EPAM: Eversive Pneumatic Artificial Muscle

Pneumatic Artificial Muscles, which are lightweight actuators with inherently compliant behavior, are broadly recognized as safe actuators for devices that assist or interact with humans. This paper presents the design and implementation of a soft pneumatic muscle based on the eversion principle - Eversive Pneumatic Artificial Muscle (EPAM). The proposed pneumatic muscle exerts a pulling force when elongating based on the eversion (growing) principle. It is capable of extending its length by a minimum of 100% when fully inflated. In contrast to other soft pneumatic actuators, such as the McKibben’s muscle, which contract when pressurized, our EPAM extends when pressure is increased. Additionally, important advantages of employing the eversion principle are the capability to achieve high pulling forces and an efficient force to pressure ratio. In a pivoting joint/link mechanism configuration the proposed muscle provides motion comparable to human arm flexion and extension. In this work, we present the design of the proposed EPAM, study its behavior, and evaluate its displacement capability and generated forces in an agonistic and antagonistic joint/link arrangement. The developed EPAM prototype with a diameter of 25 mm and a length of 250 mm shows promising results, capable of exerting 10 N force when pressurized up to 62 KPa

An Overview of Legged Robots

The objective of this paper is to present the evolution and the state-of-theart in the area of legged locomotion systems. In a first phase different possibilities for mobile robots are discussed, namely the case of artificial legged locomotion systems, while emphasizing their advantages and limitations. In a second phase an historical overview of the evolution of these systems is presented, bearing in mind several particular cases often considered as milestones on the technological and scientific progress. After this historical timeline, some of the present day systems are examined and their performance is analyzed. In a third phase are pointed out the major areas for research and development that are presently being followed in the construction of legged robots. Finally, some of the problems still unsolved, that remain defying robotics research, are also addressed.N/

Design and Fabrication of Soft 3D Printed Actuators: Expanding Soft Robotics Applications

Soft pneumatic actuators are ideal for soft robotic applications due to their innate compliance and high power-weight ratios. Presently, the majority of soft pneumatic actuators are used to create bending motions, with very few able to produce significant linear movements. Fewer can actively produce strains in multiple directions. The further development of these actuators is limited by their fabrication methods, specifically the lack of suitable stretchable materials for 3D printing. In this thesis, a new highly elastic resin for digital light projection 3D printers, designated ElastAMBER, is developed and evaluated, which shows improvements over previously synthesised elastic resins. It is prepared from a di-functional polyether urethane acrylate oligomer and a blend of two different diluent monomers. ElastAMBER exhibits a viscosity of 1000 mPa.s at 40 °C, allowing easy printing at near room temperatures. The 3D-printed components present an elastomeric behaviour with a maximum extension ratio of 4.02 ± 0.06, an ultimate tensile strength of (1.23 ± 0.09) MPa, low hysteresis, and negligible viscoelastic relaxation

High Fidelity Dynamic Modeling and Nonlinear Control of Fluidic Artificial Muscles

A fluidic artificial muscle is a type of soft actuator. Soft actuators transmit power with elastic or hyper-elastic bladders that are deformed with a pressurized fluid. In a fluidic artificial muscle a rubber tube is encompassed by a helical fiber braid with caps on both ends. One of the end caps has an orifice, allowing the control of fluid flow in and out of the device. As the actuator is pressurized, the rubber tube expands radially and is constrained by the helical fiber braid. This constraint results in a contractile motion similar to that of biological muscles. Although artificial muscles have been extensively studied, physics-based models do not exist that predict theirmotion.This dissertation presents a new comprehensive lumped-parameter dynamic model for both pneumatic and hydraulic artificial muscles. It includes a tube stiffness model derived from the theory of large deformations, thin wall pressure vessel theory, and a classical artificial muscle force model. Furthermore, it incorporates models for the kinetic friction and braid deformation. The new comprehensive dynamic model is able to accurately predict the displacement of artificial muscles as a function of pressure. On average, the model can predict the quasi-static position of the artificial muscles within 5% error and the dynamic displacement within 10% error with respect to the maximum stroke. Results show the potential utility of the model in mechanical system design and control design. Applications include wearable robots, mobile robots, and systems requiring compact, powerful actuation.The new model was used to derive sliding mode position and impedance control laws. The accuracy of the controllers ranged from ± 6 µm to ± 50 µm, with respect to a 32 mm and 24 mm stroke artificial muscles, respectively. Tracking errors were reduced by 59% or more when using the high-fidelity model sliding mode controller compared to classical methods. The newmodel redefines the state-of-the-art in controller performance for fluidic artificial muscles

