Bio-inspired Design and Non-linear Model Predictive Control of a Self-aligning Gait Rehabilitation Robot PDF Download

Author: Yinan Jin
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
The field of robot-assisted rehabilitation has seen significant development in recent years. With the development of compliant robots that can be safely used in proximity to people, the use of robots to assist rehabilitation has increased rapidly. The need for gait rehabilitation robots arises from the increasing number of people who are affected by conditions that impair their ability to walk. These conditions can include neurological disorders such as strokes, spinal cord injuries, and traumatic brain injuries. In traditional gait rehabilitation, patients receive manual therapy from a team of physical therapists. While manual therapy can be effective, it can also be time-consuming and resource-intensive, and therapists may not be able to provide consistent and precise support to patients. Gait rehabilitation robots, on the other hand, provide a consistent and precise form of therapy that may help patients make faster and more significant progress. Gait rehabilitation robots can also help reduce the physical demands on therapists and improve the efficiency of therapy sessions. This can allow more patients to receive therapy, which can improve access to care and reduce the burden on health care systems. However, most of existing robotic orthoses have not applied appropriate self-aligning mechanism, gravity-balancing mechanism, or compliant actuators. These limitations should be considered in this proposed research. This thesis proposes a novel intrinsically compliant gait rehabilitation robot with multiple actuated degrees-of-freedom (DOFs). The robot design is flexible and can be personalised with the use of telescopic pelvis, thigh, and shank sections. This newly designed rehabilitation robotic orthosis has multiple actuated and passive DOFs. Because of the importance of alignment between the designed rehabilitation robot joints and human anatomical joints, the robot design has a self-aligning mechanism. A novel gear-couple mechanism, toothed cam-couple mechanism and four-bar linkage mechanism are designed and applied to the hip, knee, and ankle joints to align the robot joints with anatomical joints during gait rehabilitation. Simulation-based and motion capture system-based tests are applied to those three mechanisms to evaluate and choose the most effective self-aligning mechanism. The gear-couple mechanism is finally chosen to be applied to the prototype design. A partial gravity-balancing mechanism is also applied to the designed rehabilitation robot. Gravity-balancing can help overcome the inertia of the rehabilitation robot and can further help reduce joint misalignment. The compliance in the robot is intrinsic due to the use of pneumatic muscle actuators (PMAs). The PMAs have been carefully selected to provide the required torques at the hip, knee and ankle joints during gait rehabilitation. Mechanical amplification of the actuation from the PMAs has been achieved by using gear-couples to replace the usual revolute robot joints. However, with the increase in flexibility of the designed prototype and application of PMAs, which are nonlinear actuators, it is challenging to design the robot control system. This challenge was overcome by developing a system dynamic identification model based on the Koopman operator for the design of a nonlinear model predictive controller (NMPC). The new robot design, together with its self-aligning and gravity-balancing mechanisms, is discussed in detail in this thesis. Compliant actuation and its amplification are explained and various algorithms that are designed and implemented on the robot system as robot firmware are explained. A NMPC is designed and developed to control the rehabilitation robot. The experimental setup and evaluation of the robot design, together with the nonlinear model predictive controller, was carried out with healthy users and yielded the intended results. The robotic orthosis along with the NMPC could successfully guide the healthy human subject along the pre-defined trajectory.

Author: Maziar Ahmad Sharbafi
Publisher: Butterworth-Heinemann
ISBN: 0128037741
Category : Technology & Engineering
Languages : en
Pages : 698

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Book Description
Bioinspired Legged Locomotion: Models, Concepts, Control and Applications explores the universe of legged robots, bringing in perspectives from engineering, biology, motion science, and medicine to provide a comprehensive overview of the field. With comprehensive coverage, each chapter brings outlines, and an abstract, introduction, new developments, and a summary. Beginning with bio-inspired locomotion concepts, the book's editors present a thorough review of current literature that is followed by a more detailed view of bouncing, swinging, and balancing, the three fundamental sub functions of locomotion. This part is closed with a presentation of conceptual models for locomotion. Next, the book explores bio-inspired body design, discussing the concepts of motion control, stability, efficiency, and robustness. The morphology of legged robots follows this discussion, including biped and quadruped designs. Finally, a section on high-level control and applications discusses neuromuscular models, closing the book with examples of applications and discussions of performance, efficiency, and robustness. At the end, the editors share their perspective on the future directions of each area, presenting state-of-the-art knowledge on the subject using a structured and consistent approach that will help researchers in both academia and industry formulate a better understanding of bioinspired legged robotic locomotion and quickly apply the concepts in research or products. Presents state-of-the-art control approaches with biological relevance Provides a thorough understanding of the principles of organization of biological locomotion Teaches the organization of complex systems based on low-dimensional motion concepts/control Acts as a guideline reference for future robots/assistive devices with legged architecture Includes a selective bibliography on the most relevant published articles

