Human inspired humanoid robots control architecture

This PhD Thesis tries to present a different point of view when talking about the development of control architectures for humanoid robots. Specifically, this Thesis is focused on studying the human postural control system as well as on the use of this knowledge to develop a novel architecture for postural control in humanoid robots. The research carried on in this thesis shows that there are two types of components for postural control: a reactive one, and other predictive or anticipatory. This work has focused on the development of the second component through the implementation of a predictive system complementing the reactive one. The anticipative control system has been analysed in the human case and it has been extrapolated to the architecture for controlling the humanoid robot TEO. In this way, its different components have been developed based on how humans work without forgetting the tasks it has been designed for. This control system is based on the composition of sensorial perceptions, the evaluation of stimulus through the use of the psychophysics theory of the surprise, and the creation of events that can be used for activating some reaction strategies (synergies) The control system developed in this Thesis, as well as the human being does, processes information coming from different sensorial sources. It also composes the named perceptions, which depend on the type of task the postural control acts over. The value of those perceptions is obtained using bio-inspired evaluation techniques of sensorial inference. Once the sensorial input has been obtained, it is necessary to process it in order to foresee possible disturbances that may provoke an incorrect performance of a task. The system developed in this Thesis evaluates the sensorial information, previously transformed into perceptions, through the use of the “Surprise Theory”, and it generates some events called “surprises” used for predicting the evolution of a task. Finally, the anticipative system for postural control can compose, if necessary, the proper reactions through the use of predefined movement patterns called synergies. Those reactions can complement or substitute completely the normal performance of a task. The performance of the anticipative system for postural control as well as the performance of each one of its components have been tested through simulations and the application of the results in the humanoid robot TEO from the RoboticsLab research group in the Systems Engineering and Automation Department from the Carlos III University of Madrid. ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Esta Tesis Doctoral pretende aportar un punto de vista diferente en el desarrollo de arquitecturas de control para robots humanoides. En concreto, esta Tesis se centra en el estudio del sistema de control postural humano y en la aplicación de este conocimiento en el desarrollo de una nueva arquitectura de control postural para robots humanoides. El estudio realizado en esta Tesis pone de manifiesto la existencia de una componente de control postural reactiva y otra predictiva o anticipativa. Este trabajo se ha centrado en el desarrollo de la segunda componente mediante la implementación de un sistema predictivo que complemente al sistema reactivo. El sistema de control anticipativo ha sido estudiado en el caso humano y extrapolado para la arquitectura de control del robot humanoide TEO. De este modo, sus diferentes componentes han sido desarrollados inspirándose en el funcionamiento humano y considerando las tareas para las que dicho robot ha sido concebido. Dicho sistema está basado en la composición de percepciones sensoriales, la evaluación de los estímulos mediante el uso de la teoría psicofísica de la sorpresa y la generación de eventos que sirvan para activar estrategias de reacción (sinergias). El sistema de control desarrollado en esta Tesis, al igual que el ser humano, procesa información de múltiples fuentes sensoriales y compone las denominadas percepciones, que dependen del tipo de tarea sobre la que actúa el control postural. El valor de estas percepciones es obtenido utilizando técnicas de evaluación bioinspiradas de inferencia sensorial. Una vez la entrada sensorial ha sido obtenida, es necesario procesarla para prever posibles perturbaciones que puedan ocasionar una incorrecta realización de una tarea. El sistema desarrollado en esta Tesis evalúa la información sensorial, previamente transformada en percepciones, mediante la ‘Teoría de la Sorpresa’ y genera eventos llamados ‘sorpresas’ que sirven para predecir la evolución de una tarea. Por último, el sistema anticipativo de control postural puede componer, si fuese necesario, las reacciones adecuadas mediante el uso de patrones de movimientos predefinidos llamados sinergias. Dichas reacciones pueden complementar o sustituir por completo la ejecución normal de una tarea. El funcionamiento del sistema anticipativo de control postural y de cada uno de sus componentes ha sido probado tanto por medio de simulaciones como por su aplicación en el robot humanoide TEO del grupo de investigación RoboticsLab en el Departamento de Ingeniería de Sistemas y Automática de la Universidad Carlos III de Madrid

Humanoids. Los humanos y los robots cara a cara

Contiene: Entrevista con Santiago Martínez de la Casa, Investigador del Laboratorio de Robótica de la UC3M.-- Entrevista con Concepción Alicia Monje Micharet, Investigadora Laboratorio de Robótica de la UC3M.-- Entrevista con Alberto Jardón Huete, Investigador Laboratorio de Robótica de la UC3M

