Proof of concept for robot-aided upper limb rehabilitation using disturbance observers

This paper presents a wearable upper body exoskeleton system with a model-based compensation control framework to support robot-aided shoulder-elbow rehabilitation and power assistance tasks. To eliminate the need for EMG and force sensors, we exploit off-the-shelf compensation techniques developed for robot manipulators. Thus, target rehabilitation tasks are addressed by using only encoder readings. A proof-of-concept evaluation was conducted with live able-bodied participants. The patient-active rehabilitation task was realized via observer-based user torque estimation, in which resistive forces were adjusted using virtual impedance. In the patient-passive rehabilitation task, the proposed controller enabled precise joint tracking with a maximum positioning error of 0.25°. In the power assistance task, the users' muscular activities were reduced up to 85% while exercising with a 5 kg dumbbell. Therefore, the exoskeleton system was regarded as being useful for the target tasks, indicating that it has a potential to promote robot-aided therapy protocols.Ministry of Education, Culture, Sports, Science and Technology, Japanpost-prin

Multimodal series elastic actuator for human-machine interaction with applications in robot-aided rehabilitation

Series elastic actuators (SEAs) are becoming an elemental building block in collaborative robotic systems. They introduce an elastic element between the mechanical drive and the end-effector, making otherwise rigid structures compliant when in contact with humans. Topologically, SEAs are more amenable to accurate force control than classical actuation techniques, as the elastic element may be used to provide a direct force estimate. The compliant nature of SEAs provides the potential to be applied in robot-aided rehabilitation. This thesis proposes the design of a novel SEA to be used in robot-aided musculoskeletal rehabilitation. An active disturbance rejection controller is derived and experimentally validated and multiobjective optimization is executed to tune the controller for best performance in human-machine interaction. This thesis also evaluates the constrained workspaces for individuals experiencing upper-limb musculoskeletal disorders. This evaluation can be used as a tool to determine the kinematic structure of devices centred around the novel SEA

Human-robot interaction torque estimation methods for a lower limb rehabilitation robotic system with uncertainties

Lower limb rehabilitation robot (LLRR) users, to successfully conduct isotonic exercises, require real-time feedback on the torque they exert on the robot to meet the goal of the treatment. Still, direct torque measuring is expensive, and indirect encoder-based estimation strategies, such as inverse dynamics (ID) and Nonlinear Disturbance Observers (NDO), are sensitive to Body Segment Inertial Parameters (BSIPs) uncertainties. We envision a way to minimize such parametric uncertainties. This paper proposes two human–robot interaction torque estimation methods: the Identified ID-based method (IID) and the Identified NDO-based method (INDO). Evaluating in simulation the proposal to apply, in each rehabilitation session, a sequential two-phase method: (1) An initial calibration phase will use an online parameter estimation to reduce sensitivity to BSIPs uncertainties. (2) The torque estimation phase uses the estimated parameters to obtain a better result. We conducted simulations under signal-to-noise ratio (SNR) = 40 dB and 20% BSIPs uncertainties. In addition, we compared the effectiveness with two of the best methods reported in the literature via simulation. Both proposed methods obtained the best Coefficient of Correlation, Mean Absolute Error, and Root Mean Squared Error compared to the benchmarks. Moreover, the IID and INDO fulfilled more than 72.2% and 88.9% of the requirements, respectively. In contrast, both methods reported in the literature only accomplish 27.8% and 33.3% of the requirements when using simulations under noise and BSIPs uncertainties. Therefore, this paper extends two methods reported in the literature and copes with BSIPs uncertainties without using additional sensors

Wrist rehabilitation exoskeleton robot based on pneumatic soft actuators

The aim of this paper is to describe the design of a soft, wearable splint for wrist joint rehabilitation, based on pneumatic soft actuators. The extensor bending and the contraction types of pneumatic soft actuators have been adopted in this study. These actuators are shown to be appropriate by examining their characteristics. The main contributions of this study are developing a safe, lightweight, soft and small actuator for direct human interaction, designing a novel single portable wearable soft robot capable of performing all wrist rehabilitation movements, and using low-cost materials to create the device. Three modes of rehabilitation exercises in the exoskeleton are involved: Flexion/Extension, Radial/Ulnar deviation, and circular movements

A Soft+Rigid Hybrid Exoskeleton Concept in Scissors-Pendulum Mode: A Suit for Human State Sensing and an Exoskeleton for Assistance

In this paper, we present a novel concept that can enable the human aware control of exoskeletons through the integration of a soft suit and a robotic exoskeleton. Unlike the state-of-the-art exoskeleton controllers which mostly rely on lumped human-robot models, the proposed concept makes use of the independent state measurements concerning the human user and the robot. The ability to observe the human state independently is the key factor in this approach. In order to realize such a system from the hardware point of view, we propose a system integration frame that combines a soft suit for human state measurement and a rigid exoskeleton for human assistance. We identify the technological requirements that are necessary for the realization of such a system with a particular emphasis on soft suit integration. We also propose a template model, named scissor pendulum, that may encapsulate the dominant dynamics of the human-robot combined model to synthesize a controller for human state regulation. A series of simulation experiments were conducted to check the controller performance. As a result, satisfactory human state regulation was attained, adequately confirming that the proposed system could potentially improve exoskeleton-aided applications

Disturbance Observer-based Robust Control and Its Applications: 35th Anniversary Overview

