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

Virtual reality exposure therapy for social phobia

This thesis presents researches and experiments performed in collaboration with a psychiatrist in order to validate and improve the use of virtual reality in social phobia psychotherapy. Cognitive and behavioral therapies are strongly based on the exposure to anxiety provoking stimuli. Virtual reality seems to be appropriate for such exposures as it allows for on-demand reproduction of reality. The idea has been validated for the treatment of various phobias but is more delicate in the case of social phobia; whereas the sense of presence provoked by the immersion in a virtual environment supports the emergence of fears linked to a location, we had to verify that we can reproduce social phobia related anxiety-provoking stimuli by simulating virtual humans. Therefore, and in order to provide therapists with an efficient virtual reality system dedicated to the exposure to social situations, we have developed software solutions supporting different immersion setups and enabling realistic simulations of inhabited virtual environments. We have experimented with public speaking scenarios within a preliminary study, three clinical case studies and a validation study on 200 subjects. We have been able to confirm that our virtual reality platform fulfilled therapeutic exposure requirements for social phobia. Moreover, we have been able to show that virtual reality exposure has additional advantages such as the possibility to improve clinical assessment with embedded monitoring tools. Our experiments with physiological measurements and eye tracking technology during immersion leaded to the validation of systems for objective and reliable assessment of patients' safety behaviors. The observation of such phobic reactions has confirmed the simulation impact and may provide therapists with enhanced pathological progression monitoring. During our experiments, we have also been able to observe that subjects' reactions during immersion were so much influenced by their sensitivity to fearful stimuli that their cognitive reactions were 'overloaded' by the arousal of anxiety and emotions. This has allowed us to consider that the sense of presence was more importantly related to the subjective impact of the content than to the technological process

Parametric mechanical design and optimisation of the Canterbury Hand.

As part of worldwide research humanoid robots have been developed for household, industrial and exploratory applications. If such robots are to interact with people and human created environments they will require human-like hands. The objective of this thesis was the parametric design and optimisation of a dexterous, and anthropomorphic robotic end effector. Known as the ‘Canterbury Hand’ it has 11 degree of freedoms with four fingers and a thumb. The hand has applications for dexterous teleoperation and object manipulation in industrial, hazardous or uncertain environments such as orbital robotics. The human hand was analysed so that the Canterbury Hand could copy its motions, appearance and grasp types. An analysis of the current literature on experimental prosthetic and robotic hands was also carried out. A disadvantage of many of these hand designs was that they were remotely powered using large, heavy actuator packs. The advantage of the Canterbury Hand is that it has been designed to hold the motors, wires, and circuit boards entirely within itself; although a belt carried battery pack is required. The hand was modelled using a parametric 3D computer aided design (CAD) program. Two different configurations of the hand were created in the model. One configuration, as a dexterous robot hand, used Ø13mm 3 Watt DC motors, while the other used Ø10mm, 0.5 Watt DC motors (although this hand is still slightly too large for a general prosthesis). The parts within the hand were modelled to permit changes to the geometry. This was necessary for the optimisation process. The bearing geometry of the finger and thumb linkages, as well as the thumb rotation axis was optimised for anthropomorphic motion, appearance and increased force output. A design table within a spreadsheet was created to interact with the CAD models of the hand to quickly implement the optimised geometry. The work reported in this thesis has shown the possibilities for parametric design and optimisation of an anthropomorphic, dexterous robotic hand