Bio-Inspired Soft Artificial Muscles for Robotic and Healthcare Applications

Soft robotics and soft artificial muscles have emerged as prolific research areas and have gained substantial traction over the last two decades. There is a large paradigm shift of research interests in soft artificial muscles for robotic and medical applications due to their soft, flexible and compliant characteristics compared to rigid actuators. Soft artificial muscles provide safe human-machine interaction, thus promoting their implementation in medical fields such as wearable assistive devices, haptic devices, soft surgical instruments and cardiac compression devices. Depending on the structure and material composition, soft artificial muscles can be controlled with various excitation sources, including electricity, magnetic fields, temperature and pressure. Pressure-driven artificial muscles are among the most popular soft actuators due to their fast response, high exertion force and energy efficiency. Although significant progress has been made, challenges remain for a new type of artificial muscle that is easy to manufacture, flexible, multifunctional and has a high length-to-diameter ratio. Inspired by human muscles, this thesis proposes a soft, scalable, flexible, multifunctional, responsive, and high aspect ratio hydraulic filament artificial muscle (HFAM) for robotic and medical applications. The HFAM consists of a silicone tube inserted inside a coil spring, which expands longitudinally when receiving positive hydraulic pressure. This simple fabrication method enables low-cost and mass production of a wide range of product sizes and materials. This thesis investigates the characteristics of the proposed HFAM and two implementations, as a wearable soft robotic glove to aid in grasping objects, and as a smart surgical suture for perforation closure. Multiple HFAMs are also combined by twisting and braiding techniques to enhance their performance. In addition, smart textiles are created from HFAMs using traditional knitting and weaving techniques for shape-programmable structures, shape-morphing soft robots and smart compression devices for massage therapy. Finally, a proof-of-concept robotic cardiac compression device is developed by arranging HFAMs in a special configuration to assist in heart failure treatment. Overall this fundamental work contributes to the development of soft artificial muscle technologies and paves the way for future comprehensive studies to develop HFAMs for specific medical and robotic requirements

Design and Evaluation of AIRGAIT Exoskeleton\u27s Leg Orthosis: Development of a Control Scheme and Strategy for a Noble Control of Antagonistic Mono- and Bi-Articular Actuators

芝浦工業大学201

Elbow exoskeleton mechanism for multistage poststroke rehabilitation.

More than three million people are suffering from stroke in England. The process of post-stroke rehabilitation consists of a series of biomechanical exercises- controlled joint movement in acute phase; external assistance in the mid phase; and variable levels of resistance in the last phase. Post-stroke rehabilitation performed by physiotherapist has many limitations including cost, time, repeatability and intensity of exercises. Although a large variety of arm exoskeletons have been developed in the last two decades to substitute the conventional exercises provided by physiotherapist, most of these systems have limitations with structural configuration, sensory data acquisition and control architecture. It is still difficult to facilitate multistage post-stroke rehabilitation to patients sited around hospital bed without expert intervention. To support this, a framework for elbow exoskeleton has been developed that is portable and has the potential to offer all three types of exercises (external force, assistive and resistive) in a single structure. The design enhances torque to weight ratio compared to joint based actuation systems. The structural lengths of the exoskeleton are determined based on the mean anthropometric parameters of healthy users and the lengths of upperarm and forearm are determined to fit a wide range of users. The operation of the exoskeleton is divided into three regions where each type of exercise can be served in a specific way depending on the requirements of users. Electric motor provides power in the first region of operation whereas spring based assistive force is used in the second region and spring based resistive force is applied in the third region. This design concept provides an engineering solution of integrating three phases of post-stroke exercises in a single device. With this strategy, the energy source is only used in the first region to power the motor whereas the other two modes of exercise can work on the stored energy of springs. All these operations are controlled by a single motor and the maximum torque of the motor required is only 5 Nm. However, due to mechanical advantage, the exoskeleton can provide the joint torque up to 10 Nm. To remove the dependency on biosensor, the exoskeleton has been designed with a hardware-based mechanism that can provide assistive and resistive force. All exoskeleton components are integrated into a microcontroller-based circuit for measuring three joint parameters (angle, velocity and torque) and for controlling exercises. A user-friendly, multi-purpose graphical interface has been developed for participants to control the mode of exercise and it can be managed manually or in automatic mode. To validate the conceptual design, a prototype of the exoskeleton has been developed and it has been tested with healthy subjects. The generated assistive torque can be varied up to 0.037 Nm whereas resistive torque can be varied up to 0.057 Nm. The mass of the exoskeleton is approximately 1.8 kg. Two comparative studies have been performed to assess the measurement accuracy of the exoskeleton. In the first study, data collected from two healthy participants after using the exoskeleton and Kinect sensor by keeping Kinect sensor as reference. The mean measurement errors in joint angle are within 5.18 % for participant 1 and 1.66% for participant 2; the errors in torque measurement are within 8.48% and 7.93% respectively. In the next study, the repeatability of joint measurement by exoskeleton is analysed. The exoskeleton has been used by three healthy users in two rotation cycles. It shows a strong correction (correlation coefficient: 0.99) between two consecutive joint angle measurements and standard deviation is calculated to determine the error margin which comes under acceptable range (maximum: 8.897). The research embodied in this thesis presents a design framework of a portable exoskeleton model for providing three modes of exercises, which could provide a potential solution for all stages of post- stroke rehabilitation

