Passive Motion Paradigm: An Alternative to Optimal Control

In the last years, optimal control theory (OCT) has emerged as the leading approach for investigating neural control of movement and motor cognition for two complementary research lines: behavioral neuroscience and humanoid robotics. In both cases, there are general problems that need to be addressed, such as the “degrees of freedom (DoFs) problem,” the common core of production, observation, reasoning, and learning of “actions.” OCT, directly derived from engineering design techniques of control systems quantifies task goals as “cost functions” and uses the sophisticated formal tools of optimal control to obtain desired behavior (and predictions). We propose an alternative “softer” approach passive motion paradigm (PMP) that we believe is closer to the biomechanics and cybernetics of action. The basic idea is that actions (overt as well as covert) are the consequences of an internal simulation process that “animates” the body schema with the attractor dynamics of force fields induced by the goal and task-specific constraints. This internal simulation offers the brain a way to dynamically link motor redundancy with task-oriented constraints “at runtime,” hence solving the “DoFs problem” without explicit kinematic inversion and cost function computation. We argue that the function of such computational machinery is not only restricted to shaping motor output during action execution but also to provide the self with information on the feasibility, consequence, understanding and meaning of “potential actions.” In this sense, taking into account recent developments in neuroscience (motor imagery, simulation theory of covert actions, mirror neuron system) and in embodied robotics, PMP offers a novel framework for understanding motor cognition that goes beyond the engineering control paradigm provided by OCT. Therefore, the paper is at the same time a review of the PMP rationale, as a computational theory, and a perspective presentation of how to develop it for designing better cognitive architectures

Revisiting the Body-Schema Concept in the Context of Whole-Body Postural-Focal Dynamics

The body-schema concept is revisited in the context of embodied cognition, further developing the theory formulated by Marc Jeannerod that the motor system is part of a simulation network related to action, whose function is not only to shape the motor system for preparing an action (either overt or covert) but also to provide the self with information on the feasibility and the meaning of potential actions. The proposed computational formulation is based on a dynamical system approach, which is linked to an extension of the equilibrium-point hypothesis, called Passive Motor Paradigm: this dynamical system generates goal-oriented, spatio-temporal, sensorimotor patterns, integrating a direct and inverse internal model in a multi-referential framework. The purpose of such computational model is to operate at the same time as a general synergy formation machinery for planning whole-body actions in humanoid robots and/or for predicting coordinated sensory–motor patterns in human movements. In order to illustrate the computational approach, the integration of simultaneous, even partially conflicting tasks will be analyzed in some detail with regard to postural-focal dynamics, which can be defined as the fusion of a focal task, namely reaching a target with the whole-body, and a postural task, namely maintaining overall stability

The Irresistible Animacy of Lively Artefacts

This thesis explores the perception of ‘liveliness’, or ‘animacy’, in robotically driven artefacts. This perception is irresistible, pervasive, aesthetically potent and poorly understood. I argue that the Cartesian rationalist tendencies of robotic and artificial intelligence research cultures, and associated cognitivist theories of mind, fail to acknowledge the perceptual and instinctual emotional affects that lively artefacts elicit. The thesis examines how we see artefacts with particular qualities of motion to be alive, and asks what notions of cognition can explain these perceptions. ‘Irresistible Animacy’ is our human tendency to be drawn to the primitive and strangely thrilling nature of experiencing lively artefacts. I have two research methodologies; one is interdisciplinary scholarship and the other is my artistic practice of building lively artefacts. I have developed an approach that draws on first-order cybernetics’ central animating principle of feedback-control, and second-order cybernetics’ concerns with cognition. The foundations of this approach are based upon practices of machine making to embody and perform animate behaviour, both as scientific and artistic pursuits. These have inspired embodied, embedded, enactive, and extended notions of cognition. I have developed an understanding using a theoretical framework, drawing upon literature on visual perception, behavioural and social psychology, puppetry, animation, cybernetics, robotics, interaction and aesthetics. I take as a starting point, the understanding that the visual cortex of the vertebrate eye includes active feature-detection for animate agents in our environment, and actively constructs the causal and social structure of this environment. I suggest perceptual ambiguity is at the centre of all animated art forms. Ambiguity encourages natural curiosity and interactive participation. It also elicits complex visceral qualities of presence and the uncanny. In the making of my own Lively Artefacts, I demonstrate a series of different approaches including the use of abstraction, artificial life algorithms, and reactive techniques

