Error minimising gradients for improving cerebellar model articulation controller performance

In motion control applications where the desired trajectory velocity exceeds an actuator’s maximum velocity limitations, large position errors will occur between the desired and actual trajectory responses. In these situations standard control approaches cannot predict the output saturation of the actuator and thus the associated error summation cannot be minimised.An adaptive feedforward control solution such as the Cerebellar Model Articulation Controller (CMAC) is able to provide an inherent level of prediction for these situations, moving the system output in the direction of the excessive desired velocity before actuator saturation occurs. However the pre-empting level of a CMAC is not adaptive, and thus the optimal point in time to start moving the system output in the direction of the excessive desired velocity remains unsolved. While the CMAC can adaptively minimise an actuator’s position error, the minimisation of the summation of error over time created by the divergence of the desired and actual trajectory responses requires an additional adaptive level of control.This thesis presents an improved method of training CMACs to minimise the summation of error over time created when the desired trajectory velocity exceeds the actuator’s maximum velocity limitations. This improved method called the Error Minimising Gradient Controller (EMGC) is able to adaptively modify a CMAC’s training signal so that the CMAC will start to move the output of the system in the direction of the excessive desired velocity with an optimised pre-empting level.The EMGC was originally created to minimise the loss of linguistic information conveyed through an actuated series of concatenated hand sign gestures reproducing deafblind sign language. The EMGC concept however is able to be implemented on any system where the error summation associated with excessive desired velocities needs to be minimised, with the EMGC producing an improved output approximation over using a CMAC alone.In this thesis, the EMGC was tested and benchmarked against a feedforward / feedback combined controller using a CMAC and PID controller. The EMGC was tested on an air-muscle actuator for a variety of situations comprising of a position discontinuity in a continuous desired trajectory. Tested situations included various discontinuity magnitudes together with varying approach and departure gradient profiles.Testing demonstrated that the addition of an EMGC can reduce a situation’s error summation magnitude if the base CMAC controller has not already provided a prior enough pre-empting output in the direction of the situation. The addition of an EMGC to a CMAC produces an improved approximation of reproduced motion trajectories, not only minimising position error for a single sampling instance, but also over time for periodic signals

Semi-autonomous control of prosthetic hands based on multimodal sensing, human grasp demonstration and user intention

Semi-autonomous control strategies for prosthetic hands provide a promising way to simplify and improve the grasping process for the user by adopting techniques usually applied in robotic grasping. Such strategies endow prosthetic hands with the ability to autonomously select and execute grasps while keeping the user in the loop to intervene at any time for triggering, accepting or rejecting decisions taken by the controller in an intuitive and easy way. In this paper, we present a semi-autonomous control strategy that allows the user to perform fluent grasping of everyday objects based on a single EMG channel and a multi-modal sensor system embedded in the hand for object perception and autonomous grasp execution. We conduct a user study with 20 subjects to assess the effectiveness and intuitiveness of our semi-autonomous control strategy and compare it to a conventional electromyography-based control strategy. The results show that the workload is reduced by 25.9 % compared to conventional electromyographic control, the physical demand is reduced by 60 % and the grasping process is accelerated by 19.4 %

Design and development of a hominid robot with local control in its adaptable feet to enhance locomotion capabilities

With increasing mechanization of our daily lives, the expectations and demands in robotic systems increase in the general public and in scientists alike. In recent events such as the Deepwater Horizon''-accident or the nuclear disaster at Fukushima, mobile robotic systems were used, e.g., to support local task forces by gaining visual material to allow an analysis of the situation. Especially the Fukushima example shows that the robotic systems not only have to face a variety of different tasks during operation but also have to deal with different demands regarding the robot's mobility characteristics. To be able to cope with future requirements, it seems necessary to develop kinematically complex systems that feature several different operating modes. That is where this thesis comes in: A robotic system is developed, whose morphology is oriented on chimpanzees and which has the possibility due to its electro-mechanical structure and the degrees of freedom in its arms and legs to walk with different gaits in different postures. For the proposed robot, the chimpanzee was chosen as a model, since these animals show a multitude of different gaits in nature. A quadrupedal gait like crawl allows the robot to traverse safely and stable over rough terrain. A change into the humanoid, bipedal posture enables the robot to move in man-made environments. The structures, which are necessary to ensure an effective and stable locomotion in these two poses, e.g., the feet, are presented in more detail within the thesis. This includes the biological model and an abstraction to allow a technical implementation. In addition, biological spines are analyzed and the development of an active, artificial spine for the robotic system is described. These additional degrees of freedom can increase the robot's locomotion and manipulation capabilities and even allow to show movements, which are not possible without a spine. Unfortunately, the benefits of using an artificial spine in robotic systems are nowadays still neglected, due to the increased complexity of system design and control. To be able to control such a kinematically complex system, a multitude of sensors is installed within the robot's structures. By placing evaluation electronics close by, a local and decentralized preprocessing is realized. Due to this preprocessing is it possible to realize behaviors on the lowest level of robot control: in this thesis it is exemplarily demonstrated by a local controller in the robot's lower leg. In addition to the development and evaluation of robot's structures, the functionality of the overall system is analyzed in different environments. This includes the presentation of detailed data to show the advantages and disadvantages of the local controller. The robot can change its posture independently from a quadrupedal into a bipedal stance and the other way around without external assistance. Once the robot stands upright, it is to investigate to what extent the quadrupedal walking pattern and control structures (like the local controller) have to be modified to contribute to the bipedal walking as well

