Force Control of Musculoskeletal Manipulator Driven By Spiral Motors

This paper presents force control of musculoskeletal manipulator driven by spiral motors. The kinematic and dynamic properties are shown to address the presence of ennvironmental contact with the manipulator. From this contact, the force control schemes were explored, by comparing between monoarticular-only structure and biarticular structure manipulator. Force control schemes were divided into independent muscle control, end effector step force command, and muscular viscoelasticity control. The results show advantages of biarticular actuation compared to monoarticular-only actuation in the feasibility of magnetic levitation (gap) control alongside force control

Upravljanje silom mišićno-koštanog manipulatora pogonjenog spiralnim motorom

This paper presents force control of musculoskeletal manipulator driven by spiral motors. The kinematic and dynamic properties are shown to address the presence of ennvironmental contact with the manipulator. From this contact, the force control schemes were explored, by comparing between monoarticular-only structure and biarticular structure manipulator. Force control schemes were divided into independent muscle control, end effector step force command, and muscular viscoelasticity control. The results show advantages of biarticular actuation compared to monoarticular-only actuation in the feasibility of magnetic levitation (gap) control alongside force control.U ovome radu predstavljeno je upravljanje silom mišićno-koštanog manipulatora pogonjenog spiralnim motorom. Kinematička i dinamička svojstva prikazuju prisutnost kontakta manipulatora s okolinom. Na temelju kontakta istraženo je upravljanje silom usporedbom jednozglobne i dvozglobne strukture manipulatora. Upravljanje silom podijeljeno je u neovisno upravljanje mišićima, upravljanje alatom manipulatora (eng. end effector) i upravljanje mišićnom viskoelastičnosti. Rezultati pokazuju prednost dvozglobne strukture u odnosu na jednozglobnu u smislu izvedivosti upravljanja magnetskom levitacijom pored upravljanja silom

Planar Task Space Control of a Biarticular Manipulator Driven by Spiral Motors

This paper elaborates upon a musculoskeletal‐ inspired robot manipulator using a prototype of the spiral motor developed in our laboratory. The spiral motors represent the antagonistic muscles due to the high forward/backward drivability without any gears or mechanisms. Modelling of the biarticular structure with spiral motor dynamics was presented and simulations were carried out to compare two control methods, Inverse Kinematics (IK) and direct‐Cartesian control, between monoarticular only structures and biarticular structures using the spiral motor. The results show the feasibility of the control, especially in maintaining air gaps within the spiral motor

RBF Neural Network Control for Linear Motor-Direct Drive Actuator Based on an Extended State Observer

Hydraulic power and other kinds of disturbance in a linear motor-direct drive actuator (LM-DDA) have a great impact on the performance of the system. A mathematical model of the LM-DDA system is established and a double-loop control system is presented. An extended state observer (ESO) with switched gain was utilized to estimate the influence of the hydraulic power and other load disturbances. Meanwhile, Radial Basis Function (RBF) neural network was utilized to optimize the parameters in this intelligent controller. The results of the dynamic tests demonstrate the performance with rapid response and improved accuracy could be attained by the proposed control scheme

Design and evaluation of a powered prosthetic foot with monoarticular and biarticular actuation

To overcome the limitations of passive prosthetic feet, powered prostheses have been developed, that can provide the range of motion and power of their human counterparts. These devices can equalize spatio-temporal gait parameters and improve the metabolic effort compared to passive prostheses, but asymmetries and compensatory motions between the healthy and impaired leg remain. Unlike their human counter part, existing powered prosthetic feet are fully monoarticular actuating only the prosthetic ankle joint, whereas in the biological counter part, ankle and knee joint are additionally coupled by the biarticular gastrocnemius muscle. The goal of this work is to investigate the benefits of a powered biarticular transtibial prosthesis comprising mono- and biarticular actuators similar to the human example. The contributions of the present work are as follows: A biarticular prosthesis prototype is methodically designed to match the capabilities of the monoarticular muscles at the human ankle joint as well as the biarticular gastrocnemius muscle during level walking. The prototype consists of an existing powered monoarticular prosthetic foot, which is extended with a knee orthoses and a stationary biarticular Bowden cable actuator. Both actuators are modeled as serial elastic actuators (SEA) and the identification of the model parameters is conducted. A model based torque control utilizing the measurements commonly available in SEAs, an impedance control law based on human ankle reference trajectories, and a high level control to enable steady walking in the lab are introduced. The proposed hardware setup and control structure can provide sagittal plane angles and torques similar to the mono- and biarticular muscles at the human ankle, with proper torque tracking performance and a freely adjustable allocation of torque between the monoarticular and biarticular actuator. The biarticular prosthesis is evaluated in the gait lab with three subjects with unilateral transtibial amputation utilizing a continuous sweep experimental protocol to investigate the metabolic effort and spatio-temporal gait parameters. All subjects show a tendency to reduced metabolic effort for medium activity of the artificial gastrocnemius, although noise level and time variation are large. In addition to the reduction in metabolic effort, the artificial gastrocnemius is able to influence spatio temporal gait parameters between the impaired and the intact side, but partially opposing effects are observed among the individual subjects. In conclusion, this thesis describes the implementation of an artificial gastrocnemius following the human example and the systematic investigation of metabolic effort and spatio-temporal gait parameters. It is shown that the addition of the artificial gastrocnemius to a monoarticular prosthesis can positively affect the investigated parameters. The meaningfulness of the results should be improved by increased clinical effort in future work