E-Health: Criminal Liability and Automation

Questo lavoro di ricerca indaga i problemi relativi alla responsabilità penale legata all’uso di sistemi di automazione e d'intelligenza artificiale nel settore dell’e-health. Tale indagine è stata svolta inquadrando il sistema sanitario all’interno di una visione socio-tecnica, con particolare attenzione all’interazione tra uomo e macchina, al livello di automazione dei sistemi e al concetto di errore e gestione del rischio. Sono state approfondite alcune specifiche aree di interesse quali: la responsabilità penale per danno da dispositivi medici difettosi; la responsabilità medica, connessa all’uso di sistemi a elevata automazione e legata a difetti del sistema; e, in particolare, la responsabilità penale legata all’uso di sistemi d’intelligenza artificiale e i modelli elaborati dalla dottrina per regolare tale fenomeno. Sono stati esaminati: il modello zoologico, il modello dell’agente mediato, il modello della conseguenza naturale e probabile e il modello della responsabilità diretta. Si esamina la possibilità che un agente autonomo intelligente sia in grado di soddisfare i requisiti dell’actus reus e della mens rea, quali condizioni necessarie all’attribuzione di responsabilità penale, qualora un AI ponga in essere una condotta astrattamente riconducibile a una fattispecie criminosa. I profili di responsabilità sono analizzati sulla base di casi e scenari e infine si cerca di evidenziare possibili soluzioni e rimedi, anche alla luce della teoria degli agenti normativi.This research thesis investigates all the issues related to the criminal liability that arise when highly automated and/or artificial intelligence systems are used in e-Health. This investigation has been conducted looking at the health system with a socio-technical point of view, paying specific attention to the human-machine interaction, the specific level of automation involved, and finally to concepts of error and risk management. Some topics over the others have been deeply examined, e.g. product liability for defective medical devices; medical liability in case of highly automated systems with defects; criminal liability in presence of artificial intelligence systems, along with the doctrine models developed to cope with these issues. The following models have been analysed: the zoological model, the perpetration through another model, the natural and probable consequences model, and finally the direct liability model. The existence of the criminal requirements, actus reus and mens rea, as mandatory elements to identify the criminal liability, has also been investigated. All the liability profiles have been analysed using real world case and scenarios. Eventually, some solution and remedies have been proposed as a conclusion, using also the theory elements of normative agents

Parametric mechanical design and optimisation of the Canterbury Hand.

As part of worldwide research humanoid robots have been developed for household, industrial and exploratory applications. If such robots are to interact with people and human created environments they will require human-like hands. The objective of this thesis was the parametric design and optimisation of a dexterous, and anthropomorphic robotic end effector. Known as the ‘Canterbury Hand’ it has 11 degree of freedoms with four fingers and a thumb. The hand has applications for dexterous teleoperation and object manipulation in industrial, hazardous or uncertain environments such as orbital robotics. The human hand was analysed so that the Canterbury Hand could copy its motions, appearance and grasp types. An analysis of the current literature on experimental prosthetic and robotic hands was also carried out. A disadvantage of many of these hand designs was that they were remotely powered using large, heavy actuator packs. The advantage of the Canterbury Hand is that it has been designed to hold the motors, wires, and circuit boards entirely within itself; although a belt carried battery pack is required. The hand was modelled using a parametric 3D computer aided design (CAD) program. Two different configurations of the hand were created in the model. One configuration, as a dexterous robot hand, used Ø13mm 3 Watt DC motors, while the other used Ø10mm, 0.5 Watt DC motors (although this hand is still slightly too large for a general prosthesis). The parts within the hand were modelled to permit changes to the geometry. This was necessary for the optimisation process. The bearing geometry of the finger and thumb linkages, as well as the thumb rotation axis was optimised for anthropomorphic motion, appearance and increased force output. A design table within a spreadsheet was created to interact with the CAD models of the hand to quickly implement the optimised geometry. The work reported in this thesis has shown the possibilities for parametric design and optimisation of an anthropomorphic, dexterous robotic hand