Author: Jun Ueda
Publisher: Academic Press
ISBN: 0128031522
Category : Technology & Engineering
Languages : en
Pages : 360

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Book Description
Human Modelling for Bio-inspired Robotics: Mechanical Engineering in Assistive Technologies presents the most cutting-edge research outcomes in the area of mechanical and control aspects of human functions for macro-scale (human size) applications. Intended to provide researchers both in academia and industry with key content on which to base their developments, this book is organized and written by senior experts in their fields. Human Modeling for Bio-Inspired Robotics: Mechanical Engineering in Assistive Technologies offers a system-level investigation into human mechanisms that inspire the development of assistive technologies and humanoid robotics, including topics in modelling of anatomical, musculoskeletal, neural and cognitive systems, as well as motor skills, adaptation and integration. Each chapter is written by a subject expert and discusses its background, research challenges, key outcomes, application, and future trends. This book will be especially useful for academic and industry researchers in this exciting field, as well as graduate-level students to bring them up to speed with the latest technology in mechanical design and control aspects of the area. Previous knowledge of the fundamentals of kinematics, dynamics, control, and signal processing is assumed. Presents the most recent research outcomes in the area of mechanical and control aspects of human functions for macro-scale (human size) applications Covers background information and fundamental concepts of human modelling Includes modelling of anatomical, musculoskeletal, neural and cognitive systems, as well as motor skills, adaptation, integration, and safety issues Assumes previous knowledge of the fundamentals of kinematics, dynamics, control, and signal processing

Author: Prashant Kumar Jamwal
Publisher:
ISBN:
Category : Ankle
Languages : en
Pages : 200

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Book Description
While rehabilitation robots are not uncommon in the literature, they are undesirably inspired by industrial robot designs. Some of the shortcomings which are common to all these contemporary robots are, kinematic incompatibility, stiff actuation, non-backdrivability, high cost, unfriendly or intimidating appearance due to use of heavy and bulky electromagnetic actuators. Wearable robots, owing to their biologically inspired design, compliant actuation, backdrivability and safe use, are better candidates for rehabilitation robots compared to industrial robots. In recent years, wearable robots have received considerable attention and several instances such as exoskeletons, orthotics, and prosthetics have been proposed by researchers. However, there are certain challenges from the design and control perspective of wearable robots, which limit their wider implementation. Bio-inspired or biological design, kinematic compliance and holistic design optimization are the chief design issues, whereas, suitable actuation, development of appropriate physical and cognitive human-robot interaction are the essential control related concerns. Most of the skeletal joints in the human body are actuated by parallel action of a group of muscles and hence a bio-inspired wearable robot design is likely to be based on parallel mechanisms. Impending research issues associated with the use of parallel mechanism are small workspace, abundance of singularities and unavailability of forward kinematics solution. Ambulatory requirement of the wearable robots also calls for compact, light weight, and energy proficient technologies for actuators, sensors, and controllers. This thesis explores the wide-ranging potential of wearable robots in rehabilitation in the pretext of a wearable ankle rehabilitation robot. In this research, a parallel mechanism based wearable robot for ankle rehabilitation was developed to study design and control related aspects of wearable robots in general. Arrangement of actuators, in the kinematically compliant design, had been carefully selected to allow natural foot-ankle motions while keeping the ankle joint position stationary. A fuzzy based computational model was developed in this research to provide a unique solution for the forward kinematics of parallel robots. The proposed method is accurate and time efficient compared to previous methods proposed in the literature. The fast computation of forward kinematics has facilitated its online use in the controller replacing use of heavy inclinometers. A complete design analysis had been carried out by mathematically formulating important performance indices affecting robot performance in three major aspects such as, kinematic, actuation and structural aspects. Initially, a single objective optimisation approach was adopted following past practice, wherein a performance index called global condition number was optimized. Analysis of the results shows that some of the objectives were of conflicting nature and hence the single objective approach could not optimize all the performance criteria simultaneously. Subsequently, robot design optimization was carried out using existing multiobjective optimization methods, namely, preference based optimization and the evolutionary algorithm (EA) based optimization. Interestingly, these existing optimization methods were also found to be unsuccessful due to the incompatible and contradictory nature of objectives, their large number and continuous solution space. Further investigation in the EA methodology revealed fundamental shortcomings in the existing NSGA II approach. As a result of subsequent research efforts, a major breakthrough was achieved through the development of a fuzzy dominance based evolutionary optimization method to address the inadequacies of existing EA approach. Finally, the robot design optimization was carried out using newly developed fuzzy sorting genetic algorithm (FSGA) and the wearable robot was constructed using the optimized design. To improve the compliance of the wearable robot, light weight yet powerful actuators called Pneumatic muscle actuators (PMA) were used which exhibit skeletal muscle like behaviour. Construction of a dynamic model of the PMA was a difficult task owing to their non-linear and time dependent behaviour. Therefore, a Mamdani based fuzzy model was developed and optimized to accurately predict the PMA behaviour in the presence of an external force. The forward kinematics model of the robot and the dynamic model of PMA were finally incorporated in an overall fuzzy controller designed for the position control of the wearable robot. Apart from the conceptualization of a wearable ankle robot design, optimization of two variants of fuzzy inference systems namely, Takagi-Sugeno fuzzy system and Mamdani fuzzy system as well as their distinctive uses in this thesis are important contributions of the present research. The major contribution of this research lies in the development of a fuzzy dominance based evolutionary optimization method which is a strong alternate to the predominantly used evolutionary algorithm NSGA II, which has been used in diverse optimization applications over the last two decades.

