A new approach on human-robot collaboration with humanoid robot RH-2

This paper was originally submitted under the auspices of the CLAWAR Association. It is an extension of work presented at CLAWAR 2009: The 12th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines, Istanbul, Turkey.This paper presents a novel control architecture for humanoid robot RH-2. The main objective is that a robot can perform different tasks in collaboration with humans in working environments. In order to achieve this goal, two control loops have to be defined. The outer loop, called collaborative control loop, is devoted to the generation of stable motion patterns for a robot, given a specific manipulation task. The inner loop, called posture stability control loop, acts to guarantee the stability of humanoid for different poses determined by motion patterns. A case study is presented in order to show the effectiveness of the proposed control architecture.This work has been supported by the CAM Project S2009/DPI-1559/ROBOCITY2030 II, the CYCIT Project PI2004-00325 and the European Project Robot@CWE FP6-2005-IST-5

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

Automatic selection of ergonomic indicators for the design of collaborative robots: a virtual-human in the loop approach

Conference of 2014 14th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2014 ; Conference Date: 18 November 2014 Through 20 November 2014; Conference Code:112990International audienceThe growing number of musculoskeletal disorders in industry could be addressed by the use of collaborative robots, which allow the joint manipulation of objects by both a robot and a person. Designing these robots requires to assess the ergonomic benefit they offer. However there is a lack of adapted assessment methods in the literature. Many biomechanical quantities can represent the physical solicitations to which the worker is exposed, but their relevance strongly depends on the considered task. This paper presents a method to automatically select relevant ergonomic indicators for a given task to be performed with a collaborative robot. A virtual human simulation is used to estimate thirty indicators for varying human and robot features. A variance-based analysis is then conducted to extract the most discriminating indicators. The method is validated on several different tasks. The relevance of the proposed approach is confirmed by the obtained results

Becoming Human with Humanoid

Nowadays, our expectations of robots have been significantly increases. The robot, which was initially only doing simple jobs, is now expected to be smarter and more dynamic. People want a robot that resembles a human (humanoid) has and has emotional intelligence that can perform action-reaction interactions. This book consists of two sections. The first section focuses on emotional intelligence, while the second section discusses the control of robotics. The contents of the book reveal the outcomes of research conducted by scholars in robotics fields to accommodate needs of society and industry

Enabling Human-Robot Collaboration via Holistic Human Perception and Partner-Aware Control

As robotic technology advances, the barriers to the coexistence of humans and robots are slowly coming down. Application domains like elderly care, collaborative manufacturing, collaborative manipulation, etc., are considered the need of the hour, and progress in robotics holds the potential to address many societal challenges. The future socio-technical systems constitute of blended workforce with a symbiotic relationship between human and robot partners working collaboratively. This thesis attempts to address some of the research challenges in enabling human-robot collaboration. In particular, the challenge of a holistic perception of a human partner to continuously communicate his intentions and needs in real-time to a robot partner is crucial for the successful realization of a collaborative task. Towards that end, we present a holistic human perception framework for real-time monitoring of whole-body human motion and dynamics. On the other hand, the challenge of leveraging assistance from a human partner will lead to improved human-robot collaboration. In this direction, we attempt at methodically defining what constitutes assistance from a human partner and propose partner-aware robot control strategies to endow robots with the capacity to meaningfully engage in a collaborative task

