Adaptive Compliance Shaping with Human Impedance Estimation

Human impedance parameters play an integral role in the dynamics of strength amplification exoskeletons. Many methods are used to estimate the stiffness of human muscles, but few are used to improve the performance of strength amplification controllers for these devices. We propose a compliance shaping amplification controller incorporating an accurate online human stiffness estimation from surface electromyography (sEMG) sensors and stretch sensors connected to the forearm and upper arm of the human. These sensor values along with exoskeleton position and velocity are used to train a random forest regression model that accurately predicts a person's stiffness despite varying movement, relaxation, and muscle co-contraction. Our model's accuracy is verified using experimental test data and the model is implemented into the compliance shaping controller. Ultimately we show that the online estimation of stiffness can improve the bandwidth and amplification of the controller while remaining robustly stable.Comment: 8 pages, 9 figures, Accepted for publication at the 2020 American Control Conference. Copyright IEEE 202

Robust Estimator-Based Safety Verification: A Vector Norm Approach

In this paper, we consider the problem of verifying safety constraint satisfaction for single-input single-output systems with uncertain transfer function coefficients. We propose a new type of barrier function based on a vector norm. This type of barrier function has a measurable upper bound without full state availability. An identifier-based estimator allows an exact bound for the uncertainty-based component of the barrier function estimate. Assuming that the system is safe initially allows an exponentially decreasing bound on the error due to the estimator transient. Barrier function and estimator synthesis is proposed as two convex sub-problems, exploiting linear matrix inequalities. The barrier function controller combination is then used to construct a safety backup controller. And we demonstrate the system in a simulation of a 1 degree-of-freedom human-exoskeleton interaction.Comment: 6 pages, 5 figures. Accepted for publication at the 2020 American Control Conference. Copyright IEEE 202

Towards a safe and responsive control framework for human-centered robots

Human-centered robots are a specific kind of service robot, which interact with humans physically or cognitively and help humans with tasks in uncertain environments. They can be humanoid robots, exoskeletons, or manipulators and mobile platforms that provide us good services. However, human-centered robots are still not perfect enough for us to use nowadays. On the one hand, human-centered robots are still slow and inefficient for their tasks because the human inputs and dynamics that they react to are uncertain, immeasurable, or even completely unknown. On the other hand, human-centered robots face much more complicated safety requirements than other kinds of robots because humans are dynamic and vulnerable during physical human-robot interaction. To resolve these issues of human-centered robots, the work in this dissertation explores new models for reducing human uncertainty and new control algorithms for improving safety warranty. The first half of this dissertation introduces a complex stiffness model for describing the uncertain human impedance. The discovery of this new model is motivated to explain the observation of a consistent damping ratio of a human versus different environmental dynamics. It replaces the linear damping term in a conventional mass-spring-damping model with a hysteretic damping term, an imaginary value in the frequency domain. Because of the correlation between the stiffness term and the newly discovered hysteretic damping term in the complex stiffness model, we can significantly reduce the human impedance uncertainty. Based on the complex stiffness model, we can adopt nonlinear control strategies for improving the responsiveness and the human-friendliness of human-centered robots. The second half of this dissertation introduces the concept of a barrier pair, which consists of a barrier function and a controller for the safety verification and warranty of a human-centered robot. We obtain a barrier pair by solving an optimization problem subject to a series of linear matrix inequalities representing the state-space, input, and stability constraints of a human-centered robot. By incorporating sampling-based methods into the synthesis of barrier pairs, human-centered robots can guarantee safe operation with non-convex state-space constraints. The sampling-based barrier pair method helps us construct a control framework of human-robot shared autonomy. A human-centered robot in this control framework uses an inference of a human's objective to figure out how to assist the human and prevent the human from potential accidents.Mechanical Engineerin

Development of Digital Control Systems for Wearable Mechatronic Devices: Applications in Musculoskeletal Rehabilitation of the Upper Limb

