Brain computer interface based robotic rehabilitation with online modification of task speed

We present a systematic approach that enables online modification/adaptation of robot assisted rehabilitation exercises by continuously monitoring intention levels of patients utilizing an electroencephalogram (EEG) based Brain-Computer Interface (BCI). In particular, we use Linear Discriminant Analysis (LDA) to classify event-related synchronization (ERS) and desynchronization (ERD) patterns associated with motor imagery; however, instead of providing a binary classification output, we utilize posterior probabilities extracted from LDA classifier as the continuous-valued outputs to control a rehabilitation robot. Passive velocity field control (PVFC) is used as the underlying robot controller to map instantaneous levels of motor imagery during the movement to the speed of contour following tasks. In other words, PVFC changes the speed of contour following tasks with respect to intention levels of motor imagery. PVFC also allows decoupling of the task and the speed of the task from each other, and ensures coupled stability of the overall robot patient system. The proposed framework is implemented on AssistOn-Mobile - a series elastic actuator based on a holonomic mobile platform, and feasibility studies with healthy volunteers have been conducted test effectiveness of the proposed approach. Giving patients online control over the speed of the task, the proposed approach ensures active involvement of patients throughout exercise routines and has the potential to increase the efficacy of robot assisted therapies

Parameter-Dependent Lyapunov Functions for Linear Systems With Constant Uncertainties

Robust stability of linear time-invariant systems with respect to structured uncertainties is considered. The small gain condition is sufficient to prove robust stability and scalings are typically used to reduce the conservatism of this condition. It is known that if the small gain condition is satisfied with constant scalings then there is a single quadratic Lyapunov function which proves robust stability with respect to all allowable time-varying perturbations. In this technical note we show that if the small gain condition is satisfied with frequency-varying scalings then an explicit parameter dependent Lyapunov function can be constructed to prove robust stability with respect to constant uncertainties. This Lyapunov function has a rational quadratic dependence on the uncertainties

Smart Exercise Adaptive Control of a Three Degree of Freedom Upper-limb Manipulator Robot

An adaptive velocity field controller for robotic manipulators is proposed in this thesis. The control objective is to cause the user to exercise in a manner that optimizes a criterion related to the user’s mechanical power. The control structure allows for passive user-manipulator physical interaction while the adaptive algorithm identifies the user’s biomechanical characteristics as a linear Hill based force-velocity curve defined at each pose of a repetitive exercise motion i.e. a Hill surface. The study of such a surface allows for the characterization of maximal effort exercise tasks and subsequently the control of exercises that is unique to each user. This allows for the intelligent characterization of a user’s abilities such that repetitive exercises defined by velocity fields can be safely performed. Such a study involving a 3DOF manipulator operating in full 3D has not been conducted in literature to the best of author’s knowledge. The proposed control structure is verified through experimentation on a unimanual setup of the BURT rehabilitation manipulator system involving a single user. The manipulator system includes friction, actuator/sensor noise, and unmodelled dynamics

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

Optimal exoskeleton design and effective human-in-the-loop control frameworks for rehabilitation robotics