Stable locomotion of humanoid robots based on mass concentrated model

El estudio de la locomoción de robots humanoides es actualmente un área muy activa, en el campo de la robótica. Partiendo del principio que el hombre esta construyendo robots para trabajar juntos cooperando en ambientes humanos. La estabilidad durante la caminata es un factor crítico que prevee la caída del robot, la cual puede causar deterioros al mismo y a las personas en su entorno. De esta manera, el presente trabajo pretende resolver una parte del problema de la locomoción bípeda, esto es los métodos empleados para “La generación del paso” (“Gait generation”) y asi obtener la caminata estable. Para obtener una marcha estable se utilizan modelos de masa concentrada. De esta manera el modelo del “pendulo invertido simple” y el modelo del “carro sobre la mesa” se han utilizado para conseguir la marcha estable de robots humanoides. En el modelo del pendulo invertido, la masa el pendulo conduce el movimiento del centro de gravedad (CDG) del robot humanoide durante la marcha. Se detallara que el CDG se mueve como una bola libre sobre un plano bajo las leyes del pendulo en el campo de gravedad. Mientras que en el modelo del “carro sobre la mesa”, el carro conduce el movimiento del CDG durante la marcha. En este caso, el movimiento del carro es tratado como un sistema servocontrolado, y el movimiento del CDG es obtenido con los actuales y futuros estados de referencia del Zero Moment Point (ZMP). El método para generar el paso propuesto esta compuesto de varias capas como son Movimiento global, movimiento local, generación de patrones de movimiento, cinemática inversa y dinámica inversa y finalmente una corrección off-line. Donde la entrada en este método es la meta global (es decir la configuración final del robot, en el entorno de marcha) y las salidas son los patrones de movimiento de las articulaciones junto con el patrón de referencia del ZMP. Por otro lado, se ha propuesto el método para generar el “Paso acíclico”. Este método abarca el movimiento del paso dinámico incluyendo todo el cuerpo del robot humanoide, desde desde cuaquier postura genérica estáticamente estable hasta otra; donde las entradas son los estados inicial y final del robot (esto es los ángulos iniciales y finales de las articulaciones) y las salidas son las trayectorias de referencia de cada articulación y del ZMP. Se han obtenido resultados satisfactorios en las simulaciones y en el robot humanoide real Rh-1 desarrollado en el Robotics lab de la Universidad Carlos III de Madrid. De igual manera el movimiento innovador llamado “Paso acíclico” se ha implemenado exitosamente en el robot humanoide HRP-2 (desarrollado por el AIST e Industrias Kawada Inc., Japon). Finalmente los resultados, contribuciones y trabajos futuros se expondran y discutirán. _______________________________________________The study of humanoid robot locomotion is currently a very active area in robotics, since humans build robots to work their environments in common cooperation and in harmony. Stability during walking motion is a critical fact in preventing the robot from falling down and causing the human or itself damages. This work tries to solve a part of the locomotion problem, which is, the “Gait Generation” methods used to obtain stable walking. Mass concentrated models are used to obtain stable walking motion. Thus the inverted pendulum model and the cart-table model are used to obtain stable walking motion in humanoid robots. In the inverted pendulum model, the mass of the pendulum drives the center of gravity (COG) motion of the humanoid robot while it is walking. It will be detailed that the COG moves like a free ball on a plane under the laws of the pendulum in the field of gravity. While in the cart-table model, the cart drives the COG motion during walking motion. In this case, the cart motion is treated as a servo control system, obtaining its motion from future reference states of the ZMP. The gait generation method proposed has many layers like Global motion, local motion, motion patterns generation, inverse kinematics and inverse dynamics and finally off-line correction. When the input in the gait generation method is the global goal (that is the final configuration of the robot in walking environment), and the output is the joint patterns and ZMP reference patterns. Otherwise, the “Acyclic gait” method is proposed. This method deals with the whole body humanoid robot dynamic step motion from any generic posture to another one when the input is the initial and goal robot states (that is the initial and goal joint angles) and the output is the joint and ZMP reference patterns. Successful simulation and actual results have been obtained with the Rh- 1 humanoid robot developed in the Robotics lab (Universidad Carlos III de Madrid, Spain) and the innovative motion called “Acyclic gait” implemented in the HRP-2 humanoid robot platform (developed by the AIST and Kawada Industries Inc., Japan). Furthermore, the results, contributions and future works will be discussed

Stabilizer architecture for humanoid robots collaborating with humans

Hoy en día, los avances en las tecnologías de información y comunicación permiten el uso de robots como compañeros en las actividades con los seres humanos. Mientras que la mayoría de las investigaciones existentes se dedica a la interacción entre humanos y robots, el marco de esta investigación está centrado en el uso de robots como agentes de colaboración. En particular, este estudio está dedicado a los robots humanoides que puedan ayudar a la gente en varias tareas en entornos de trabajo. Los robots humanoides son sin duda los m as adecuados para este tipo de situaciones: pueden usar las mismas herramientas que los seres humanos y son lo m as probablemente aceptados por ellos. Después de explicar las ventajas de las tareas de colaboración entre los humanos y los robots y las diferencias con respecto a los sistemas de interacción y de teleoperación, este trabajo se centra en el nivel de las tecnologías que es necesario para lograr ese objetivo. El problema más complicado en el control de humanoides es el balance de la estructura. Este estudio se centra en técnicas novedosas para la estimación de la actitud del robot, que se utilizarán para el control. El control del robot se basa en un modelo muy conocido y simplificado: el péndulo invertido. Este modelo permite tener un control en tiempo real sobre la estructura, mientras que esté sometida a fuerzas externas / disturbios. Trayectorias suaves para el control de humanoides se han propuesto y probado en plataformas reales: éstos permiten reducir los impactos del robot con su entorno. Finalmente, el estudio extiende estos resultados a una contribución para la arquitectura de colaboración humano-humanoide. Dos tipos de colaboraciones humano humanoide se analizan: la colaboración física, donde robots y humanos comparten el mismo espacio y tienen un contacto físico (o por medio de un objeto), y una colaboración a distancia, en la que el ser humano está relativamente lejos del robot y los dos agentes colaboran por medio de una interfaz. El paradigma básico de esta colaboración robótica es: lo que es difícil (o peligroso) para el ser humano se hace por medio del robot y lo que es difícil para el robot lo puede mejor hacer el humano. Es importante destacar que el contexto de los experimentos no se basa en una unica plataforma humanoide; por el contrario, tres plataformas han sido objeto de los experimentos: se han empleado los robots HOAP-3, HRP-2 y TEO. ----------------------------------------------------------------------------------------------------------------------------------------------------------Nowadays, the advances in information and communication technologies permit the use of robots as companions in activities with humans. While most of the existing research is dedicated to the interaction between humans and robots, the framework of this research is the use of robots as collaborative agents. In particular, this study is dedicated to humanoid robots which should assist people in several tasks in working environments. Humanoid robots are certainly the most adequate for such situations: they can use the same tools as humans and are most likely accepted by them. After explaining the advantages of collaborative tasks among humans and robots and the differences with respect to interaction and teleoperation systems, this work focuses on the level of technologies which is necessary in order to achieve such a goal. The most complicated problem in humanoid control is the structure balance. This study focuses in novel techniques in the attitude estimation of the robot, to be used for the control. The control of the robot is based on a very well-known and simplified model: the double inverted pendulum. This model permits having a real-time control on the structure while submitted to external forces/disturbances. The control actions are strongly dependent on the three stability regions, which are determined by the position of the ZMP in the support polygon. Smooth trajectories for the humanoid control have been proposed and tested on real platforms: these permit reducing the impacts of the robot with its environment. Finally, the study extends these results to a contribution for human-humanoid collaboration architecture. Two types of human-humanoid collaborations are analyzed: a physical collaboration, where robot and human share the same space and have a physical contact (or by means of an object), and a remote collaboration, in which the human is relatively far away from the robot and the two agents collaborate using an interface. The basic paradigm for this robotic collaboration is: what is difficult (or dangerous) for the human is done by the robot and what is difficult for the robot is better done by the human. Importantly, the testing context is not based on a single humanoid platform; on the contrary, three platforms have been object of the experiments: the Hoap-3, HRP-2 and HRP2 robot have been employed

