Impedence Control for Variable Stiffness Mechanisms with Nonlinear Joint Coupling

The current discussion on physical human robot interaction and the related safety aspects, but also the interest of neuro-scientists to validate their hypotheses on human motor skills with bio-mimetic robots, led to a recent revival of tendondriven robots. In this paper, the modeling of tendon-driven elastic systems with nonlinear couplings is recapitulated. A control law is developed that takes the desired joint position and stiffness as input. Therefore, desired motor positions are determined that are commanded to an impedance controller. We give a physical interpretation of the controller. More importantly, a static decoupling of the joint motion and the stiffness variation is given. The combination of active (controller) and passive (mechanical) stiffness is investigated. The controller stiffness is designed according to the desired overall stiffness. A damping design of the impedance controller is included in these considerations. The controller performance is evaluated in simulation

Control of a wrist joint motion simulator: a phantom study

The presence of muscle redundancy and co-activation of agonist-antagonist pairs in vivo makes the optimization of the load distribution between muscles in physiologic joint simulators vital. This optimization is usually achieved by employing different control strategies based on position and/or force feedback. A muscle activated physiologic wrist simulator was developed to test and iteratively refine such control strategies on a functional replica of a human arm. Motions of the wrist were recreated by applying tensile loads using electromechanical actuators. Load cells were used to monitor the force applied by each muscle and an optical motion capture system was used to track joint angles of the wrist in real-time. Four control strategies were evaluated based on their kinematic error, repeatability and ability to vary co-contraction. With kinematic errors of less than 1.5°, the ability to vary co-contraction, and without the need for predefined antagonistic forces or muscle force ratios, novel control strategies – hybrid control and cascade control – were preferred over standard control strategies – position control and force control. Muscle forces obtained from hybrid and cascade control corresponded well with in vivo EMG data and muscle force data from other wrist simulators in the literature. The decoupling of the wrist axes combined with the robustness of the control strategies resulted in complex motions, like dart thrower’s motion and circumduction, being accurate and repeatable. Thus, two novel strategies with repeatable kinematics and physiologically relevant muscle forces are introduced for the control of joint simulators

A robotic model to investigate human motor control

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Concept of an exoskeleton for industrial applications with modulated impedance based on Electromyographic signal recorded from the operator

The introduction of an active exoskeleton that enhances the operator power in the manufacturing field was demonstrated in literature to lead to beneficial effects in terms of reducing fatiguing and the occurrence of musculo-skeletal diseases. However, a large number of manufacturing operations would not benefit from power increases because it rather requires the modulation of the operator stiffness. However, in literature, considerably less attention was given to those robotic devices that regulate their stiffness based on the operator stiffness, even if their introduction in the line would aid the operator during different manipulations respect with the exoskeletons with variable power. In this thesis the description of the command logic of an exoskeleton for manufacturing applications, whose stiffness is modulated based on the operator stiffness, is described. Since the operator stiffness cannot be mechanically measured without deflecting the limb, an estimation based on the superficial Electromyographic signal is required. A model composed of 1 joint and 2 antagonist muscles was developed to approximate the elbow and the wrist joints. Each muscle was approximated as the Hill model and the analysis of the joint stiffness, at different joint angle and muscle activations, was performed. The same Hill muscle model was then implemented in a 2 joint and 6 muscles (2J6M) model which approximated the elbow-shoulder system. Since the estimation of the exerted stiffness with a 2J6M model would be quite onerous in terms of processing time, the estimation of the operator end-point stiffness in realtime would therefore be questionable. Then, a linear relation between the end-point stiffness and the component of muscle activation that does not generate any end-point force, is proposed. Once the stiffness the operator exerts was estimated, three command logics that identifies the stiffness the exoskeleton is required to exert are proposed. These proposed command logics are: Proportional, Integral 1 s, and Integral 2 s. The stiffening exerted by a device in which a Proportional logic is implemented is proportional, sample by sample, to the estimated stiffness exerted by the operator. The stiffening exerted by the exoskeleton in which an Integral logic is implemented is proportional to the stiffness exerted by the operator, averaged along the previous 1 second (Integral 1 s) or 2 seconds (Integral 2 s). The most effective command logic, among the proposed ones, was identified with empirical tests conducted on subjects using a wrist haptic device (the Hi5, developed by the Bioengineering group of the Imperial College of London). The experimental protocol consisted in a wrist flexion/extension tracking task with an external perturbation, alternated with isometric force exertion for the estimation of the occurrence of the fatigue. The fatigue perceived by the subject, the tracking error, defined as the RMS of the difference between wrist and target angles, and the energy consumption, defined as the sum of the squared signals recorded from two antagonist muscles, indicated the Integral 1 s logic to be the most effective for controlling the exoskeleton. A logistic relation between the stiffness exerted by the subject and the stiffness exerted by the robotic devices was selected, because it assured a smooth transition between the maximum and the minimum stiffness the device is required to exert. However, the logistic relation parameters are subject-specific, therefore an experimental estimation is required. An example was provided. Finally, the literature about variable stiffness actuators was analyzed to identify the most suitable device for exoskeleton stiffness modulation. This actuator is intended to be integrated on an existing exoskeleton that already enhances the operator power based on the operator Electromyographic signal. The identified variable stiffness actuator is the DLR FSJ, which controls its stiffness modulating the preload of a single spring