Design and development of robust hands for humanoid robots

Design and development of robust hands for humanoid robot

Mental State Attribution to Robots: A Systematic Review of Conceptions, Methods, and Findings

The topic of mental state attribution to robots has been approached by researchers from a variety of disciplines, including psychology, neuroscience, computer science, and philosophy. As a consequence, the empirical studies that have been conducted so far exhibit considerable diversity in terms of how the phenomenon is described and how it is approached from a theoretical and methodological standpoint. This literature review addresses the need for a shared scientific understanding of mental state attribution to robots by systematically and comprehensively collating conceptions, methods, and findings from 155 empirical studies across multiple disciplines. The findings of the review include that: (1) the terminology used to describe mental state attribution to robots is diverse but largely homogenous in usage; (2) the tendency to attribute mental states to robots is determined by factors such as the age and motivation of the human as well as the behavior, appearance, and identity of the robot; (3) there is a computer < robot < human pattern in the tendency to attribute mental states that appears to be moderated by the presence of socially interactive behavior; (4) there are conflicting findings in the empirical literature that stem from different sources of evidence, including self-report and non-verbal behavioral or neurological data. The review contributes toward more cumulative research on the topic and opens up for a transdisciplinary discussion about the nature of the phenomenon and what types of research methods are appropriate for investigation