Humanoid robot control of complex postural tasks based on learning from demostration

Mención Internacional en el título de doctorThis thesis addresses the problem of planning and controlling complex tasks in a humanoid robot from a postural point of view. It is motivated by the growth of robotics in our current society, where simple robots are being integrated. Its objective is to make an advancement in the development of complex behaviors in humanoid robots, in order to allow them to share our environment in the future. The work presents different contributions in the areas of humanoid robot postural control, behavior planning, non-linear control, learning from demonstration and reinforcement learning. First, as an introduction of the thesis, a group of methods and mathematical formulations are presented, describing concepts such as humanoid robot modelling, generation of locomotion trajectories and generation of whole-body trajectories. Next, the process of human learning is studied in order to develop a novel method of postural task transference between a human and a robot. It uses the demonstrated action goal as a metrics of comparison, which is codified using the reward associated to the task execution. As an evolution of the previous study, this process is generalized to a set of sequential behaviors, which are executed by the robot based on human demonstrations. Afterwards, the execution of postural movements using a robust control approach is proposed. This method allows to control the desired trajectory even with mismatches in the robot model. Finally, an architecture that encompasses all methods of postural planning and control is presented. It is complemented by an environment recognition module that identifies the free space in order to perform path planning and generate safe movements for the robot. The experimental justification of this thesis was developed using the humanoid robot HOAP-3. Tasks such as walking, standing up from a chair, dancing or opening a door have been implemented using the techniques proposed in this work.Esta tesis aborda el problema de la planificación y control de tareas complejas de un robot humanoide desde el punto de vista postural. Viene motivada por el auge de la robótica en la sociedad actual, donde ya se están incorporando robots sencillos y su objetivo es avanzar en el desarrollo de comportamientos complejos en robots humanoides, para que en el futuro sean capaces de compartir nuestro entorno. El trabajo presenta diferentes contribuciones en las áreas de control postural de robots humanoides, planificación de comportamientos, control no lineal, aprendizaje por demostración y aprendizaje por refuerzo. En primer lugar se desarrollan un conjunto de métodos y formulaciones matemáticas sobre los que se sustenta la tesis, describiendo conceptos de modelado de robots humanoides, generación de trayectorias de locomoción y generación de trayectorias del cuerpo completo. A continuación se estudia el proceso de aprendizaje humano, para desarrollar un novedoso método de transferencia de una tarea postural de un humano a un robot, usando como métrica de comparación el objetivo de la acción demostrada, que es codificada a través del refuerzo asociado a la ejecución de dicha tarea. Como evolución del trabajo anterior, se generaliza este proceso para la realización de un conjunto de comportamientos secuenciales, que son de nuevo realizados por el robot basándose en las demostraciones de un ser humano. Seguidamente se estudia la ejecución de movimientos posturales utilizando un método de control robusto ante imprecisiones en el modelado del robot. Para analizar, se presenta una arquitectura que aglutina los métodos de planificación y el control postural desarrollados en los capítulos anteriores. Esto se complementa con un módulo de reconocimiento del entorno y extracción del espacio libre para poder planificar y generar movimientos seguros en dicho entorno. La justificación experimental de la tesis se ha desarrollado con el robot humanoide HOAP-3. En este robot se han implementado tareas como caminar, levantarse de una silla, bailar o abrir una puerta. Todo ello haciendo uso de las técnicas propuestas en este trabajo.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Manuel Ángel Armada Rodríguez.- Secretario: Luis Santiago Garrido Bullón.- Vocal: Sylvain Calino

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