Disturbance Observer has been one of the most widely used robust control tools since it was proposed in 1983. This paper introduces the origins of Disturbance Observer and presents a survey of the major results on Disturbance Observer-based robust control in the last thirty-five years. Furthermore, it explains the analysis and synthesis techniques of Disturbance Observer-based robust control for linear and nonlinear systems by using a unified framework. In the last section, this paper presents concluding remarks on Disturbance Observer-based robust control and its engineering applications.Comment: 12 pages, 4 figure

Design and Control of Compliant Actuation Topologies for Energy-Efficient Articulated Robots

Considerable advances have been made in the field of robotic actuation in recent years. At the heart of this has been increased use of compliance. Arguably the most common approach is that of Series-Elastic Actuation (SEA), and SEAs have evolved to become the core component of many articulated robots. Another approach is integration of compliance in parallel to the main actuation, referred to as Parallel- Elastic Actuation (PEA). A wide variety of such systems has been proposed. While both approaches have demonstrated significant potential benefits, a number of key challenges remain with regards to the design and control of such actuators. This thesis addresses some of the challenges that exist in design and control of compliant actuation systems. First, it investigates the design, dynamics, and control of SEAs as the core components of next-generation robots. We consider the influence of selected physical stiffness on torque controllability and backdrivability, and propose an optimality criterion for impedance rendering. Furthermore, we consider disturbance observers for robust torque control. Simulation studies and experimental data validate the analyses. Secondly, this work investigates augmentation of articulated robots with adjustable parallel compliance and multi-articulated actuation for increased energy efficiency. Particularly, design optimisation of parallel compliance topologies with adjustable pretension is proposed, including multi-articulated arrangements. Novel control strategies are developed for such systems. To validate the proposed concepts, novel hardware is designed, simulation studies are performed, and experimental data of two platforms are provided, that show the benefits over state-of-the-art SEA-only based actuatio

Development of Waterloo Robotic Rollator (WATRR)

One of the major risk factors for impaired mobility is aging, and with the aging population on the rise, the demand for assistive technologies for individuals with mobility impairment is at an all time high. Impaired mobility can lead to loss of independence, increased chance of mortality, deterioration of health, decreased cognitive function and a poor quality of life. Moreover, individuals with impaired mobility also tend to have higher hospital utilization costs. Mobility capability can be (re)built through the use of assistive technologies. Rollators/Walkers are a commonly used mobility aid that has shown to help with mobility by providing support, particularly transferring a portion of the lower limb loads to the upper limbs. However, safety has been a concern with rollators, with thousands of accidents occurring every year. Currently, many research projects are investigating methods to improve rollators, particularly surrounding the use of robotic rollators. At University of Waterloo Neural and Rehabilitation lab (NRE lab), our goal is to develop technology to improve lives of people, with development of robotic rollators being one of our research foci. The Waterloo Robotic Rollators (WATRR) is an active rollator system with built-in sensing and actuation systems. It is believed that the user experience and safety of rollators can be improved through the use of smart control algorithms. The purpose of this thesis was to develop methods to address safety and user experience concerns by proposing a hybrid control approach, where distance and orientation control are key control parameters, including automatic braking. First, the Waterloo Robotic Rollator (WATRR), a low weight robotic rollator platform, representative of current rollators with sensors and actuators is presented. I describe key design decisions for the platform, offer an overview of the software architecture, and discuss further research development goals. The proposed hybrid controller is then described and both simulation and experimental data for controller design is presented. To enable the envisioned hybrid control systems, a human state estimator and a robot state estimator are required. The human state estimator uses computer vision and machine learning in a hourglass network structure to predict shoulder locations. Using the estimated location and depth data, human velocity, distance and orientation relative to the rollator are estimated. For the robot state estimator, a new velocity estimator based on learning methods is proposed. As rollator lateral velocity can be difficult to estimate with traditional methods, we propose an augmented learning-aided state estimator. This estimator is a Long- Short-Term Memory (LSTM) based estimator, augmented with an Unscented Kalman Filter (UKF). The proposed estimator was validated through experimental data. The main contribution of this thesis was a new lightweight rollator system with sensors and actuators that enabled development of advanced controls. Next, previous control systems are not only improved upon by using a new hybrid controller but also implemented on our platform. A new robot state estimator is developed that relies solely on the kinematics and is able to estimate lateral velocity with a mean error of $<10mm/s$ without requiring additional instrumentation or knowledge of the rollator's time varying parameters. Finally, a new human state estimator is designed which does not require instrumentation on the human and outperforms current estimators

Impact of Ear Occlusion on In-Ear Sounds Generated by Intra-oral Behaviors

We conducted a case study with one volunteer and a recording setup to detect sounds induced by the actions: jaw clenching, tooth grinding, reading, eating, and drinking. The setup consisted of two in-ear microphones, where the left ear was semi-occluded with a commercially available earpiece and the right ear was occluded with a mouldable silicon ear piece. Investigations in the time and frequency domains demonstrated that for behaviors such as eating, tooth grinding, and reading, sounds could be recorded with both sensors. For jaw clenching, however, occluding the ear with a mouldable piece was necessary to enable its detection. This can be attributed to the fact that the mouldable ear piece sealed the ear canal and isolated it from the environment, resulting in a detectable change in pressure. In conclusion, our work suggests that detecting behaviors such as eating, grinding, reading with a semi-occluded ear is possible, whereas, behaviors such as clenching require the complete occlusion of the ear if the activity should be easily detectable. Nevertheless, the latter approach may limit real-world applicability because it hinders the hearing capabilities.</p

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