Attention, since they decrease the cost of repetitive movement therapies, enable quantitative measurement of the patient progress and promise development of more e ective rehabilitation protocols. The goal of this dissertation is to provide systematic frameworks for optimal design of rehabilitation robots and e ective delivery of therapeutic exercises. The design framework is built upon identification and categorization of the design requirements, and satisfaction of them through several design stages. In particular, type selection is performed to ensure imperative design requirements of safety, ergonomy and wearability, optimal dimensional synthesis is undertaken to maximize global kinematic and dynamic performance defined over the singularity-free workspace volume, while workspace optimization is performed to utilize maximum singularity-free device workspace computed via Grassmann line theory. Then, humanin- the-loop controllers that ensure coupled stability of the human-robot system are implemented in the robot task space using appropriate error metrics. The design framework is demonstrated on a forearm-wrist exoskeleton, since forearm and wrist rotations are critical in performing activities of daily living and recovery of these joints is essential for achieving functional independence of patients. In particular, a non-symmetric 3RPS-R mechanism is selected as the underlying kinematics type and the performance improvements due to workspace and multi-criteria optimizations are experimentally characterized as 27 % larger workspace volume, 32 % higher position control bandwidth and 17 % increase in kinematic isotropy when compared to a similar device in the literature. The exoskeleton is also shown to feature high passive back-driveability and accurate sti ness rendering capability, even under open-loop impedance control. Local controllers to accommodate for each stage of rehabilitation therapies are designed for the forearm-wrist exoskeleton in SO(3): trajectory tracking controllers are designed for early stages of rehabilitation when severely injured patients are kept passive, impedance controllers are designed to render virtual tunnels implementing forbidden regions in the device workspace and allowing for haptic interactions with virtual environments, and passive contour tracking controllers are implemented to allow for rehabilitation exercises that emphasize coordination and synchronization of multi degrees-of-freedom movements, while leaving the exact timing along the desired contour to the patient. These local controllers are incorporated into a multi-lateral shared controller architecture, which allows for patients to train with online virtual dynamic tasks in collaboration with a therapist. Utilizing this control architecture not only enables the shift of control authority of each agent so that therapists can guide or evaluate movements of patients or share the control with them, but also enables the implementation of remote and group therapies, as well as remote assessments. The proposed control framework to deliver e ective robotic therapies can ensure active involvement of patients through online modification of the task parameters, while simultaneously guaranteeing their safety. In particular, utilizing passive velocity field control and extending it with a method for online generation of velocity fields for parametric curves, temporal, spatial and assistive aspects of a desired task can be seamlessly modified online, while ensuring passivity with respect to externally applied forces. Through human subject experiments, this control framework is shown to be e ective in delivering evidence-based rehabilitation therapies, providing assistance as-needed, preventing slacking behavior of patients, and delivering repetitive therapies without exact repetition. Lastly, to guide design of e ective rehabilitation treatment protocols, a set of healthy human subject experiments are conducted in order to identify underlying principles of adaptation mechanism of human motor control system. In these catch-trial based experiments, equivalent transfer functions are utilized during execution of rhythmic dynamic tasks. Statistical evidence suggests that i) force feedback is the dominant factor that guides human adaptation while performing fast rhythmic dynamic tasks rather than the visual feedback and ii) as the e ort required to perform the task increases, the rate of adaptation decreases; indicating a fundamental trade-o between task performance and level of force feedback provided

Control of a BCI-based upper limb rehabilitation system utilizing posterior probabilities (BBA tabanlı üst uzuv rehabilitasyon sisteminin sonsal olasılık değerleri kullanılarak kontrolü)

In this paper, an electroencephalogram (EEG) based Brain-Computer Interface (BCI) is integrated with a robotic system designed to target rehabilitation therapies of stroke patients such that patients can control the rehabilitation robot by imagining movements of their right arm. In particular, the power density of frequency bands are used as features from the EEG signals recorded during the experiments and they are classified by Linear Discriminant Analysis (LDA). As one of the novel contributions of this study, the posterior probabilities extracted from the classifier are directly used as the continuous-valued outputs, instead of the discrete classification output commonly used by BCI systems, to control the speed of the therapeutic movements performed by the robotic system. Adjusting the exercise speed of patients online, as proposed in this study, according to the instantaneous levels of motor imagery during the movement, has the potential to increase efficacy of robot assisted therapies by ensuring active involvement of patients. The proposed BCI-based robotic rehabilitation system has been successfully implemented on physical setups in our laboratory and sample experimental data are presented

Design, control and implementation of CoCoA: a human-friendly autonomous service robot

The growing demand to automate everyday tasks combined with the rapid development of software technologies that can furnish service robots with a large repertoire of skills, are driving the need for design and implementation of human-friendly service robots, i.e., safe and dependable machines operating in the close vicinity of humans or directly interacting with them in social domains. The technological shift from classical industrial robots utilized in structured factory oors to service robots that are used in close collaboration with humans introduces many demanding challenges to ensure safety and autonomy of operation of such robots. In this thesis, we present mechanical design, modeling and software integration for motion/navigation planning, and human-collaborative control of a human-friendly service robot CoCoA: Cognitive Collaborative Assistant. CoCoA is designed to be bimanual with dual 7 degrees-of-freedom (DoF) anthropomorphic arms, featuring spherical wrists. Each arm weighs less than 1.6 kg and possesses a payload capacity of 1 kg. Bowden-cable based transmissions are used for the arms to enable grounding of motors and this arrangement results in lightweight arms with passive back-driveability. Thanks to passive back-driveability and low inertia of its arms, the operation of CoCoA is guaranteed to be safe not only during physical interactions, but also under collisions with the robot arms. The holonomic base of Co- CoA possesses four driven and steered wheel modules and is compatible with wheelchair accessible environments. CoCoA also features a single DoF torso, and dual one DoF grippers, resulting in a service robot with a total of 25 active DoF. The dynamic/kinematic/geometric models of CoCoA are derived in open source software. Inverse kinematics, stable grasp, kinematic reachability and inverse reachability databases are generated for the robot to enable computation of kinematically-feasible collision-free motion/grasp plans for its arms/grippers and navigation plans for its holonomic base, at interactive rates. For the real-time control of the robot, motion/navigation plans characterizing feasible joint trajectories are passed to feedback controllers dedicated to each joint. The joint space control of each joint is implemented in hardware, while communication/synchronization among di erent DoF is ensured through EtherCAT/RS-485 eldbuses running at high sampling rates. To comply with human movements under physical interactions and to enable human collaborative contour tracking tasks, CoCoA also implements passive velocity eld control that guarantees user safety by ensuring passivity of interaction with respect to externally applied forces. The feasibility of the design and the applicability of the overall planning and control framework are demonstrated through dynamic simulations and physical implementations of several service robotics scenarios