A method for the mechatronico analysis of parallel kinematics manipulators based on decoupling the dynamics of actuators and mechanism

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Intrinsic and Extrinsic Biomechanical Factors in a Co-adaptive ECoG-based Brain Computer Interface

Paralysis, due to spinal cord injury, amyotrophic lateral sclerosis (ALS), or stroke, is the result of severed communication between the brain and the motor periphery. Brain computer interfaces (BCIs) are neuroprosthetic devices that create novel communication pathways by measuring and transforming neural activity into operational commands. State of the art BCI systems measure brain activity using penetrating electrode arrays able to record from hundreds of individual cortical neurons simultaneously. Unfortunately, these systems are highly susceptible to signal degradation which limits their efficacy to 1-2 years. However, electrocorticography (ECoG) signals recorded from the surface of the brain deliver a more competitive balance between surgical risk, long-term stability, signal bandwidth, and signal-to-noise ratio when compared to both the aforementioned intracortical systems and the more common non-invasive electroencephalography (EEG) technologies. Historically, neural signals for controlling a computer cursor or robotic arm have been mapped to extrinsic, kinematic (i.e. position or velocity) variables. Although this strategy is adequate for use in simple environments, it may not be ideal for control of real-world prosthetic devices that are subject to external and unexpected forces. When reaching for an object, the trajectory of the hand through space can be defined in either extrinsic (e.g. Cartesian) or intrinsic (e.g. joint angles, muscle forces) frames of reference. During this movement, the brain has to perform a series of sensorimotor transformations that involve solving a complex, 2nd order differential equation (i.e. musculoskeletal biomechanics) in order to determine the appropriate muscle activations. Functional neuromuscular stimulation (FNS) is a desirable BCI application because it attempts to restore motor function to paralyzed limbs through electrical excitation of muscles. Rather than applying the conventional extrinsic kinematic control signals to such a system, it may be more appropriate to map neural activity to muscle activation directly and allow the brain to develop its own transfer function. This dissertation examines the application of intrinsic decoding schemes to control an upper limb using ECoG in non-human primates. ECoG electrode arrays were chronically implanted in rhesus monkeys over sensorimotor cortex. A novel multi-joint reaching task was developed to train the subjects to control a virtual arm simulating muscle and inertial forces. Utilizing a co-adaptive algorithm (where both the brain adapts via biofeedback and the decoding algorithm adapts to improve performance), new decoding models were initially built over the course of the first 3-5 minutes of each daily experimental session and then continually adapted throughout the day. Three subjects performed the task using neural control signals mapped to 1) joint angular velocity, 2) joint torque, and 3) muscle forces of the virtual arm. Performance exceeded 97%, 93%, and 89% accuracy for the three control paradigms respectively. Neural control features in the upper gamma frequency bands (70-115 and 130-175 Hz) were found to be directionally tuned in an ordered fashion, with preferred directions varying topographically in the mediolateral direction without distinction between motor and sensory areas. Long-term stability was demonstrated by all three monkeys, which maintained performance at 42, 55, and 57 months post-implantation. These results provide insights into the capabilities of sensorimotor cortex for control of non-linear multi-joint reaching dynamics and present a first step toward design of intrinsic, force-based BCI systems suitable for long-term FNS applications