The programmable spring: towards physical emulators of mechanical systems

The way motion is generated and controlled in robotics has traditionally been based on a philosophy of rigidity, where movements are tightly controlled and external influences are ironed out. More recent research into autonomous robots, biological actuation and human machine interaction has uncovered the value of compliant mechanisms in both aiding the production of effective, adaptive and efficient behaviour, and increasing the margins for safety in machines that operate alongside people. Various actuation methods have previously been proposed that allow robotic systems to exploit rather than avoid the influences of external perturbations, but many of these devices can be complex and costly to engineer, and are often task specific. This thesis documents the development of a general purpose modular actuator that can emulate the behaviour of various spring damping systems. It builds on some of the work done to produce reliable force controlled electronic actuators by developing a low cost implementation of an existing force actuator, and combining it with a novel high level control structure running in software on an embedded microcontroller. The actuator hardware with its embedded software results in a compact modular device capable of approximating the behaviour of various mechanical systems and actuation devices. Specifying these behaviours is achieved with an intuitive user interface and a control system based on a concept called profile groups. Profile group configurations that specify complex mechanical behaviours can be rapidly designed and the resulting configurations downloaded for a device to emulate. The novel control system and intuitive user interface developed to facilitate the rapid prototyping of mechanical behaviours are explained in detail. Two prototype devices are demonstrated emulating a number of mechanical systems and the results are compared to mechanical counterparts. Performance issues are discussed and some solutions proposed alongside general improvements to the control system. The applications beyond robotics are also explored

Robot Manipulators

Robot manipulators are developing more in the direction of industrial robots than of human workers. Recently, the applications of robot manipulators are spreading their focus, for example Da Vinci as a medical robot, ASIMO as a humanoid robot and so on. There are many research topics within the field of robot manipulators, e.g. motion planning, cooperation with a human, and fusion with external sensors like vision, haptic and force, etc. Moreover, these include both technical problems in the industry and theoretical problems in the academic fields. This book is a collection of papers presenting the latest research issues from around the world

Control of the interaction of a gantry robot end effector with the environment by the adaptive behaviour of its joint drive actuators

The thesis examines a way in which the performance of the robot electric actuators can be precisely and accurately force controlled where there is a need for maintaining a stable specified contact force with an external environment. It describes the advantages of the proposed research, which eliminates the need for any external sensors and solely depends on the precise torque control of electric motors. The aim of the research is thus the development of a software based control system and then a proposal for possible inclusion of this control philosophy in existing range of automated manufacturing techniques.The primary aim of the research is to introduce force controlled behaviour in the electric actuators when the robot interacts with the environment, by measuring and controlling the contact forces between them. A software control system is developed and implemented on a robot gantry manipulator to follow two dimensional contours without the explicit geometrical knowledge of those contours. The torque signatures from the electric actuators are monitored and maintained within a desired force band. The secondary aim is the optimal design of the software controller structure. Experiments are performed and the mathematical model is validated against conventional Proportional Integral Derivative (PID) control. Fuzzy control is introduced in the software architecture to incorporate a sophisticated control. Investigation is carried out with the combination of PID and Fuzzy logic which depend on the geometrical complexity of the external environment to achieve the expected results

Inteligentno upravljanje paralelnim robotom sa šest stupnjeva slobode korištenim za rehabilitaciju donjih udova

The process of empowering muscles in order to make them to a normal and common value is an expensive and prolonged work, in common available methods. There are some commercial exercise machines used for this purpose called rehabilitation systems. However, due to their insufficient motion freedom and prospect of being expensive, these machines have limited usage. Hence, it is clearly necessary that Mechatronic technologies should be used in this area. In this paper, an algorithm and an improved rule are presented for controlling a rehabilitation system of lower limbs which is implemented on a 6-Degree Of Freedom (DOF) Stewart parallel robot. Impedance control and adaptive control are used for this purpose. Estimation and optimization of control parameters will be done by artificial neural networks and genetic algorithms, respectively (intelligent strategy). Safety is guaranteed since some of controller parameters can be adapted under the stability conditions given by using Routh stability theory. Thereafter, the results of simulations are presented by defining a physiotherapy standard mode on a desired trajectory. MATLAB/SIMULINK is used for simulations. Finally, a comparative discussion between this strategy and common methods is devised.Proces osposobljavanja mišića za normalne funkcije je skup i dugotrajan uz korištenje dostupnih metoda. Postoje komercijalni strojevi za tu svrhu koji se nazivaju sustavi za rehabilitaciju. Zbog njihove nedostatne slobode pokreta i visoke cijene takvi strojevi imaju ograničenu upotrebu. Stoga je jasno da je u području rehabilitiacije potrebno koristiti mehatroničke sustave. U ovom radu prikazan je algoritam i poboljšano pravilo za upravljanje rehabilitacijskog sustava za donje udove koji je implementiran na Stewart paralelnom robotu sa šest stupnjeva slobode. Pritom je korišteno upravljanje impedancijom i adaptivno upravljanje. Za estimaciju i optimiranje parametara upravljanja koriste se neuronske mreže i genetički algoritmi. Sigurnost je garantirana jer se neki parametri regulatora adaptiraju prema uvjetima stabilnosti koji su dobiveni korištenjem Ruthove teorije stabilnosti. Nakon toga, rezultati simulacija prikazani su definiranjem standardnog fizioterapijskog rada na željenoj trajektoriji. Za simulacije se koristi MATLAB/SIMULINK. Konačno, u radu je dana i usporedba predložene strategije s uobičajenim metodama