Vector Field Control Methods for Discretely Variable Passive Robotic Devices

Passive transmission-based robotic devices are capable of providing motion guidance while ensuring user safety and engagement. To circumvent some of the drawbacks associated with steering continuously variable transmissions based on rolling contacts, we are exploring a class of discretely variable devices, based on brakes and hydrostatic transmissions. Previously available control methods for discretely variable devices were built on velocity fields and only developed to stabilize a 1D target manifold. For n -DOF devices, methods to stabilize target manifolds of dimension 1 to n—1 are of interest. In this paper we contribute constraint field methods that stabilize n — 1 dimensional target manifolds while leaving the orthogonal subspace free to the control of the operator. We also contribute force-modulated SDOF velocity fields, which add between 1 and n— 2 virtual DOFs to the motion of devices whose physical constraints leave one DOF. Control performance is demonstrated in simulation for 3-DOF devices capable of imposing 1-D or 2-D constraints and in experiment for 2-DOF devices imposing 1-D constraints. Our experimental apparatus features digital hydraulic transmissions that are easily configured for n-dimensional space and capable of imposing constraints of any dimension, thus motivating the contributed methods

Multi-AGV transport of a load: state of art and centralized proposal

[EN] An automatic guided vehicle is a battery powered fully automated industrial transport system. These vehicles are widely used in the industrial sector to substitute manual forklifts and conveyors. The challenge of using AGVs as transport agents in industrial environments goes through providing them with enough intelligence to develop collaborative tasks. Among these collaborative tasks the multi-AGV transport of one object is differentiated from the multi-object multi-AGV transport. This work presents the state of art of cooperative transport solutions of one object between several AGVs. The theoretical fundaments are revised and several proposals for its resolution are classified and described. Finally, an own proposal of one-object multi-AGV transport with omnidirectional AGVs based on centralized remote control is presented.[ES] Un vehículo de guiado automático (Automatic Guided Vehicle –AGV-en inglés) es un sistema de transporte industrial completamente automatizado y alimentado por baterías. Estos vehículos son ampliamente utilizados en el sector industrial para sustituir a carretillas manuales y cintas transportadoras. El reto de la utilización de AGVs como agentes de transporte en entornos industriales pasa por dotarles de la inteligencia suficiente para desarrollar tareas colaborativas. Dentro de estas tareas colaborativas se diferencia el transporte multi-AGV de un objeto del transporte multi-AGV de múltiples objetos. Este trabajo presenta el estado del arte de las soluciones de transporte cooperativo de un objeto entre varios AGVs. Para ello, se revisan los fundamentos teóricos y se clasifican y describen varias propuestas para su resolución. Finalmente se propone una solución de control remoto centralizado para el transporte de una carga con AGVs omnidireccionales.Este trabajo ha sido apoyado parcialmente por la Junta de Castilla y León bajo el proyecto 10/16/BU/0014 y la empresa ASTI Mobile Robotics.Espinosa, F.; Santos, C.; Sierra-García, JE. (2020). Transporte multi-AGV de una carga: estado del arte y propuesta centralizada. Revista Iberoamericana de Automática e Informática industrial. 18(1):82-91. https://doi.org/10.4995/riai.2020.12846OJS8291181Adăscăliţei, F., and Doroftei, I. 2011. Practical Applications for Mobile Robots based on Mecanum Wheels - A Systematic Survey. The Romanian Review Precision Mechanics, Optics & Mechatronics, nº 40.Alonso-Mora, J., Barker, S. and Rus, D. 2017. Multi-robot formation control and object transport in dynamic environments via constrained optimization. The International Journal of Robotics Research. 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