MUSME 2011 4 th International Symposium on Multibody Systems and Mechatronics

El libro de actas recoge las aportaciones de los autores a través de los correspondientes artículos a la Dinámica de Sistemas Multicuerpo y la Mecatrónica (Musme). Estas disciplinas se han convertido en una importante herramienta para diseñar máquinas, analizar prototipos virtuales y realizar análisis CAD sobre complejos sistemas mecánicos articulados multicuerpo. La dinámica de sistemas multicuerpo comprende un gran número de aspectos que incluyen la mecánica, dinámica estructural, matemáticas aplicadas, métodos de control, ciencia de los ordenadores y mecatrónica. Los artículos recogidos en el libro de actas están relacionados con alguno de los siguientes tópicos del congreso: Análisis y síntesis de mecanismos ; Diseño de algoritmos para sistemas mecatrónicos ; Procedimientos de simulación y resultados ; Prototipos y rendimiento ; Robots y micromáquinas ; Validaciones experimentales ; Teoría de simulación mecatrónica ; Sistemas mecatrónicos ; Control de sistemas mecatrónicosUniversitat Politècnica de València (2011). MUSME 2011 4 th International Symposium on Multibody Systems and Mechatronics. Editorial Universitat Politècnica de València. http://hdl.handle.net/10251/13224Archivo delegad

Advances of Italian Machine Design

This 2028 Special Issue presents recent developments and achievements in the field of Mechanism and Machine Science coming from the Italian community with international collaborations and ranging from theoretical contributions to experimental and practical applications. It contains selected contributions that were accepted for presentation at the Second International Conference of IFToMM Italy, IFIT2018, that has been held in Cassino on 29 and 30 November 2018. This IFIT conference is the second event of a series that was established in 2016 by IFToMM Italy in Vicenza. IFIT was established to bring together researchers, industry professionals and students, from the Italian and the international community in an intimate, collegial and stimulating environment

Nonlinear Modeling and Control of Driving Interfaces and Continuum Robots for System Performance Gains

