La robotique humanoïde arrive a maturité avec des robots plus rapides et plus précis. Pour faire face à la complexité mécanique, la recherche a commencé à regarder au-delà du cadre habituel de la robotique, vers les sciences de la vie, afin de mieux organiser le contrôle du mouvement. Cette thèse explore le lien entre mouvement humain et le contrôle des systèmes anthropomorphes tels que les robots humanoïdes. Tout d’abord, en utilisant des méthodes classiques de la robotique, telles que l’optimisation, nous étudions les principes qui sont à la base de mouvements répétitifs humains, tels que ceux effectués lorsqu’on joue au yoyo. Nous nous concentrons ensuite sur la locomotion en nous inspirant de résultats en neurosciences qui mettent en évidence le rôle de la tête dans la marche humaine. En développant une interface permettant à un utilisateur de commander la tête du robot, nous proposons une méthode de contrôle du mouvement corps-complet d’un robot humanoïde, incluant la production de pas et permettant au corps de suivre le mouvement de la tête. Cette idée est poursuivie dans l’étude finale dans laquelle nous analysons la locomotion de sujets humains, dirigée vers une cible, afin d’extraire des caractéristiques du mouvement sous forme invariants. En faisant le lien entre la notion “d’invariant” en neurosciences et celle de “tâche cinématique” en robotique humanoïde, nous développons une méthode pour produire une locomotion réaliste pour d’autres systèmes anthropomorphes. Dans ce cas, les résultats sont illustrés sur le robot humanoïde HRP2 du LAAS-CNRS. La contribution générale de cette thèse est de montrer que, bien que la planification de mouvement pour les robots humanoïdes peut être traitée par des méthodes classiques de robotique, la production de mouvements réalistes nécessite de combiner ces méthodes à l’observation systématique et formelle du comportement humain. / Humanoid robotics is coming of age with faster and more agile robots. To compliment the physical complexity of humanoid robots, the robotics algorithms being developed to derive their motion have also become progressively complex. The work in this thesis spans across two research fields, human neuroscience and humanoid robotics, and brings some ideas from the former to aid the latter. By exploring the anthropological link between the structure of a human and that of a humanoid robot we aim to guide conventional robotics methods like local optimization and task-based inverse kinematics towards more realistic human-like solutions. First, we look at dynamic manipulation of human hand trajectories while playing with a yoyo. By recording human yoyo playing, we identify the control scheme used as well as a detailed dynamic model of the hand-yoyo system. Using optimization this model is then used to implement stable yoyo-playing within the kinematic and dynamic limits of the humanoid HRP-2. The thesis then extends its focus to human and humanoid locomotion. We take inspiration from human neuroscience research on the role of the head in human walking and implement a humanoid robotics analogy to this. By allowing a user to steer the head of a humanoid, we develop a control method to generate deliberative whole-body humanoid motion including stepping, purely as a consequence of the head movement. This idea of understanding locomotion as a consequence of reaching a goal is extended in the final study where we look at human motion in more detail. Here, we aim to draw to a link between “invariants” in neuroscience and “kinematic tasks” in humanoid robotics. We record and extract stereotypical characteristics of human movements during a walking and grasping task. These results are then normalized and generalized such that they can be regenerated for other anthropomorphic figures with different kinematic limits than that of humans. The final experiments show a generalized stack of tasks that can generate realistic walking and grasping motion for the humanoid HRP-2. The general contribution of this thesis is in showing that while motion planning for humanoid robots can be tackled by classical methods of robotics, the production of realistic movements necessitate the combination of these methods with the systematic and formal observation of human behavior.

<p>U tezi je prikazan novi metod za sintezu i realizaciju dvonožnog<br />veštačkog hoda koji se zasniva na upotrebi jednostavnih pokreta čijim<br />je kombinovanjem moguće realizovati kompleksne pokrete kao što je<br />hod, a čiji se parametri mogu menjati tokom kretanja. Time je omogućeno<br />da se na osnovu informacija o nameravanom kretanju i stanja okoline<br />izvrši sinteza kretanja izborom i kombinacijom jednostavnih<br />bazičnih pokreta koje se nazivaju primitivi. Takođe je omogućeno da se,<br />tokom izvršavanja hoda bez njegovog prekida, menjaju parametri<br />kretanja kao što su brzina hoda, dužina koraka, pravac kretanja i<br />visina podizanja noge tokom prenosne faze. Potvrda je data kroz<br />eksperimentalne rezultate koji su sprovedeni simulacijom na<br />dinamičkom modelu humanoidnog robota.</p> / <p>This dissertation presents new method for the synthesis and realization of<br />biped artificial walk based on the use of simple movements that can be<br />combined in order to achieve complex movements such as walk, whereas it<br />is possible to change the motion parameters at any time. It means that,<br />based on the information about intended movement and current state of the<br />environment, it is possible to synthesize motion by selecting and tying simple<br />movements, i.e. motion primitives. It also enables the robot to change<br />walking parameters online such as walking speed, direction of walk, foot<br />length during swing phase and step length. Proof of this method is given by<br />experimental results obtained during the simulation on a dynamic model of<br />humanoid robot.</p>