Simulation And Control At the Boundaries Between Humans And Assistive Robots

Human-machine interaction has become an important area of research as progress is made in the fields of rehabilitation robotics, powered prostheses, and advanced exercise machines. Adding to the advances in this area, a novel controller for a powered transfemoral prosthesis is introduced that requires limited tuning and explicitly considers energy regeneration. Results from a trial conducted with an individual with an amputation show self-powering operation for the prosthesis while concurrently attaining basic gait fidelity across varied walking speeds. Experience in prosthesis development revealed that, though every effort is made to ensure the safety of the human subject, limited testing of such devices prior to human trials can be completed in the current research environment. Two complementary alternatives are developed to fill that gap. First, the feasibility of implementing impulse-momentum sliding mode control on a robot that can physically replace a human with a transfemoral amputation to emulate weight-bearing for initial prototype walking tests is established. Second, a more general human simulation approach is proposed that can be used in any of the aforementioned human-machine interaction fields. Seeking this general human simulation method, a unique pair of solutions for simulating a Hill muscle-actuated linkage system is formulated. These include using the Lyapunov-based backstepping control method to generate a closed-loop tracking simulation and, motivated by limitations observed in backstepping, an optimal control solver based on differential flatness and sum of squares polynomials in support of receding horizon controlled (e.g. model predictive control) or open-loop simulations. v The backstepping framework provides insight into muscle redundancy resolution. The optimal control framework uses this insight to produce a computationally efficient approach to musculoskeletal system modeling. A simulation of a human arm is evaluated in both structures. Strong tracking performance is achieved in the backstepping case. An exercise optimization application using the optimal control solver showcases the computational benefits of the solver and reveals the feasibility of finding trajectories for human-exercise machine interaction that can isolate a muscle of interest for strengthening

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

Design and Testing of an Agonist-Antagonist Position-Impedance Controlled Myoelectric Prosthesis

Intuitive prosthetic control is limited by the inability to easily convey intention and perceive physical requirements of the task. Rather than providing haptic feedback and allowing users to consciously control every component of manipulation, relegating some aspects of control to the device may simplify operation. This study focuses on the development and testing of a control scheme able to identify object stiffness and regulate impedance. The system includes an algorithm to detect the apparent stiffness of an object, a proportional nonlinear EMG control algorithm for interpreting a user’s desired grasp aperture, and an antagonistically acting impedance controller. Performance of a testbed prosthetic simulation used to controllably extrude pastes of different properties from a compliant tube was compared to that of the non-dominant human hand. The paste volume extrusion error and response time to perform the task were recorded for comparison. Statistical analysis using (GEE) and (TOST) suggests the prosthetic controller and human hand performed similarly along these metrics. Performance differences in the trials were more strongly correlated to tube type and repetition block. The results suggest that the developed controller allows users to perform a controlled squeezing task at a level comparable to the human hand with minimal training. It also suggests that a priori stiffness estimation acquired through quick palpations may be sufficient for effective control during simple manipulation. The lack of a learning curve suggests that the development of systems that automatically control aspects of mechanical interaction may offer users more advanced control capabilities with low cognitive load