Event-triggered Learning

Machine learning has seen many recent breakthroughs. Inspired by these, learningcontrol systems emerged. In essence, the goal is to learn models and control policies for dynamical systems. Dealing with learning-control systems is hard and there are several key challenges that differ from classical machine learning tasks. Conceptually, excitation and exploration play a major role in learning-control systems. On the one hand, we usually aim for controllers that stabilize a system with the goal of avoiding deviations from a setpoint or reference. However, we also need informative data for learning, which is often not the case when controllers work well. Therefore, there is a problem due to the opposing objectives of many control theoretical tasks and the requirements for successful learning outcomes. Additionally, change of dynamics or other conditions is often encountered for control systems in practice. For example, new tasks, changing load conditions, or different external conditions have a substantial influence on the underlying distribution. Learning can provide the flexibility to adapt the behavior of learning-control systems to these events. Since learning has to be applied with sufficient excitation there are many practical situations that hinge on the following problem: "When to trigger learning updates in learning-control systems?" This is the core question of this thesis and despite its relevance, there is no general method that provides an answer. We propose and develop a new paradigm for principled decision making on when to learn, which we call event-triggered learning (ETL). The first triggers that we discuss are designed for networked control systems. All agents use model-based predictions to anticipate the other agents’ behavior which makes communication only necessary when the predictions deviate too much. Essentially, an accurate model can save communication, while a poor model leads to poor predictions and thus frequent updates. The learning triggers are based on the inter-communication times (the time between two communication instances). They are independent and identically distributed random variables, which directly leads to sound guarantees. The framework is validated in experiments and leads to 70% communication savings for wireless sensor networks that monitor human walking. In the second part, we consider optimal control algorithms and start with linear quadratic regulators. A perfect model yields the best possible controller, while poor models result in poor controllers. Thus, by analyzing the control performance, we can infer the model’s accuracy. From a technical point of view, we have to deal with correlated data and work with more sophisticated tools to provide the desired theoretical guarantees. While we obtain a powerful test that is tightly tailored to the problem at hand, it does not generalize to different control architectures. Therefore, we also consider a more general point of view, where we recast the learning of linear systems as a filtering problem. We leverage Kalman filter-based techniques to derive a sound test and utilize the point estimate of the parameters for targeted learning experiments. The algorithm is independent of the underlying control architecture, but demonstrated for model predictive control. Most of the results in the first two parts critically depend on linearity assumptions in the dynamics and further problem-specific properties. In the third part, we take a step back and ask the fundamental question of how to compare (nonlinear) dynamical systems directly from state data. We propose a kernel two-sample test that compares stationary distributions of dynamical systems. Additionally, we introduce a new type of mixing that can directly be estimated from data to deal with the autocorrelations. In summary, this thesis introduces a new paradigm for deciding when to trigger updates in learning-control systems. Additionally, we develop three instantiations of this paradigm for different learning-control problems. Further, we present applications of the algorithms that yield substantial communication savings, effective controller updates, and the detection of anomalies in human walking data

Bin-picking de precisão usando um sensor 3D e um sensor laser 1D

The technique that is being used by a robot to grab objects that are randomly placed inside a box or on a pallet is called bin-picking. This process is of great interest in an industrial environment as it provides enhanced automation, increased production and cost reduction. Bin-picking has evolved greatly over the years due to tremendous strides empowered by advanced vision technology, software, and gripping solutions which are in constant development. However, the creation of a versatile system, capable of collecting any type of object without deforming it, regardless of the disordered environment around it, remains a challenge. To this goal, the use of 3D perception is unavoidable. Still, the information acquired by some lower cost 3D sensors is not very precise; therefore, the combination of this information with the one of other devices is an approach already in study. The main goal of this work is to develop a solution for the execution of a precise bin-picking process capable of grasping small and fragile objects without breaking or deforming them. This may be done by combining the information provided by two sensors: one 3D sensor (Kinect) used to analyse the workspace and identify the object, and a 1D laser sensor to determine the exact distance to the object when approaching it. Additionally, the developed system may be placed at the end of a manipulator in order to become an active perception unit. Once the global system of sensors, their controllers and the robotic manipulator are integrated into a ROS (Robot Operating System) infrastructure, the data provided by the sensors can be analysed and combined to provide a bin-picking solution. Finally, the testing phase demonstrated the viability and the reliability of the developed bin-picking process.À tecnologia usada por um robô para agarrar objetos que estão dispostos de forma aleatória dentro de uma caixa ou sobre uma palete chama-se binpicking. Este processo é de grande interesse para a industria uma vez que oferece maior autonomia, aumento de produção e redução de custos. O binpicking tem evoluido de forma significativa ao longo dos anos graças aos avanços possibilitados pelo desenvolvimento tecnológico na área da visão, software e soluções de diferentes garras que estão em constante evolução. Contudo, a criação de um sistema versátil, capaz de agarrar qualquer tipo de objeto sem o deformar, independentemente do ambiente desordenado à sua volta, continua a ser o principal objetivo. Para esse fim, o recurso à perceção 3D é imprescindível. Ainda assim, a informação adquirida por sensores 3D não é muito precisa e, por isso, a combinação deste com a de outros dispositivos é uma abordagem ainda em estudo. O objetivo principal deste trabalho é então desenvolver uma solução para a execução de um processo de bin-picking capaz de agarrar objetos pequenos e frágeis sem os partir ou deformar. Isto poderá ser feito através da combinação entre a informação proveniente de dois sensores: um sensor 3D (Kinect) usado para analisar o espaço de trabalho e identificar o objeto, e um sensor laser 1D usado para determinar a sua distância exata e assim se poder aproximar. Adicionalmente, o sistema desenvolvido pode ser acoplado a um manipulador de forma a criar uma unidade de perceção ativa. Uma vez tendo um sistema global de sensores, os seus controladores e o manipulador robótico integrados numa infraestrutura ROS (Robot Operating System), os dados fornecidos pelos sensores podem ser analisados e combinados, e uma solução de bin-picking pode ser desenvolvida. Por último, a fase de testes demonstrou, depois de alguns ajustes nas medidas do sensor laser, a viabilidade e fiabilidade do processo de bin-picking desenvolvido.Mestrado em Engenharia Mecânic