Compliance adaptation of an intrinsically soft ankle rehabilitation robot driven by pneumatic muscles

Pneumatic muscles (PMs)-driven robots become more and more popular in medical and rehabilitation field as the actuators are intrinsically complaint and thus are safer for patients than traditional rigid robots. This paper proposes a new compliance adaptation method of a soft ankle rehabilitation robot that is driven by four pneumatic muscles enabling three rotational movement degrees of freedom (DoFs). The stiffness of a PM is dominated by the nominal pressure. It is possible to control the robot joint compliance independently of the robot movement in task space. The controller is designed in joint space to regulate the compliance property of the soft robot by tuning the stiffness of each active link. Experiments in actual environment were conducted to verify the control scheme and results show that the robot compliance can be adjusted when provided changing nominal pressures and the robot assistance output can be regulated, which provides a feasible solution to implement the patient-cooperative training strategy

Mechatronics of systems with undetermined configurations

This work is submitted for the award of a PhD by published works. It deals with some of the efforts of the author over the last ten years in the field of Mechatronics. Mechatronics is a new area invented by the Japanese in the late 1970's, it consists of a synthesis of computers and electronics to improve mechanical systems. To control any mechanical event three fundamental features must be brought together: the sensors used to observe the process, the control software, including the control algorithm used and thirdly the actuator that provides the stimulus to achieve the end result. Simulation, which plays such an important part in the Mechatronics process, is used in both in continuous and discrete forms. The author has spent some considerable time developing skills in all these areas. The author was certainly the first at Middlesex to appreciate the new developments in Mechatronics and their significance for manufacturing. The author was one of the first mechanical engineers to recognise the significance of the new transputer chip. This was applied to the LQG optimal control of a cinefilm copying process. A 300% improvement in operating speed was achieved, together with tension control. To make more efficient use of robots they have to be made both faster and cheaper. The author found extremely low natural frequencies of vibration, ranging from 3 to 25 Hz. This limits the speed of response of existing robots. The vibration data was some of the earliest available in this field, certainly in the UK. Several schemes have been devised to control the flexible robot and maintain the required precision. Actuator technology is one area where mechatronic systems have been the subject of intense development. At Middlesex we have improved on the Aexator pneumatic muscle actuator, enabling it to be used with a precision of about 2 mm. New control challenges have been undertaken now in the field of machine tool chatter and the prevention of slip. A variety of novel and traditional control algorithms have been investigated in order to find out the best approach to solve this problem

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

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

A Neural Tool for Ground-Based Telescope Tracking control

Neural Network models (NN) have emerged as important components for applications of adaptive control theories. Their basic generalization capability, based on acquired knowledge, together with execution rapidity and correlation ability between input stimula, are basic attributes to consider NN as an extremely powerful tool for on-line control of complex systems. By a control system point of view, not only accuracy and speed, but also, in some cases, a high level of adaptation capability is required in order to match all working phases of the whole system during its lifetime. This is particularly remarkable for a new generation ground-based telescope control system. Infact, strong changes in terms of system speed and instantaneous position error tolerance are necessary, especially in case of trajectory disturb induced by wind shake. The classical control scheme adopted in such a system is based on the Proportional Integral (PI) filter, already applied and implemented on a large amount of new generation telescopes, considered as a standard in this technological environment. In this paper we introduce the concept of a new approach, the Neural Variable Structure Proportional Integral, (NVSPI), related to the implementation of a standard Multi Layer Perceptron (MLP) network in new generation ground-based Alt-Az telescope control systems. Its main purpose is to improve adaptive capability of the Variable Structure Proportional Integral model, (VSPI), an already innovative control scheme recently introduced by authors [1], based on a modified version of classical PI control model, in terms of flexibility and accuracy of the dynamic response range also in presence of wind noise effects. The realization of a powerful well tested and validated telescope model simulation system allowed the possibility to directly compare performances of the two control schemes on simulated tracking trajectories, revealing extremely encouraging results in terms of NVSPI control robustness and reliability