Experience acquisition simulator for operating microtuneling boring machines

This paper describes an innovative modeling, interfacing and training framework and application for microtunneling machines under heterogeneous gravel and sand soils, based on a machine simulator. It is initialized using a selective collection of skilled pilots' know-how during the performance of a pipe jacking microtunneling machine operation, generating a rule-based system based on grouped rules and states that replicate the machine's performance. The adjustment of these states and associated rules allows the creation, setup and analysis of a realistic functional model for tunneling machines. The developed system integrates a friendly Human-Machine Interface (HMI) that closely resembles real machines' pilot cabinets and allows natural interaction with the implemented inference engine through the simulated control panel. Additionally, the framework allows the training of tunneling machine operators by simulation and subsequent gathered data analysis, obviating or reducing mechanical movement times if desired. The virtual pilot's desk allows global training time and cost reductions, and increases safety for future operatorsand machinery. The HMI is divided into two screens, which replicate the data and the command panels of a real machine's control desk. The presented framework has allowed the first implementation of a jack piping microtunneling machine simulator by means of the developed pilots' steering know-how capture methodology.This work has been funded by the Spanish government under the framework of the Multidimensional City project PSE-380000-2008-5 http://www.laciudadmultidimensional.es, and has received funding from the RoboCity2030-II-CM project (S2009/DPI-1559), funded by Programas de Actividades I+D en la Comunidad de Madrid and cofunded by Structural Funds of the EU

Robot-aided tunnel inspection and maintenance system by vision and proximity sensor integration

This article describes an unprecedented alternative to manual procedures for the application of advanced composite materials, such as Fiber Reinforced Polymer (FRP) and epoxy resins. A complete mobile integrated system is presented for the inspection and maintenance of concrete surfaces in tunnels. It allows performance of operations with minimum interference on passing traffic. The core of this system resides in a specially designed light-weight robotic tool, which is sensed and automated for processes. Sensing includes vision and a laser telemeter to assure precise inspection, superficial preparation, and composite application. The designed interconnection flange allows simple and robust attachment of the tool to a robotic arm's tip. The robot&-tool set is to be mounted on a standard articulated lift platform. Therefore, an operator can direct the platform and the robot&-tool set's operations from a control station placed at ground-level, in a wheeled vehicle on which the articulated lift platform is mounted. A graphical Human&-Machine Interface (HMI) has been developed for the system. It allows the operator to identify fissures for the injection of epoxy resin, and weakened surfaces for FRP adhesion. Actual procedures are planned and performed by the system's automatic components.This work has been supported by the CAM Project S2009/DPI-1559/ROBOCITY2030 II, developed by the research team RoboticsLab at the University Carlos III of Madrid

Flexible field factory for construction industry

Purpose - The paper aims to present the concept, the layout design and the evaluation performed of a flexible field factory for construction industry. Both the concept and layout are focused on flexibility and mobility factors, providing a versatile system for manufacturing and assembly that can be transported to construction sites without need of special permissions. Design/methodology/approach - The design is based on the design for manufacture and assembly (DFMA) principles, lean manufacturing, and construction industry experts' knowledge. Findings - The developed factory layout is dimensioned to fit in a standard 20-feet-long container. Simulation processes have been run to verify the viability of the system. The time estimates calculated in the simulations are compared with traditional in and off-site construction method estimates, providing quantified cost and time benefits. Originality/value - This paper presents the concept of the robotized field factory designed for on-site prefabrication, the design of which began during the EU 6FP ManuBuild Project. This reconfigurable and flexible system is oriented to the production of small and medium size modular systems. The viability of the field factory has been evaluated thanks to the application of a modular system for building installations called Service Core. Its design has been based on DFMA and lean principles as well as the expertise from construction partners from the ManuBuild Project.This work has been funded by the E.U. community under FP6 Project ManuBuild and also supported by CAM project S2009/DPI-1559/ROBOCITY2030 II. The authors would also like to acknowledge the work of the other partners involved in the project: DRAGADOS, and Fraunhofer IAO

Correction of Visual Perception Based on Neuro-Fuzzy Learning for the Humanoid Robot TEO

New applications related to robotic manipulation or transportation tasks, with or without physical grasping, are continuously being developed. To perform these activities, the robot takes advantage of different kinds of perceptions. One of the key perceptions in robotics is vision. However, some problems related to image processing makes the application of visual information within robot control algorithms difficult. Camera-based systems have inherent errors that affect the quality and reliability of the information obtained. The need of correcting image distortion slows down image parameter computing, which decreases performance of control algorithms. In this paper, a new approach to correcting several sources of visual distortions on images in only one computing step is proposed. The goal of this system/algorithm is the computation of the tilt angle of an object transported by a robot, minimizing image inherent errors and increasing computing speed. After capturing the image, the computer system extracts the angle using a Fuzzy filter that corrects at the same time all possible distortions, obtaining the real angle in only one processing step. This filter has been developed by the means of Neuro-Fuzzy learning techniques, using datasets with information obtained from real experiments. In this way, the computing time has been decreased and the performance of the application has been improved. The resulting algorithm has been tried out experimentally in robot transportation tasks in the humanoid robot TEO (Task Environment Operator) from the University Carlos III of Madrid.The research leading to these results has received funding from the RoboCity2030-III-CM project (Robótica aplicada a la mejora de la calidad de vida de los ciudadanos. fase III; S2013/MIT-2748), funded by Programas de Actividades I + D en la Comunidad de Madrid and cofunded by Structural Funds of the EU