Projeto do sistema de controle de um exoesqueleto do membro inferior direito

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Mecânica, 2017.Nesta pesquisa o modelo de um exoesqueleto do membro inferior direita para melhorar a mobilidade do usuário e seu sistema de controle foram desenvolvidos. O projeto físico do modelo do exoesqueleto consiste em três partes principais: um quadril e a parte superior e inferior da perna conectados um com o outro por juntas revolutas. Cada uma das juntas é atuado por um motor Brushless DC (BLDC) com caixa de redução para aumentar torque. Os motores a serem usados na construção possuem sensores de velocidade e de posição para fornecer os dados necessários para o sistema de controle. Solidworks Computer Aided Design (CAD) software é usado para desenvolver o modelo do exoesqueleto, que é salvo em formato extensible markup language (XML) para depois ser importado em Simmechanics, permitindo a integração de modelos de corpos físicos com componentes de Simulink. A cinemática inversa do exoesqueleto é desenvolvido e projetado em Very high speed integrated circuit Hardware Description Language (VHDL) usando aritmética em ponto flutuante para ser executado a partir de um dispositivo Field Programmable Gate Array (FPGA). Quatro representações diferentes do projeto de hardware do modelo cinematico do exoesqueleto foram desenvolvidos fazendo análise de erro com Mean Square Error (MSE) e Average Relative Error (ARE). Análise de trade-off de desempenho e área em FPGA é feito. A estratégia de controle Proportional-Integrative-Derivative (PID) é escolhido para desenvolver o sistema de controle do exoesqueleto por ser relativamente simples e eficiente para desenvolver e por ser amplamente usado em muitas áreas de aplicação. Duas estratégias de sistemas de controle combinado de posiçaõ e velocidade são desenvolvidos e comparados um com o outro. Cada sistema de controle consiste em dois controladores de velocidade e dois de posição. Os parâmetros PID são calculados usando os métodos de sintonização Ziegler-Nichols e Particle Swarm Optimization (PSO). PSO é um método de sintonização relativamente simples porém eficiente que é aplicado em muitos problemas de otimização. PSO é baseado no comportamento supostamente inteligente de cardumes de peixes e bandos de aves em procura de alimento. O algoritmo, junto com o método Ziegler-Nichols, é usado para achar parâmetros PID apropriados para os blocos de controle nas duas estratégias te controle desenvolvidos. A resposta do sistema de controle é avaliada, analisando a resposta a um step input. Simulação da marcha humana é também feito nos dois modelos de sistema de controle do exoesqueleto fornecendo dados de marcha humana ao modelo e analisando visualmente os movimentos do exoesqueleto em Simulink. Os dados para simulação da marcha humana são extraídos de uma base de dados existente e adaptados para fazer simulações nos modelos de sistema de controle do exoesqueleto.In this research a model of an exoskeleton of the right lower limb for user mobility enhancement and its control system are designed. The exoskeleton design consists of three major parts: a hip, an upper leg and a lower leg part, connected to one another with revolute joints. The joints will each be actuated by Brushless DC (BLDC) Motors equipped with gearboxes to increase torque. The motors are also equipped with velocity and position sensors which provide the necessary data for the designed control systems. Solidworks Computer Aided Design (CAD) software is used to develop a model of the exoskeleton which is then exported in extensible markup language (XML) format to be imported in Simmechanics, enabling the integration of physical body components with Simulink components. The inverse kinematics of the exoskeleton model is calculated and designed in Very high speed integrated circuit Hardware Description Language (VHDL) using floating-point numbers, to be executed from a Field Programmable Gate Array (FPGA) Device. Four different bit width representations of the hardware design of the kinematics model of the exoskeleton are developed, performing error analysis with the Mean Square Error (MSE) and the Average Relative Error (ARE) approaches. Trade-off analysis is then performed against performance and area on FPGA. The Proportional-Integrative-Derivative (PID) control strategy is chosen to develop the control system for the exoskeleton for its relatively simple design and proven efficient implementation in a very broad range of real life application areas. Two control system strategies are developed and compared to one another. Each control system design is comprised of two velocity- and two position controllers. PID parameters are calculated using the Ziegler-Nichols method and Particle Swarm Optimization (PSO). PSO is a relatively simple yet powerful optimization method that is applied in many optimization problem areas. It is based on the seemingly intelligent behaviour of fish schools and bird flocks in search of food. The algorithm, alongside the Ziegler-Nichols method, is used to find suitable PID parameters for control system blocks in the two designs. The system response of the control systems is evaluated analyzing step response. Human gait simulation is also performed on the developed exoskeleton control systems by observing the exoskeleton model movements in Simulink. The gait simulation data is extracted from a human gait database and adapted to be fed as input to the exoskeleton control system models