The way our brain works is still an open question, but one thing seems to be clear: biological neural systems are computationally powerful, robust and noisy. Natural nervous system are able to control limbs in different scenarios with high precision. As neural networks in living beings communicate through spikes, modern neuromorphic systems try to mimic them by using spike-based neuron models. This thesis is focused on the advancement of neurorobotics or brain inspired robotic arm controllers based on artificial neural network architectures. The architecture chosen to implement those controllers was the spike neuron version of Reservoir Computing framework, called Liquid State Machines. The main goal is to explore the possibility of using brain inspired neural networks to control a robot by demonstration. Moreover, it aims to achieve systems robust to environmental noise and internal structure destruction presenting a graceful degradation. As the validation, a series of action learning experiments are presented where simulated robotic arms are controlled. The investigation starts with a 2 degrees of freedom arm and moves to the research version of the Rethink Robotics Inc. collaborative humanoid robot Baxter. Moreover, a proof-of- concept experiment is also done using the real Baxter robot. The results show Liquid State Machines, when endowed with an extra external feedback loop, can be also employed to control more complex humanoid robotic arms than a simple planar 2 degrees of freedom one. Additionally, the new parallel architecture presented here was capable to withstand noise and internal destruction better than a simple use of multiple columns also presenting a graceful degradation behaviour.

<p>In the field of robotics there is a great interest in developing strategies and algorithms to reproduce human-like behavior. One can think of human-like machines that may replace humans in hazardous working areas, perform enduring assembly tasks, serve the elderly and handicapped, etc. The main challenges in the development of such robots are, first, to construct sophisticated electro-mechanical humanoids and, second, to plan and control human-like motor patterns.</p><p>A promising idea for motion planning and control is to reparameterize any somewhat coordinated motion in terms of virtual holonomic constraints, i.e. trajectories of all degrees of freedom of the mechanical system are described by geometric relations among the generalized coordinates. Imposing such virtual holonomic constraints on the system dynamics allows to generate synchronized motor patterns by feedback control. In fact, there exist consistent geometric relations in ordinary human movements that can be used advantageously. In this thesis the virtual constraints approach is extended to a wider and rigorous use for analyzing, planning and reproducing human-like motions based on mathematical tools previously utilized for very particular control problems.</p><p>It is often the case that some desired motions cannot be achieved by the robot due to limitations in available actuation power. This constraint rises the question of how to modify the mechanical design in order to achieve better performance. An underactuated planar two-link robot is used to demonstrate that springs can complement the actuation in parallel to an ordinary motor. Motion planning is carried out for the original robot dynamics while the springs are treated as part of the control action with a torque profile suited to the preplanned trajectory.</p><p>Another issue discussed in this thesis is to find stable and unstable (hybrid) limit cycles for passive dynamic walking robots without integrating the full set of differential equations. Such procedure is demonstrated for the compass-gait biped by means of optimization with a reduced number of initial conditions and parameters to search. The properties of virtual constraints and reduced dynamics are exploited to solve this problem.</p>