Author: Borna Ghannadi
Publisher:
ISBN:
Category : Human-robot interaction
Languages : en
Pages : 221

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Book Description
Stroke rehabilitation technologies have focused on reducing treatment cost while improving effectiveness. Rehabilitation robots are generally developed for home and clinical usage to: 1) deliver repetitive and stimulating practice to post-stroke patients, 2) minimize therapist interventions, and 3) increase the number of patients per therapist, thereby decreasing the associated cost. The control of rehabilitation robots is often limited to black- or gray-box approaches; thus, safety issues regarding the human-robot interaction are not easily considered. Furthermore, despite numerous studies of control strategies for rehabilitation, there are very few rehabilitation robots in which the tasks are implemented using optimal control theory. Optimal controllers using physics-based models have the potential to overcome these issues. This thesis presents advanced impedance- and model-based controllers for an end-effector-based upper extremity stroke rehabilitation robot. The final goal is to implement a biomechanically-plausible real-time nonlinear model predictive control for the studied rehabilitation system. The real-time term indicates that the controller computations finish within the sampling frequency time. This control structure, along with advanced impedance-based controllers, can be applied to any human-environment interactions. This makes them promising tools for different types of assistive devices, exoskeletons, active prostheses and orthoses, and exercise equipment. In this thesis, a high-fidelity biomechatronic model of the human-robot interaction is developed. The rehabilitation robot is a 2 degree-of-freedom parallelogram linkage with joint friction and backlash, and nonlinear dynamics. The mechatronic model of the robot with relatively accurate identified dynamic parameters is used in the human-robot interaction plant. Different musculoskeletal upper extremity, biomechanic, models are used to model human body motions while interacting with the rehabilitation robot model. Human-robot interaction models are recruited for model-in-loop simulations, thereby tuning the developed controllers in a structured resolution. The interaction models are optimized for real-time simulations. Thus, they are also used within the model-based control structures to provide biofeedback during a rehabilitation therapy. In robotic rehabilitation, because of physical interaction of the patient with a mechanical device, safety is a fundamental element in the design of a controller. Thus, impedance-based assistance is commonly used for robotic rehabilitation. One of our objectives is to achieve a reliable and real-time implementable controller. In our definition, a reliable controller is capable of handling variable exercises and admittance interactions. The controller should reduce therapist intervention and improve the quality of the rehabilitation. Hence, we develop advanced impedance-based assistance controllers for the rehabilitation robot. Overall, two types of impedance-based (i.e., hybrid force-impedance and optimal impedance) controllers are developed and tuned using model-in-loop simulations. Their performances are assessed using simulations and/or experiments. Furthermore, their drawbacks are discussed and possible methods for their improvements are proposed. In contrast to black/gray-box controllers, a physics-based model can leverage the inherent dynamics of the system and facilitate implementation of special control techniques, which can optimize a specific performance criterion while meeting stringent system constraints. Thus, we present model-based controllers for the upper extremity rehabilitation robot using our developed musculoskeletal models. Two types of model-based controllers (i.e., nonlinear model predictive control using external 3-dimensional musculoskeletal model or internal 2-dimensional musculoskeletal model) are proposed. Their performances are evaluated in simulations and/or experiments. The biomechanically-plausible nonlinear model predictive control using internal 2-dimensional musculoskeletal model predicts muscular activities of the human subject and provides optimal assistance in real-time experiments, thereby conforming to our final goal for this project.