Towards the Improvement of robot motion learning techniques

Dissertação de Mestrado em Engenharia InformáticaThis manuscript presents solutions and methods to address some of the many problems that arise when dealing with the complex task of motor skill learning in robots. In the last years, several research lines have focused on learning motion primitives either through imitation learning or reinforcement learning. However, for many applications, learning a motion primitive of a single form is not enough and it is required that after being assimilated, the primitive is generalizable such that it can be executed in different contexts and for distinct instances of the same task. Therefore, the motion primitive must adapt a set of parameters according to the environment variables instead of always executing the exact same motor commands when it is put into action. Another aspect to have into consideration is how the learning process of motion primitives is guided. Some primitives are too complex to be learned all at once, i.e, learning all their intricacies without a properly structured approach may be intractable. In this thesis, these aspects are mindfully taken into account, allowing to develop reinforcement learning techniques that are then used to teach a controller of a biped robot that is only able to generate stable locomotion on a flat surface, making it tolerant to a range of slope angles, perpendicular and/or parallel to the direction of walking. Legged locomotion is a relevant example of a complex and dynamic motor skill that has been the focus of intensive research for many years in robotics and it is expected for the techniques that are successful in the learning of such a hard task to be useful in other contexts. In order to achieve this goal, three main steps, divided into chapters of this thesis, are taken. First, an existing algorithm - Cost-regularized Kernel Regression (CrKR) - originally introduced to allow learning to generalize parameterized policies is modified and extended into a new algorithm named CrKR++. Some of the performed changes allow to use the algorithm for training sessions with a high number of samples, which is needed when it is intended to learn complex policies. This feat would be impracticable with the original version of the algorithm due to its high computational complexity. The remaining changes are issued with the purpose of improving the general effectiveness of the algorithm. Second, a framework that enables storing, combining and mutual learning of parameterized policies is presented. This framework, where the CrKR++ algorithm plays a core role, provides the means, for instance, to create a movement primitives library or to perform gradual learning of a motor skill, being named Flexible Framework for Learning (F3L). Finally, the developed framework is used to teach the controller of the biped robot to adapt its locomotion parameters according to the slope angles of the underlying surface. The achieved solution and intermediate steps are tested in simulation software with Dynamic Anthropomorphic Robot with Intelligence–Open Platform (DARwIn-OP) in carefully delineated experiments.Esta tese apresenta soluções e métodos que abordam alguns dos muitos problemas que surgem quando lidando com o complexo problema da aprendizagem de tarefas motoras em robôs. Nos últimos anos, várias linhas de investigação focaram-se na aprendizagem de primitivas de movimento, quer pela aprendizagem via imitação quer pela aprendizagem via reforço. Contudo, em muitas aplicações, não basta assimilar uma primitiva numa única forma e pode ser necessário que depois de assimilada, uma primitiva seja generalizável de maneira a ser possível executá-la em diferentes contextos e para diferentes instâncias de uma mesma tarefa. Uma primitiva de movimento deve portanto nestes casos adaptar um conjunto de parâmetros de acordo com as condições do meio envolvente em vez de executar sempre os mesmos comandos motores quando colocada em ação. Outro aspeto a ter em consideração é ainda a forma como o processo de aprendizagem das primitivas de movimento é guiado. Algumas primitivas são demasiado complexas para serem apreendidas de uma vez só, isto é, aprender todas as suas nuances sem uma abordagem estruturada pode revelar-se extremamente difícil. Nesta tese, estes dois aspetos são tidos em conta, o que permite desenvolver novas técnicas de aprendizagem via reforço que são depois usadas para ensinar um programa controlador de um robô bípede que é apenas capaz de lidar com superfícies planas, tornando-o tolerante a uma gama de inclinações em direções perpendiculares ou paralelas à direção do movimento. A locomoção com pernas é o exemplo definitivo de uma tarefa motora complexa e dinâmica que tem sido alvo de investigação intensiva durante anos na robótica. É de esperar que as técnicas que sejam bem sucedidas na aprendizagem de uma tarefa com este grau de dificuldade sejam também úteis em outros contextos. Para atingir este objetivo, três passos principais, que se dividem em capítulos desta tese são dados. Em primeiro lugar, um algoritmo já existente - CrKR - ,originalmente criado para permitir a aprendizagem de políticas parametrizadas, é modificado e transformado num novo algoritmo denominado CrKR++. Algumas das modificações feitas permitem usar o algoritmo em sessões de treino com um maior número de amostras, o que é necessário quando se pretende aprender políticas com um elevado grau de complexidade. Tal seria impossível com a versão original do algoritmo devido à sua elevada complexidade computacional. As restantes modificações são introduzidas com o propósito de melhorar a eficácia geral do algoritmo. Em segundo lugar, uma framework que permite o armazenamento, a combinação e a aprendizagem mútua de políticas parametrizadas é apresentada. Esta framework, onde o algoritmo CrKR++ desempenha uma função nuclear, providencia os meios para, por exemplo, criar uma biblioteca de primitivas de movimento ou realizar aprendizagem gradual de uma tarefa motora sendo denominada de F3L. Por fim, a framework desenvolvida é utilizada para ensinar o controlador do robô bípede a adaptar determinados parâmetros da locomoção em função da inclinação da superfície subjacente. A solução alcançada bem como os passos intermédios são testados em software de simulação com o robô DARwIn-OP em experiências cuidadosamente delineadas