In the field of robotics there is a great interest in developing strategies and algorithms to reproduce human-like behavior. One can think of human-like machines that may replace humans in hazardous working areas, perform enduring assembly tasks, serve the elderly and handicapped, etc. The main challenges in the development of such robots are, first, to construct sophisticated electro-mechanical humanoids and, second, to plan and control human-like motor patterns. A promising idea for motion planning and control is to reparameterize any somewhat coordinated motion in terms of virtual holonomic constraints, i.e. trajectories of all degrees of freedom of the mechanical system are described by geometric relations among the generalized coordinates. Imposing such virtual holonomic constraints on the system dynamics allows to generate synchronized motor patterns by feedback control. In fact, there exist consistent geometric relations in ordinary human movements that can be used advantageously. In this thesis the virtual constraints approach is extended to a wider and rigorous use for analyzing, planning and reproducing human-like motions based on mathematical tools previously utilized for very particular control problems. It is often the case that some desired motions cannot be achieved by the robot due to limitations in available actuation power. This constraint rises the question of how to modify the mechanical design in order to achieve better performance. An underactuated planar two-link robot is used to demonstrate that springs can complement the actuation in parallel to an ordinary motor. Motion planning is carried out for the original robot dynamics while the springs are treated as part of the control action with a torque profile suited to the preplanned trajectory. Another issue discussed in this thesis is to find stable and unstable (hybrid) limit cycles for passive dynamic walking robots without integrating the full set of differential equations. Such procedure is demonstrated for the compass-gait biped by means of optimization with a reduced number of initial conditions and parameters to search. The properties of virtual constraints and reduced dynamics are exploited to solve this problem.

Drawing from gender studies, cultural studies, and feminist technoscience literature, this dissertation employs an interdisciplinary approach to analyze the androcentric imaginaries through which humanoid sex robots ("sexbots") emerge. Specifically, I utilize sexbots to interrogate and reflect on issues such as consent, whiteness, and humanity. By situating sexbots as proxies for feminized and racialized humans, I argue that the production, portrayal, and proliferation of sexbots are reflections of how we treat marginalized people, reifying existing hierarchal power relations. This project begins by analyzing the creation and dissemination of sexbots by popular sex technology ("sextech") companies. Critically surveying published papers, interviews, and research from various sexbot texts, I attend to gendered and racialized discourses of sexbot consent and companionship in human-sexbot relationships. Next, I analyze the overwhelming presence of whiteness with/in sexbots, exploring how anti-Black racism manifests in sexbots, and underscoring how both the present and "future" of sextech remains rooted in the past. Then, I catalog and dissect the published materials and interviews of prominent sextech creators, critically juxtaposing the marketing discourses of sexbots and evincing how both the sextech elite and science journalists—specifically writers I refer to as "sexbot journalists"—influence, change, and inform the meanings of sexbots. Finally, I turn to robots and robot alternatives found in feminist speculative fiction, utilizing these stories as a way of looking elsewhere in order to theorize what is possible for sexbots as well as our (current and future) relationships to these emerging technologies. At its core, this dissertation is an invitation to question white heteropatriarchy mediated through the controversial existence of sexbots. While synthetic women are the ostensible "subjects" of investigation—as well as commodities exchanged by creators and subsequently praised by enthusiasts—it is the "real" feminized and racialized humans who lie at the heart of this project. Through a much-needed feminist intervention, this project offers an in-depth analysis of humanoid sex robots and what they reveal about violence and power in the world around us. / Doctor of Philosophy / Humanoid sex robots ("sexbots") have served as inspiration for countless inventors, scholars, and writers of science fact and fiction. Sexbots, as I intend to show, are also shaped by gendered and racialized imaginaries, leading to their condemnation by feminist and race-critical science and technology scholars. At the same time, sexbots are popularly advertised as suitable alternatives for human companionship, promoted as emerging technologies designed for users uninterested in, or unable to, have sexual relations with "real" or "organic" women. Interrogating the troubling imaginaries behind these synthetic women, I analyze the creation, production, and dissemination of sexbots by popular sex technology ("sextech") companies. Specifically, I use sexbots to explore urgent issues such as humanity, consent, and whiteness. Unable to consent to the acts they are programmed to perform, or combat the abuse directed toward them, sexbots are often associated with sexual and gender-based violence. By situating sexbots as proxies for feminized and racialized humans, this project argues that the production, portrayal, and proliferation of sexbots are reflections of how we treat marginalized people, reinforcing existing problems related to patriarchy, misogyny, and anti-Black racism. While this project is deeply interested in sexbots, its heart is intimately human. Ultimately, I use sexbots to critically reflect on issues of power and violence in our world, as well as to (re)imagine feminist relationships to these emerging technologies.