Author: Bojan Jakimovski
Publisher: Springer Science & Business Media
ISBN: 3642225055
Category : Technology & Engineering
Languages : en
Pages : 203

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Book Description
The increasing presence of mobile robots in our everyday lives introduces the requirements for their intelligent and autonomous features. Therefore the next generation of mobile robots should be more self-capable, in respect to: increasing of their functionality in unforeseen situations, decreasing of the human involvement in their everyday operations and their maintenance; being robust; fault tolerant and reliable in their operation. Although mobile robotic systems have been a topic of research for decades and aside the technology improvements nowadays, the subject on how to program and making them more autonomous in their operations is still an open field for research. Applying bio-inspired, organic approaches in robotics domain is one of the methodologies that are considered that would help on making the robots more autonomous and self-capable, i.e. having properties such as: self-reconfiguration, self-adaptation, self-optimization, etc. In this book several novel biologically inspired approaches for walking robots (multi-legged and humanoid) domain are introduced and elaborated. They are related to self-organized and self-stabilized robot walking, anomaly detection within robot systems using self-adaptation, and mitigating the faulty robot conditions by self-reconfiguration of a multi-legged walking robot. The approaches presented have been practically evaluated in various test scenarios, the results from the experiments are discussed in details and their practical usefulness is validated.

Author: Gia Hoang Phan
Publisher: Springer Nature
ISBN: 9811695512
Category : Technology & Engineering
Languages : en
Pages : 97

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Book Description
This book presents a multi-disciplinary view of all aspects of rehabilitation robotics and non-invasive surgery, ideal for anyone new to the field. It includes perspectives from both engineers and clinicians. For skilled researchers and clinicians, it also summarizes current robot technologies and their application to various pathologies. The book will help the readers to develop the know-how and expertise necessary to guide those seeking a comprehensive understanding of this topic through their use of several commercial devices for robotic rehabilitation. The book targets the implementation of efficient robot strategies to facilitate the re-acquisition of motor skills. This technology incorporates the outcomes of behavioral studies on motor learning and its neural correlates into the design, implementation, and validation of robot agents that behave as optimal trainers, efficiently exploiting the structure and plasticity of the human sensorimotor systems.

Author: Yunhui Liu
Publisher: CRC Press
ISBN: 1439854882
Category : Medical
Languages : en
Pages : 343

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Book Description
Robotic engineering inspired by biology—biomimetics—has many potential applications: robot snakes can be used for rescue operations in disasters, snake-like endoscopes can be used in medical diagnosis, and artificial muscles can replace damaged muscles to recover the motor functions of human limbs. Conversely, the application of robotics technology to our understanding of biological systems and behaviors—biorobotic modeling and analysis—provides unique research opportunities: robotic manipulation technology with optical tweezers can be used to study the cell mechanics of human red blood cells, a surface electromyography sensing system can help us identify the relation between muscle forces and hand movements, and mathematical models of brain circuitry may help us understand how the cerebellum achieves movement control. Biologically Inspired Robotics contains cutting-edge material—considerably expanded and with additional analysis—from the 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO). These 16 chapters cover both biomimetics and biorobotic modeling/analysis, taking readers through an exploration of biologically inspired robot design and control, micro/nano bio-robotic systems, biological measurement and actuation, and applications of robotics technology to biological problems. Contributors examine a wide range of topics, including: A method for controlling the motion of a robotic snake The design of a bionic fitness cycle inspired by the jaguar The use of autonomous robotic fish to detect pollution A noninvasive brain-activity scanning method using a hybrid sensor A rehabilitation system for recovering motor function in human hands after injury Human-like robotic eye and head movements in human–machine interactions A state-of-the-art resource for graduate students and researchers in the fields of control engineering, robotics, and biomedical engineering, this text helps readers understand the technology and principles in this emerging field.