Investigation of upper limb prosthesis functionality using quantitative design tools

Upper limb prostheses offer those with limb loss a solution to restore some of their lost functionality by allowing them to participate in bilateral tasks, especially those required for daily living. Whilst there is a wide range of upper limb prostheses available, there remain high device rejection rates. Low functionality and discomfort are major factors in prosthesis rejection, which had been identified as challenges more than 60 years ago. These issues have not been effectively addressed due the lack of design tools for engineers and clinicians. Upper limb prostheses have seen greater technological advances than the methods to evaluate them effectively, which has resulted in over-engineered designs which do not meet the needs of their user. In this thesis , I aim to improve future upper limb prostheses through the development of three design tools. These design tools seek to quantify the functionality of prosthetic devices using motion capture analysis, virtual environments, and joint optimisation. By developing these tools, there is greater opportunity to optimise prostheses earlier in the design cycle which can result in improved functionality. It is anticipated that improvements in functionality will increase user satisfaction and therefore reduce device rejection rates Motion capture analysis was used to study the compensatory movements that arise from operating an upper limb prosthesis. Using a motion capture suit, the motor strategy of a participant was compared between using their biological hand and using a prosthesis through the use of an able-bodied adaptor. It was found that the shoulder and trunk had to make the most compensatory movements to complete several grasping tasks due to the lack of degrees of freedom at the distal end of the prosthesis. Without forearm supination/pronation and wrist extension/flexion, the participant had to approach the grasping tasks from a different angle, sometimes having to lean backwards and abduct their upper arm. The methodology of utilising a motion capture suit as a design tool to quantitatively assess the compensatory movements caused by a prosthetic device was successfully demonstrated. Virtual environments, in conjunction with quantitative grasp quality metrics, can be used to assess the performance of the upper limb prosthesis extremity alone, uninfluenced by user bias. A dynamic virtual environment is presented to simulate several grasping tasks with five upper limb prosthetic devices. Contact information from these grasping tasks are used to calculate the quality of the grasp and provide an overall grasping functionality score. From the simulation results, it was found that more degrees of freedom do not necessary equate to better grasping performance. The positions of force vectors during grasp formation are vital and they must be well- balanced in order to result in stable grasps. Simulated grasping and quantitative analysis in a virtual environment has been demonstrated, which can be used to better plan grasping paths and therefore improve the grasping functionality of upper limb prosthesis designs. Prosthesis users desire their devices to have a low mass, have a low cost, and have high functionality. However, these are conflicting design objectives and decisions must be made to which design considerations to prioritise. A multi-objective model was used to balance these three objectives and select the most suitable components that make up a prosthesis. A modularity scheme was used to divide an upper limb prosthesis into three categories: socket, forearm, and terminal device. In each category, several components were considered which can either be manufactured by conventional engineering or additive manufacturing. Each component would provide a unique value determined by a several quantitative utility functions. Based on satisfaction studies in the literature, the multi-objective optimisation model found that a Split Hook terminal device with an additively manufactured socket and forearm was the optimal design as it provided a low mass and excellent grasping functionality. This model has been demonstrated to work with different user requirements to intelligently select the most appropriate upper limb components within the modularity scheme. Overall, methods were developed which covered aspects of prosthesis design from clinical testing of prosthetic devices, functionality assessments of Computer Aided Design models, and intelligent selection of prosthesis components for individual requirements. It is hoped that these design tools may enable better communication between engineers and clinicians to ensure that users receive devices that are to their satisfaction