Adaptive control for wearable robots in human-centered rehabilitation tasks

Robotic rehabilitation therapies have been improving by providing the needed assistance to the patient, in a human-centered environment, and also helping the therapist to choose the necessary procedure. This thesis presents an adaptive "Assistance-as-needed" strategy which adheres to the specific needs of the patient and with the inputs from the therapist, whenever needed. The exertion of assistive and responsive behavior of the lower limb wearable robot is dedicated for the rehabilitation of incomplete spinal cord injury (SCI) patients. The main objective is to propose and evaluate an adaptive control model on a wearable robot, assisting the user and adhering to their needs, with no or less combination of external devices. The adaptation must be more interactive to understand the user needs and their volitional orders. Similarly, by using the existing muscular strength, in incomplete SCI patients, as a motivation to pursue the movement and assist them, only when needed. The adaptive behavior of the wearable robot is proposed by monitoring the interaction and movement of the user. This adaptation is achieved by modulating the stiffness of the exoskeleton in function of joint parameters, such as positions and interaction torques. These joint parameters are measured from the user independently and then used to update the new stiffness value. The adaptive algorithm performs with no need of external sensors, making it simple in terms of usage. In terms of rehabilitation, it is also desirable to be compatible with combination of assistive devices such as muscle stimulation, neural activity (BMI) and body balance (Wii), to deliver a user friendly and effective therapy. Combination of two control approaches has been employed, to improve the efficiency of the adaptive control model and was evaluated using a wearable lower limb exoskeleton device, H1. The control approaches, Hierarchical and Task based approach have been used to assist the patient as needed and simultaneously motivate the patient to pursue the therapy. Hierarchical approach facilitates combination of multiple devices to deliver an effective therapy by categorizing the control architecture in two layers, Low level and High level control. Task-based approaches engage in each task individually and allow the possibility to combine them at any point of time. It is also necessary to provide an interaction based approach to ensure the complete involvement of the user and for an effective therapy. By means of this dissertation, a task based adaptive control is proposed, in function of human-orthosis interaction, which is applied on a hierarchical control scheme. This control scheme is employed in a wearable robot, with the intention to be applied or accommodated to different pathologies, with its adaptive capabilities. The adaptive control model for gait assistance provides a comprehensive solution through a single implementation: Adaptation inside a gait cycle, continuous support through gait training and in real time. The performance of this control model has been evaluated with healthy subjects, as a preliminary study, and with paraplegic patients. Results of the healthy subjects showed a significant change in the pattern of the interaction torques, elucidating a change in the effort and adaptation to the user movement. In case of patients, the adaptation showed a significant improvement in the joint performance (flexion/extension range) and change in interaction torques. The change in interaction torques (positive to negative) reflects the active participation of the patient, which also explained the adaptive performance. The patients also reported that the movement of the exoskeleton is flexible and the walking patterns were similar to their own distinct patterns. The presented work is performed as part of the project HYPER, funded by Ministerio de Ciencia y Innovación, Spain. (CSD2009 - 00067 CONSOLIDER INGENIOLas terapias de rehabilitación robóticas han sido mejoradas gracias a la inclusión de la asistencia bajo demanda, adaptada a las variaciones de las necesidades del paciente, así como a la inclusión de la ayuda al terapeuta en la elección del procedimiento necesario. Esta tesis presenta una estrategia adaptativa de asistencia bajo demanda, la cual se ajusta a las necesidades específicas del paciente junto a las aportaciones del terapeuta siempre que sea necesario. El esfuerzo del comportamiento asistencial y receptivo del robot personal portátil para extremidades inferiores está dedicado a la rehabilitación de pacientes con lesión de la médula espinal (LME) incompleta. El objetivo principal es proponer y evaluar un modelo de control adaptativo en un robot portátil, ayudando al usuario y cumpliendo con sus necesidades, en ausencia o con reducción de dispositivos externos. La adaptación debe ser más interactiva para entender las necesidades del usuario y sus intenciones u órdenes volitivas. De modo similar, usando la fuerza muscular existente (en pacientes con LME incompleta) como motivación para lograr el movimiento y asistirles solo cuando sea necesario. El comportamiento adaptativo del robot portátil se propone mediante la monitorización de la interacción y movimiento del usuario. Esta adaptación conjunta se consigue modulando la rigidez en función de los parámetros de la articulación, tales como posiciones y pares de torsión. Dichos parámetros se miden del usuario de forma independiente y posteriormente se usan para actualizar el nuevo valor de la rigidez. El desempeño del algoritmo adaptativo no requiere de sensores externos, lo que favorece la simplicidad de su uso. Para una adecuada rehabilitación, efectiva y accesible para el usuario, es necesaria la compatibilidad con diversos mecanismos de asistencia tales como estimulación muscular, actividad neuronal y equilibrio corporal. Para mejorar la eficiencia del modelo de control adaptativo se ha empleado una combinación de dos enfoques de control, y para su evaluación se ha utilizado un exoesqueleto robótico H1. Los enfoques de control Jerárquico y de Tarea se han utilizado para ayudar al usuario según sea necesario, y al mismo tiempo motivarle para continuar el tratamiento. Enfoque jerárquico facilita la combinación de múltiples dispositivos para ofrecer un tratamiento eficaz mediante la categorización de la arquitectura de control en dos niveles : el control de bajo nivel y de alto nivel. Los enfoques basados en tareas involucran a la persona en cada tarea individual, y ofrecen la posibilidad de combinarlas en cualquier momento. También es necesario proporcionar un enfoque basado en la interacción con el usuario, para asegurar su participación y lograr así una terapia eficaz. Mediante esta tesis, proponemos un control adaptativo basado en tareas y en función de la interacción persona-ortesis, que se aplica en un esquema de control jerárquico. Este esquema de control se emplea en un robot portátil, con la intención de ser aplicado o acomodado a diferentes patologías, con sus capacidades de adaptación. El modelo de control adaptativo propuesto proporciona una solución integral a través de una única aplicación: adaptación dentro de la marcha y apoyo continúo a través de ejercicios de movilidad en tiempo real. El rendimiento del modelo se ha evaluado en sujetos sanos según un estudio preliminar, y posteriormente también en pacientes parapléjicos. Los resultados en sujetos sanos mostraron un cambio significativo en el patrón de los pares de interacción, elucidando un cambio en la energía y la adaptación al movimiento del usuario. En el caso de los pacientes, la adaptación mostró una mejora significativa en la actuación conjunta (rango de flexión / extensión) y el cambio en pares de interacción. El cambio activo en pares de interacción (positivo a negativo) refleja la participación activa del paciente, lo que también explica el comportamiento adaptativo