Pattern Generation for Rough Terrain Locomotion with Quadrupedal Robots:Morphed Oscillators & Sensory Feedback

Animals are able to locomote on rough terrain without any apparent difficulty, but this does not mean that the locomotor system is simple. The locomotor system is actually a complex multi-input multi-output closed-loop control system. This thesis is dedicated to the design of controllers for rough terrain locomotion, for animal-like quadrupedal robots. We choose the problem of blind rough terrain locomotion as the target of experiments. Blind rough terrain locomotion requires continuous and momentary corrections of leg movements and body posture, and provides a proper testbed to observe the interaction of different mod- ules involved in locomotion control. As for the specific case of this thesis, we have to design rough terrain locomotion controllers that do not depend on the torque-control capability, have limited sensing, and have to be computationally light, all due to the properties of the robotics platform that we use. We propose that a robust locomotion controller, taking into account the aforementioned constraints, is constructed from at least three modules: 1) pattern generators providing the nominal patterns of locomotion; 2) A posture controller continuously adjusting the attitude of the body and keeping the robot upright; and 3) quick reflexes to react to unwanted momentary events like stumbling or an external force impulse. We introduce the framework of morphed oscillators to systematize the design of pattern gen- erators realized as coupled nonlinear oscillators. Morphed oscillators are nonlinear oscillators that can encode arbitrary limit cycle shapes and simultaneously have infinitely large basins of attraction. More importantly, they provide dynamical systems that can assume the role of feedforward locomotion controllers known as Central Pattern Generators (CPGs), and accept discontinuous sensory feedback without the risk of producing discontinuous output. On top of the CPG module, we add a kinematic model-based posture controller inspired by virtual model control (VMC), to control the body attitude. Virtual model control produces forces, and through the application of the Jacobian transpose method, generates torques which are added to the CPG torques. However, because our robots do not have a torque- control capability, we adapt the posture controller by producing task-space velocities instead of forces, thus generating joint-space velocity feedback signals. Since the CPG model used for locomotion generates joint velocities and accepts feedback without the fear of instability or discontinuity, the posture control feedback is easily integrated into the CPG dynamics. More- over, we introduce feedback signals for adjusting the posture by shifting the trunk positions, which directly update the limit cycle shape of the morphed oscillator nodes of the CPG. Reflexes are added, with minimal complexity, to react to momentary events. We implement simple impulse-based feedback mechanisms inspired by animals and successful rough terrain robots to 1) flex the leg if the robot is stumbling (stumbling correction reflex); 2) extend the leg if an expected contact is missing (leg extension reflex); or 3) initiate a lateral stepping sequence in response to a lateral external perturbation. CPG, posture controller, and reflexes are put together in a modular control architecture alongside additional modules that estimate inclination, control speed and direction, maintain timing of feedback signals, etc. [...

Generating whole body movements for dynamics anthropomorphic systems under constraints