With the rise of (semi)autonomous vehicles and continuum robotics technology and applications, there has been an increasing interest in controller and haptic interface designs. The presence of nonlinearities in the vehicle dynamics is the main challenge in the selection of control algorithms for real-time regulation and tracking of (semi)autonomous vehicles. Moreover, control of continuum structures with infinite dimensions proves to be difficult due to their complex dynamics plus the soft and flexible nature of the manipulator body. The trajectory tracking and control of automobile and robotic systems requires control algorithms that can effectively deal with the nonlinearities of the system without the need for approximation, modeling uncertainties, and input disturbances. Control strategies based on a linearized model are often inadequate in meeting precise performance requirements. To cope with these challenges, one must consider nonlinear techniques. Nonlinear control systems provide tools and methodologies for enabling the design and realization of (semi)autonomous vehicle and continuum robots with extended specifications based on the operational mission profiles. This dissertation provides an insight into various nonlinear controllers developed for (semi)autonomous vehicles and continuum robots as a guideline for future applications in the automobile and soft robotics field. A comprehensive assessment of the approaches and control strategies, as well as insight into the future areas of research in this field, are presented.First, two vehicle haptic interfaces, including a robotic grip and a joystick, both of which are accompanied by nonlinear sliding mode control, have been developed and studied on a steer-by-wire platform integrated with a virtual reality driving environment. An operator-in-the-loop evaluation that included 30 human test subjects was used to investigate these haptic steering interfaces over a prescribed series of driving maneuvers through real time data logging and post-test questionnaires. A conventional steering wheel with a robust sliding mode controller was used for all the driving events for comparison. Test subjects operated these interfaces for a given track comprised of a double lane-change maneuver and a country road driving event. Subjective and objective results demonstrate that the driver’s experience can be enhanced up to 75.3% with a robotic steering input when compared to the traditional steering wheel during extreme maneuvers such as high-speed driving and sharp turn (e.g., hairpin turn) passing. Second, a cellphone-inspired portable human-machine-interface (HMI) that incorporated the directional control of the vehicle as well as the brake and throttle functionality into a single holistic device will be presented. A nonlinear adaptive control technique and an optimal control approach based on driver intent were also proposed to accompany the mechatronic system for combined longitudinal and lateral vehicle guidance. Assisting the disabled drivers by excluding extensive arm and leg movements ergonomically, the device has been tested in a driving simulator platform. Human test subjects evaluated the mechatronic system with various control configurations through obstacle avoidance and city road driving test, and a conventional set of steering wheel and pedals were also utilized for comparison. Subjective and objective results from the tests demonstrate that the mobile driving interface with the proposed control scheme can enhance the driver’s performance by up to 55.8% when compared to the traditional driving system during aggressive maneuvers. The system’s superior performance during certain vehicle maneuvers and approval received from the participants demonstrated its potential as an alternative driving adaptation for disabled drivers. Third, a novel strategy is designed for trajectory control of a multi-section continuum robot in three-dimensional space to achieve accurate orientation, curvature, and section length tracking. The formulation connects the continuum manipulator dynamic behavior to a virtual discrete-jointed robot whose degrees of freedom are directly mapped to those of a continuum robot section under the hypothesis of constant curvature. Based on this connection, a computed torque control architecture is developed for the virtual robot, for which inverse kinematics and dynamic equations are constructed and exploited, with appropriate transformations developed for implementation on the continuum robot. The control algorithm is validated in a realistic simulation and implemented on a six degree-of-freedom two-section OctArm continuum manipulator. Both simulation and experimental results show that the proposed method could manage simultaneous extension/contraction, bending, and torsion actions on multi-section continuum robots with decent tracking performance (e.g. steady state arc length and curvature tracking error of 3.3mm and 130mm-1, respectively). Last, semi-autonomous vehicles equipped with assistive control systems may experience degraded lateral behaviors when aggressive driver steering commands compete with high levels of autonomy. This challenge can be mitigated with effective operator intent recognition, which can configure automated systems in context-specific situations where the driver intends to perform a steering maneuver. In this article, an ensemble learning-based driver intent recognition strategy has been developed. A nonlinear model predictive control algorithm has been designed and implemented to generate haptic feedback for lateral vehicle guidance, assisting the drivers in accomplishing their intended action. To validate the framework, operator-in-the-loop testing with 30 human subjects was conducted on a steer-by-wire platform with a virtual reality driving environment. The roadway scenarios included lane change, obstacle avoidance, intersection turns, and highway exit. The automated system with learning-based driver intent recognition was compared to both the automated system with a finite state machine-based driver intent estimator and the automated system without any driver intent prediction for all driving events. Test results demonstrate that semi-autonomous vehicle performance can be enhanced by up to 74.1% with a learning-based intent predictor. The proposed holistic framework that integrates human intelligence, machine learning algorithms, and vehicle control can help solve the driver-system conflict problem leading to safer vehicle operations