Basic principles for the development of an application to bi-manipulate boxes with a humanoid robot

La logística es un sector que está en continuo crecimiento, debido tanto a la globalización, como a la actual situación creada por el Covid. En este artículose describe una aplicación para reconocer cajas, extrayendo sus características con el fin de identificar la cara de apertura por medio de un sistema de visión por computador. Este objetivo se ha conseguido teniendo en cuenta las dimensiones y la posición en el espacio de la misma, logrando estas características a través de técnicas de procesamiento de imagen en 2D y en 3D. Posteriormente, la información correspondiente a las caras de la caja es clasificada con un árbol de decisiones, obteniendo así la probabilidad de que cada una de las seis caras sea la de apertura. Este artículo sirve para establecer las bases para desarrollar en unfuturo una aplicación en la que el robot humanoide TEO mediante aprendizaje encuentre la forma más óptima de bimanipular cajas y abrirlas, integrando este conocimiento en un sistema automatizado.Logistics is a sector which is continuouslygrowing, due to globalization, as well as the current situation caused by the Covid. In this article, an application to recognize boxes is described. The characteristics are extracted with the goal of identify the opening side of the box by using computer vision techniques. This goal has been achieved considering the dimensions, as well as, the positionin the space of the box. Those characteristics were obtained processing 2D and 3D images. Then, this information has been classified by using a decision tree based on the human knowledge. The probability of each of the six faces to be the opening side is obtained. This article is a baseto develop in the future an application in which the humanoid robot TEO is capable to learn the optimal way to find the opening of boxes and bimanipulate them to be opened in an automated system.Este trabajo ha sido realizado parcialmente gracias al apoyo de RoboCity2030-DIH-CM; Madrid Robotics Digital Innovation Hub, S2018/NMT-4331, fundado por "Programas de Actividades I+D en la Comunidad de Madrid" y cofundado por los fondos estructurales de la U

Characterization and study of the primitive dynamic movements required to bi-manipulate a box

Automating the action of finding the opening side of a box is not possible if the robot is not capable of reaching and evaluating all of its sides. To achieve this goal, in this paper, three different movement strategies to bi-manipulate a box are studied: overturning, lifting, and spinning it over a surface. First of all, the dynamics involved in each of the three movement strategies are studied using physics equations. Then, a set of experiments are conducted to determine if the real response of the humanoid robot, TEO, to a box is consistent with the expected answer based on theoretical calculus. After the dynamics validation, the information on the forces and the position in the end effectors is used to characterize these movements and create its primitives. These primitive movements will be used in the future to design a hybrid position–force control in order to adapt the movements to different kinds of boxes. The structure of this control is also presented in this pape

Personal Autonomy Rehabilitation in Home Environments by a Portable Assistive Robot

Increasingly disabled and elderly people with mobility problems want to live autonomously in their home environment. They are motivated to use robotic aids to perform tasks by themselves, avoiding permanent nurse or family assistant supervision. They must find means to rehabilitate their abilities to perform daily life activities (DLAs), such as eating, shaving, or drinking. These means may be provided by robotic aids that incorporate possibilities and methods to accomplish common tasks, aiding the user in recovery of partial or complete autonomy. Results are highly conditioned by the system's usability and potential. The developed portable assistive robot ASIBOT helps users perform most of these tasks in common living environments. Minimum adaptations are needed to provide the robot with mobility throughout the environment. The robot can autonomously climb from one surface to another, fixing itself to the best place to perform each task. When the robot is attached to its wheelchair, it can move along with it as a bundle. This paper presents the work performed with the ASIBOT in the area of rehabilitation robotics. First, a brief description of the ASIBOT system is given. A description of tests that have been performed with the robot and several impaired users is given. Insight into how these experiences have influenced our research efforts, especially, in home environments, is also included. A description of the test bed that has been developed to continue research on performing DLAs by the use of robotic aids, a kitchen environment, is given. Relevant conclusions are also included.This work has been supported by the CAM Project S2009/DPI-1559/ROBOCITY2030 I

TEO robot design powered by a fuel cell system

Versión pre-print (sin revisión por pares) del artículo publicado en Cybernetics and Systems: An International Journal (2012), 43(3), 163-180, accesible en linea: http://dx.doi.org/10.1080/01969722.2012.659977.This is an Author's Original Manuscript (non-peer reviewed) of an article published in Cybernetics and Systems: An International Journal (2012), 43(3), 163-180, available online: http://dx.doi.org/10.1080/01969722.2012.659977.This article deals with the design of the full-size humanoid robot TEO, an improved version of its predecessor Rh-1. The whole platform is conceived under the premise of high efficiency in terms of energy consumption and optimization. We will focus mainly on the electromechanical structure of the lower part of the prototype, which is the main component demanding energy during motion. The dimensions and weight of the robotic platform, together with its link configuration and rigidity, will be optimized. Experimental results are presented to show the validity of the design.The research leading to these results has received funding from the RoboCity2030-II-CM project (S2009/DPI-1559), funded by Programas de Actividades I+D en la Comunidad de Madrid and cofunded by Structural Funds of the EU