The potential for wearable mechatronic systems to assist with musculoskeletal rehabilitation of the upper limb has grown with the technology. One limiting factor to realizing the benefits of these devices as motion therapy tools is within the development of digital control solutions. Despite many device prototypes and research efforts in the surrounding fields, there are a lack of requirements, details, assessments, and comparisons of control system characteristics, components, and architectures in the literature. Pairing this with the complexity of humans, the devices, and their interactions makes it a difficult task for control system developers to determine the best solution for their desired applications. The objective of this thesis is to develop, evaluate, and compare control system solutions that are capable of tracking motion through the control of wearable mechatronic devices. Due to the immaturity of these devices, the design, implementation, and testing processes for the control systems is not well established. In order to improve the efficiency and effectiveness of these processes, control system development and evaluation tools have been proposed. The Wearable Mechatronics-Enabled Control Software framework was developed to enable the implementation and comparison of different control software solutions presented in the literature. This framework reduces the amount of restructuring and modification required to complete these development tasks. An integration testing protocol was developed to isolate different aspects of the control systems during testing. A metric suite is proposed that expands on the existing literature and allows for the measurement of more control characteristics. Together, these tools were used ii ABSTRACT iii to developed, evaluate, and compare control system solutions. Using the developed control systems, a series of experiments were performed that involved tracking elbow motion using wearable mechatronic elbow devices. The accuracy and repeatability of the motion tracking performances, the adaptability of the control models, and the resource utilization of the digital systems were measured during these experiments. Statistical analysis was performed on these metrics to compare between experimental factors. The results of the tracking performances show some of the highest accuracies for elbow motion tracking with these devices. The statistical analysis revealed many factors that significantly impact the tracking performance, such as visual feedback, motion training, constrained motion, motion models, motion inputs, actuation components, and control outputs. Furthermore, the completion of the experiments resulted in three first-time studies, such as the comparison of muscle activation models and the quantification of control system task timing and data storage needs. The successes of these experiments highlight that accurate motion tracking, using biological signals of the user, is possible, but that many more efforts are needed to obtain control solutions that are robust to variations in the motion and characteristics of the user. To guide the future development of these control systems, a national survey was conducted of therapists regarding their patient data collection and analysis methods. From the results of this survey, a series of requirements for software systems, that allow therapists to interact with the control systems of these devices, were collected. Increasing the participation of therapists in the development processes of wearable assistive devices will help to produce better requirements for developers. This will allow the customization of control systems for specific therapies and patient characteristics, which will increase the benefit and adoption rate of these devices within musculoskeletal rehabilitation programs

Application of wearable sensors in actuation and control of powered ankle exoskeletons: a Comprehensive Review

Powered ankle exoskeletons (PAEs) are robotic devices developed for gait assistance, rehabilitation, and augmentation. To fulfil their purposes, PAEs vastly rely heavily on their sensor systems. Human–machine interface sensors collect the biomechanical signals from the human user to inform the higher level of the control hierarchy about the user’s locomotion intention and requirement, whereas machine–machine interface sensors monitor the output of the actuation unit to ensure precise tracking of the high-level control commands via the low-level control scheme. The current article aims to provide a comprehensive review of how wearable sensor technology has contributed to the actuation and control of the PAEs developed over the past two decades. The control schemes and actuation principles employed in the reviewed PAEs, as well as their interaction with the integrated sensor systems, are investigated in this review. Further, the role of wearable sensors in overcoming the main challenges in developing fully autonomous portable PAEs is discussed. Finally, a brief discussion on how the recent technology advancements in wearable sensors, including environment—machine interface sensors, could promote the future generation of fully autonomous portable PAEs is provided

Design, implementation and control of rehabilitation robots for upper and lower limbs

We present two novel rehabilitation robots for stroke patients. For lower limb stroke rehabilitation, we present a novel self-aligning exoskeleton for the knee joint. The primal novelty of the design originates from its kinematic structure that allows translational movements of the knee joint on the sagittal plane along with the knee rotation. Automatically adjusting its joint axes, the exoskeleton enables a perfect match between human joint axes and the device axes. Thanks to this feature, the knee exoskeleton is not only capable of guaranteeing ergonomy and comfort throughout the therapy, but also extends the usable range of motion for the knee joint. Moreover, this adjustability feature significantly shortens the setup time required to attach the patient to the robot, allowing more effective time be spend on exercises instead of wasting it for adjustments. We have implemented an impedance-type concept of the knee exoskeleton, experimentally characterized its closed-loop performance and demonstrated ergonomy and useability of this device through human subject experiments. To administer table top exercises during upper limb stroke rehabilitation, we present a novel Mecanum-wheeled holonomic mobile rehabilitation robot for home therapy. The device can move/rotate independently on its unlimited planar workspace to provide assistance to patients. We have implemented two different concepts of holonomic mobile platform based on different actuation and sensing principles: an admittance-type mobile robot and a mobile platform with series elastic actuation. The admittance-type robot is integrated with virtual reality simulations and can assist patients through virtual tunnels designed around nominal task trajectories. The holonomic platform with series elastic actuation eliminates the need for costly force sensors and enables implementation of closed loop force control with higher controller gains, providing robustness against imperfections in the power transmission and allowing lower cost drive components to be utilized. For contour following tasks with the holonomic platforms, we have synthesized passive velocity field controllers (PVFC) that ensure coordination and synchronization between various degrees of freedom of the patient arm, while letting patients to complete the task at their own preferred pace. PVFC not only minimizes the contour error but also ensures coupled stability of the human-in-the-loop system