continuing the very successful series of past conferences that have been organized in Lisbon (2003), Madrid (2005), Milan (2007), Warsaw (2009), Brussels (2011) and Zagreb (2013); this edition will once again serve as a meeting point for the international researchers, scientists and experts from academia, research laboratories and industry working in the area of multibody dynamics. Applications are related to many fields of contemporary engineering, such as vehicle and railway systems, aeronautical and space vehicles, robotic manipulators, mechatronic and autonomous systems, smart structures, biomechanical systems and nanotechnologies. The topics of the conference include, but are not restricted to: ● Formulations and Numerical Methods ● Efficient Methods and Real-Time Applications ● Flexible Multibody Dynamics ● Contact Dynamics and Constraints ● Multiphysics and Coupled Problems ● Control and Optimization ● Software Development and Computer Technology ● Aerospace and Maritime Applications ● Biomechanics ● Railroad Vehicle Dynamics ● Road Vehicle Dynamics ● Robotics ● Benchmark ProblemsPostprint (published version

    Applied Mathematics to Mechanisms and Machines

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    This book brings together all 16 articles published in the Special Issue "Applied Mathematics to Mechanisms and Machines" of the MDPI Mathematics journal, in the section “Engineering Mathematics”. The subject matter covered by these works is varied, but they all have mechanisms as the object of study and mathematics as the basis of the methodology used. In fact, the synthesis, design and optimization of mechanisms, robotics, automotives, maintenance 4.0, machine vibrations, control, biomechanics and medical devices are among the topics covered in this book. This volume may be of interest to all who work in the field of mechanism and machine science and we hope that it will contribute to the development of both mechanical engineering and applied mathematics

    12th International Conference on Vibrations in Rotating Machinery

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    Since 1976, the Vibrations in Rotating Machinery conferences have successfully brought industry and academia together to advance state-of-the-art research in dynamics of rotating machinery. 12th International Conference on Vibrations in Rotating Machinery contains contributions presented at the 12th edition of the conference, from industrial and academic experts from different countries. The book discusses the challenges in rotor-dynamics, rub, whirl, instability and more. The topics addressed include: - Active, smart vibration control - Rotor balancing, dynamics, and smart rotors - Bearings and seals - Noise vibration and harshness - Active and passive damping - Applications: wind turbines, steam turbines, gas turbines, compressors - Joints and couplings - Challenging performance boundaries of rotating machines - High power density machines - Electrical machines for aerospace - Management of extreme events - Active machines - Electric supercharging - Blades and bladed assemblies (forced response, flutter, mistuning) - Fault detection and condition monitoring - Rub, whirl and instability - Torsional vibration Providing the latest research and useful guidance, 12th International Conference on Vibrations in Rotating Machinery aims at those from industry or academia that are involved in transport, power, process, medical engineering, manufacturing or construction

    Modeling and Control of Piezoactive Micro and Nano Systems

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    Piezoelectrically-driven (piezoactive) systems such as nanopositioning platforms, scanning probe microscopes, and nanomechanical cantilever probes are advantageous devices enabling molecular-level imaging, manipulation, and characterization in disciplines ranging from materials science to physics and biology. Such emerging applications require precise modeling, control and manipulation of objects, components and subsystems ranging in sizes from few nanometers to micrometers. This dissertation presents a comprehensive modeling and control framework for piezoactive micro and nano systems utilized in various applications. The development of a precise memory-based hysteresis model for feedforward tracking as well as a Lyapunov-based robust-adaptive controller for feedback tracking control of nanopositioning stages are presented first. Although hysteresis is the most degrading factor in feedforward control, it can be effectively compensated through a robust feedback control design. Moreover, an adaptive controller can enhance the performance of closed-loop system that suffers from parametric uncertainties at high-frequency operations. Comparisons with the widely-used PID controller demonstrate the effectiveness of the proposed controller in tracking of high-frequency trajectories. The proposed controller is then implemented in a laser-free Atomic Force Microscopy (AFM) setup for high-speed and low-cost imaging of surfaces with micrometer and nanometer scale variations. It is demonstrated that the developed AFM is able to produce high-quality images at scanning frequencies up to 30 Hz, where a PID controller is unable to present acceptable results. To improve the control performance of piezoactive nanopositioning stages in tracking of time-varying trajectories with frequent stepped discontinuities, which is a common problem in SPM systems, a supervisory switching controller is designed and integrated with the proposed robust adaptive controller. The controller switches between two control modes, one mode tuned for stepped trajectory tracking and the other one tuned for continuous trajectory tracking. Switching conditions and compatibility conditions of the control inputs in switching instances are derived and analyzed. Experimental implementation of the proposed switching controller indicates significant improvements of control performance in tracking of time-varying discontinuous trajectories for which single-mode controllers yield undesirable results. Distributed-parameters modeling and control of rod-type solid-state actuators are then studied to enable accurate tracking control of piezoactive positioning systems in a wide frequency range including several resonant frequencies of system. Using the extended Hamilton\u27s principle, system partial differential equation of motion and its boundary conditions are derived. Standard vibration analysis techniques are utilized to formulate the truncated finite-mode state-space representation of the system. A new state-space controller is then proposed for asymptotic output tracking control of system. Integration of an optimal state-observer and a Lyapunov-based robust controller are presented and discussed to improve the practicability of the proposed framework. Simulation results demonstrate that distributed-parameters modeling and control is inevitable if ultra-high bandwidth tracking is desired. The last part of the dissertation, discusses new developments in modeling and system identification of piezoelectrically-driven Active Probes as advantageous nanomechanical cantilevers in various applications including tapping mode AFM and biomass sensors. Due to the discontinuous cross-section of Active Probes, a general framework is developed and presented for multiple-mode vibration analysis of system. Application in the precise pico-gram scale mass detection is then presented using frequency-shift method. This approach can benefit the characterization of DNA solutions or other biological species for medical applications
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