Author: Ye Ma
Publisher:
ISBN:
Category : Gait disorders
Languages : en
Pages : 192

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Book Description
Rehabilitation robots are widely used to assist patients with neurological disorders in performing exercise tasks. Compared with physiotherapists, gait rehabilitation robots seldom tire, are able to accomplish gait retraining precisely, and provide quantitative feedback to show the movement patterns of the patients. However, the effectiveness of robot treatment methods is still under debate. Current gait rehabilitation robots are limited in the following two aspects. Firstly, they do not have the knowledge to account for patient variability. Secondly, they do not take into account the patient's intention and engagement in the training. Therefore, this study investigated the use of biomechanical methodologies, including gait analysis technique, three-dimensional musculoskeletal modelling and simulation technique and muscle force estimation methodologies to enhance the effectiveness of gait rehabilitation robots. This study aims to develop neuromusculoskeletal models, which include the patient-specific musculoskeletal properties and model the patients' effort in muscle level. Two new models are developed in this research: the patient-specific muscle force estimation model (PMFE) and the patient-specific electromyography (EMG)-driven neuromuscular model (PENm). The PMFE and the PENm predict joint moment and muscle forces through kinematic information and EMG signals, respectively. The PMFE improves traditional inverse dynamic-static optimization model by realizing real-time calculation and ensuring good model prediction accuracy. Besides employing patient-specific musculoskeletal model for accurately modelling, the PMFE employs an analytical algorithm, the Lagrange multiplier method, in the static optimization procedure for real-time calculation. The musculoskeletal model is also simplified to one extensor and one flexor muscle around hip and knee joint for realtime calculation. The PMFE is evaluated by comparing the joint moments and individual muscle forces calculated via the PMFE and the computed muscle control method for healthy adolescents. Results show that the PMFE calculated joint moments and individual muscle forces accurately. As a case study of the PMFE, a patient-specific biological command based controller (PSBc) is developed based on the PMFE to control a human-inspired exoskeleton. The simulation and real-world experiment results show that the exoskeleton is controlled by the proposed PSBc with good accuracy. The second model, the PENm makes the following improvements for predicting individual muscle forces accurately in real-time. Firstly, the PENm incorporates EMG signals from two muscles around knee joint and using minimum musculotendon parameters in the model optimization process. Secondly, a dynamic computational model is developed based on Zajac's computation flowchart to ensure the PENm predict muscle force in real-time. Thirdly, the PENm is based on a simplified patient-specific musculoskeletal model, which provides accurate patient-specific musculotendon parameters and muscle kinematics parameters. Fourthly, a combined force-length-velocity relationship is implemented to generate accurate muscle forces. The PENm is evaluated by comparing the joint moment and muscle forces via the PENm and the inverse dynamics and EMG activations for both healthy and cerebral palsy adolescents. Results show that the PENm can predict accurate joint moment in real-time. The PENm also provide more in-depth information on muscle functions. In summary, the design of gait rehabilitation robotic control strategies and clinical gait assessment can benefit from applications of the proposed biomechanical models. This research has collaborated with Department of Exercise Science and Shanghai Sunshine Hospital. The thesis has been published in two peer-reviewed SCI journals and presented at three international conferences.

Author: Carlos A. Cifuentes
Publisher: Springer
ISBN: 3319340638
Category : Technology & Engineering
Languages : en
Pages : 125

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Book Description
This book presents the development of a new multimodal human-robot interface for testing and validating control strategies applied to robotic walkers for assisting human mobility and gait rehabilitation. The aim is to achieve a closer interaction between the robotic device and the individual, empowering the rehabilitation potential of such devices in clinical applications. A new multimodal human-robot interface for testing and validating control strategies applied to robotic walkers for assisting human mobility and gait rehabilitation is presented. Trends and opportunities for future advances in the field of assistive locomotion via the development of hybrid solutions based on the combination of smart walkers and biomechatronic exoskeletons are also discussed.