Cette thèse étudie la question de la génération de mouvements corps-complet pour des systèmes anthropomorphes. Elle considère le problème de la modélisation et de la commande en abordant la question difficile de la génération de mouvements ressemblant à ceux de l'homme. En premier lieu, un modèle dynamique du robot humanoïde HRP-2 est élaboré à partir de l'algorithme récursif de Newton-Euler pour les vecteurs spatiaux. Un nouveau schéma de commande dynamique est ensuite développé, en utilisant une cascade de programmes quadratiques (QP) optimisant des fonctions coûts et calculant les couples de commande en satisfaisant des contraintes d'égalité et d'inégalité. La cascade de problèmes quadratiques est définie par une pile de tâches associée à un ordre de priorité. Nous proposons ensuite une formulation unifiée des contraintes de contacts planaires et nous montrons que la méthode proposée permet de prendre en compte plusieurs contacts non coplanaires et généralise la contrainte usuelle du ZMP dans le cas où seulement les pieds sont en contact avec le sol. Nous relions ensuite les algorithmes de génération de mouvement issus de la robotique aux outils de capture du mouvement humain en développant une méthode originale de génération de mouvement visant à imiter le mouvement humain. Cette méthode est basée sur le recalage des données capturées et l'édition du mouvement en utilisant le solveur hiérarchique précédemment introduit et la définition de tâches et de contraintes dynamiques. Cette méthode originale permet d'ajuster un mouvement humain capturé pour le reproduire fidèlement sur un humanoïde en respectant sa propre dynamique. Enfin, dans le but de simuler des mouvements qui ressemblent à ceux de l'homme, nous développons un modèle anthropomorphe ayant un nombre de degrés de liberté supérieur à celui du robot humanoïde HRP2. Le solveur générique est utilisé pour simuler le mouvement sur ce nouveau modèle. Une série de tâches est définie pour décrire un scénario joué par un humain. Nous montrons, par une simple analyse qualitative du mouvement, que la prise en compte du modèle dynamique permet d'accroitre naturellement le réalisme du mouvement.This thesis studies the question of whole body motion generation for anthropomorphic systems. Within this work, the problem of modeling and control is considered by addressing the difficult issue of generating human-like motion. First, a dynamic model of the humanoid robot HRP-2 is elaborated based on the recursive Newton-Euler algorithm for spatial vectors. A new dynamic control scheme is then developed adopting a cascade of quadratic programs (QP) optimizing the cost functions and computing the torque control while satisfying equality and inequality constraints. The cascade of the quadratic programs is defined by a stack of tasks associated to a priority order. Next, we propose a unified formulation of the planar contact constraints, and we demonstrate that the proposed method allows taking into account multiple non coplanar contacts and generalizes the common ZMP constraint when only the feet are in contact with the ground. Then, we link the algorithms of motion generation resulting from robotics to the human motion capture tools by developing an original method of motion generation aiming at the imitation of the human motion. This method is based on the reshaping of the captured data and the motion editing by using the hierarchical solver previously introduced and the definition of dynamic tasks and constraints. This original method allows adjusting a captured human motion in order to reliably reproduce it on a humanoid while respecting its own dynamics. Finally, in order to simulate movements resembling to those of humans, we develop an anthropomorphic model with higher number of degrees of freedom than the one of HRP-2. The generic solver is used to simulate motion on this new model. A sequence of tasks is defined to describe a scenario played by a human. By a simple qualitative analysis of motion, we demonstrate that taking into account the dynamics provides a natural way to generate human-like movements

Acting Objects: Staging New Materialism, Posthumanism and the Ecocritical Crisis in Contemporary Performance

I investigate the material relationship between human and nonhuman objects in performance, asking what their shifting relations reveal about our contemporary condition. Through analysis of contemporary theatre and performance and theories of new materialism, I aim to uncover the dramaturgical models that shift focus towards the agency of objects, thereby exposing alternate models of relationality. Grounded in sensual interactions generated through the performance event, these relations are equipped to develop an expanded sensibility and responsivity in the human. Additionally, I examine how these events enable experiences of the body where the body is both actor and acted upon. Furthermore, I consider the significance of these embodied experiences and a sense of solidarity with objects on feelings of anxiety that characterize the multiple senses of contemporary eco-crisis, climate, and technology. I argue that performance serves as a site in which to better understand our changing subject position, to imagine alternative human/nonhuman relationships, and to offer suggestions toward a more creative and affirmative posthuman experience

Actor & Avatar: A Scientific and Artistic Catalog

What kind of relationship do we have with artificial beings (avatars, puppets, robots, etc.)? What does it mean to mirror ourselves in them, to perform them or to play trial identity games with them? Actor & Avatar addresses these questions from artistic and scholarly angles. Contributions on the making of "technical others" and philosophical reflections on artificial alterity are flanked by neuroscientific studies on different ways of perceiving living persons and artificial counterparts. The contributors have achieved a successful artistic-scientific collaboration with extensive visual material

Design Transactions

Design Transactions presents the outcome of new research to emerge from ‘Innochain’, a consortium of six leading European architectural and engineering-focused institutions and their industry partners. The book presents new advances in digital design tooling that challenge established building cultures and systems. It offers new sustainable and materially smart design solutions with a strong focus on changing the way the industry thinks, designs, and builds our physical environment. Divided into sections exploring communication, simulation and materialisation, Design Transactions explores digital and physical prototyping and testing that challenges the traditional linear construction methods of incremental refinement. This novel research investigates ‘the digital chain’ between phases as an opportunity for extended interdisciplinary design collaboration. The highly illustrated book features work from 15 early-stage researchers alongside chapters from world-leading industry collaborators and academics

Design Transactions: Rethinking Information for a New Material Age

Design Transactions presents the outcome of new research to emerge from ‘Innochain’, a consortium of six leading European architectural and engineering-focused institutions and their industry partners. The book presents new advances in digital design tooling that challenge established building cultures and systems. It offers new sustainable and materially smart design solutions with a strong focus on changing the way the industry thinks, designs, and builds our physical environment. Divided into sections exploring communication, simulation and materialisation, Design Transactions explores digital and physical prototyping and testing that challenges the traditional linear construction methods of incremental refinement. This novel research investigates ‘the digital chain’ between phases as an opportunity for extended interdisciplinary design collaboration. The highly illustrated book features work from 15 early-stage researchers alongside chapters from world-leading industry collaborators and academics