Advanced Knowledge Application in Practice

The integration and interdependency of the world economy leads towards the creation of a global market that offers more opportunities, but is also more complex and competitive than ever before. Therefore widespread research activity is necessary if one is to remain successful on the market. This book is the result of research and development activities from a number of researchers worldwide, covering concrete fields of research

Fused mechanomyography and inertial measurement for human-robot interface

Human-Machine Interfaces (HMI) are the technology through which we interact with the ever-increasing quantity of smart devices surrounding us. The fundamental goal of an HMI is to facilitate robot control through uniting a human operator as the supervisor with a machine as the task executor. Sensors, actuators, and onboard intelligence have not reached the point where robotic manipulators may function with complete autonomy and therefore some form of HMI is still necessary in unstructured environments. These may include environments where direct human action is undesirable or infeasible, and situations where a robot must assist and/or interface with people. Contemporary literature has introduced concepts such as body-worn mechanical devices, instrumented gloves, inertial or electromagnetic motion tracking sensors on the arms, head, or legs, electroencephalographic (EEG) brain activity sensors, electromyographic (EMG) muscular activity sensors and camera-based (vision) interfaces to recognize hand gestures and/or track arm motions for assessment of operator intent and generation of robotic control signals. While these developments offer a wealth of future potential their utility has been largely restricted to laboratory demonstrations in controlled environments due to issues such as lack of portability and robustness and an inability to extract operator intent for both arm and hand motion. Wearable physiological sensors hold particular promise for capture of human intent/command. EMG-based gesture recognition systems in particular have received significant attention in recent literature. As wearable pervasive devices, they offer benefits over camera or physical input systems in that they neither inhibit the user physically nor constrain the user to a location where the sensors are deployed. Despite these benefits, EMG alone has yet to demonstrate the capacity to recognize both gross movement (e.g. arm motion) and finer grasping (e.g. hand movement). As such, many researchers have proposed fusing muscle activity (EMG) and motion tracking e.g. (inertial measurement) to combine arm motion and grasp intent as HMI input for manipulator control. However, such work has arguably reached a plateau since EMG suffers from interference from environmental factors which cause signal degradation over time, demands an electrical connection with the skin, and has not demonstrated the capacity to function out of controlled environments for long periods of time. This thesis proposes a new form of gesture-based interface utilising a novel combination of inertial measurement units (IMUs) and mechanomyography sensors (MMGs). The modular system permits numerous configurations of IMU to derive body kinematics in real-time and uses this to convert arm movements into control signals. Additionally, bands containing six mechanomyography sensors were used to observe muscular contractions in the forearm which are generated using specific hand motions. This combination of continuous and discrete control signals allows a large variety of smart devices to be controlled. Several methods of pattern recognition were implemented to provide accurate decoding of the mechanomyographic information, including Linear Discriminant Analysis and Support Vector Machines. Based on these techniques, accuracies of 94.5% and 94.6% respectively were achieved for 12 gesture classification. In real-time tests, accuracies of 95.6% were achieved in 5 gesture classification. It has previously been noted that MMG sensors are susceptible to motion induced interference. The thesis also established that arm pose also changes the measured signal. This thesis introduces a new method of fusing of IMU and MMG to provide a classification that is robust to both of these sources of interference. Additionally, an improvement in orientation estimation, and a new orientation estimation algorithm are proposed. These improvements to the robustness of the system provide the first solution that is able to reliably track both motion and muscle activity for extended periods of time for HMI outside a clinical environment. Application in robot teleoperation in both real-world and virtual environments were explored. With multiple degrees of freedom, robot teleoperation provides an ideal test platform for HMI devices, since it requires a combination of continuous and discrete control signals. The field of prosthetics also represents a unique challenge for HMI applications. In an ideal situation, the sensor suite should be capable of detecting the muscular activity in the residual limb which is naturally indicative of intent to perform a specific hand pose and trigger this post in the prosthetic device. Dynamic environmental conditions within a socket such as skin impedance have delayed the translation of gesture control systems into prosthetic devices, however mechanomyography sensors are unaffected by such issues. There is huge potential for a system like this to be utilised as a controller as ubiquitous computing systems become more prevalent, and as the desire for a simple, universal interface increases. Such systems have the potential to impact significantly on the quality of life of prosthetic users and others.Open Acces