Recent advancements in actuator technologies, computation, and control have led to major leaps in capability and have brought humanoids ever closer to being feasible solutions for real-world applications. As the capabilities of humanoids increase, they will be called on to operate in unstructured real world environments. This realization has driven researchers to develop more dynamic, robust, and adaptable robots. Compared to state-of-the-art robots, biological systems demonstrate remarkably better efficiency, agility, adaptability, and robustness. Many recent studies suggest that a core principle behind these advantages is compliance, yet there are very few compliant humanoids that have demonstrated successful walking. The work presented in this dissertation is based on several years of developing novel actuators for two full-scale linearly actuated compliant humanoid robots, SAFFiR and THOR. Both are state-of-the-art robots intended to operate in the extremely challenging real world scenarios of shipboard firefighting and disaster response. The design, modeling, and control of actuators in robotics application is critical because the rest of the robot is often designed around the actuators. This dissertation seeks to address two goals: 1) advancing the design of compliant linear actuators that are well suited for humanoid applications, and 2) developing a better understanding of how to design and model compliant linear actuators for use in humanoids. Beyond just applications for compliant humanoids, this research tackles many of the same design and application challenges as biomechanics research so it has many potential applications in prosthetics, exoskeletons, and rehabilitation devices. / Ph. D.

Human beings have a touch and force estimation mechanism beneath their feet. They use this feeling of touch and force to maintain balance, walk, run and perform various agile motions. This paper presents a new sensor platform beneath the humanoid feet, enabled by a pragmatic model based compliant foot design and sensor configuration that mimics the human tactile sensory system for contact force measurement in humanoid robots. Unlike previous force sensor based approaches, the system is defined as a total and sufficient method of Ground Reaction Force (GRF) and Zero Moment Point (ZMP) measurement for balancing and walking using contact force feedback in mid to full sized humanoids. The conventional systems for the GRF and ZMP measurement are made of heavy metallic parts that tend to be bulky and vulnerable to inertial noises upon high acceleration. In addition to low cost and reliable operation, the proposed system can withstand shock and enable agile motion much like humans do with their footpad. The proposed foot is manufactured using state-of-the-art technique with elastomer padding which not only protects the sensors but also acts as a compliance beneath the foot giving integrity in structural design. This composite layer provides compliance and traction for foot collision while the contact surfaces are sampled for pressure distribution which can be mapped into three axis force and ZMP. A single step training process is required to relate the sensor readings to force measurement. The system’s capability of contact force measurement, subsequent ZMP estimation is experimentally verified with the application of appropriate software. Moreover, a simulation study has been conducted via Finite Element Analysis (FEA) of the footpad structure to analyze the proposed footpad structure. The experimental results demonstrate why this can be a major step toward a biomimetic, affordable yet robust contact force and ZMP measurement method for humanoid robots. This work was supported by the Office of Naval Research, Grant N00014-15-1-2128 as part of development of Project SAFFiR (Shipboard Autonomous Firefighting Robot). / Master of Science / How we interact with the surfaces in contact with us has a crucial role for balancing and walking with agility. The biological touch and force measurement systems in human is currently unmatched, not even mimicked in a significant way in the state-of-the-art humanoid robots’ systems. Human beings use this feeling of touch and force beneath the feet to maintain balance, walk, run and perform various agile motions. This research aims to find a holistic system in humanoid robot’s feet design that can mimic this human characteristics of force estimation beneath the feet and using that estimation for balancing and walking. A practical model based sensor configuration is derived from the rigorous study of human and humanoid robot’s feet contact with the ground. The sensors are tactile in nature, and unlike previous below feet based approaches, the system is defined as a total and sufficient system of Ground Reaction Force (GRF) and Center of Pressure (CoP) measurement. The conventional systems for this purpose are not only highly expensive but also having error in quantification during accelerated movement. The proposed foot is designed following the practical model derived and manufactured using the state-of-the-art mechanism for having a soft cushion between the sensors and the contact surfaces. In addition to low cost and reliable operation, the proposed system can withstand shock and enable agile motion much like humans do with their footpad. The quantification of the forces and pressure from the sensor readings and developed using appropriate software and algorithms. The system’s capability of contact force measurement, subsequent Center of Pressure measurement is experimentally verified with the application of appropriate software. Moreover, a simulation study has been conducted of the footpad structure to analyze the proposed footpad structure. The experimental results demonstrate why this can be a major step toward a biomimetic, affordable yet robust contact force and Center of Pressure measurement method for human-like robots.

Bipedal locomotion in humanoid robots is a very challenging problem within the field of robot locomotion. In this thesis, we propose and demonstrate an omni-directional walking engine that achieves stable walking using feedback from an inertial measurement unit. Our walking engine generates gaits for which the zero moment point is on the center of the supporting foot. The mechanical structure of CHARLI-L, a humanoid robot used as our test platform in this thesis, is first introduced by describing the inverse kinematics of its legs. The principles of the omni-directional gait generator that creates walking motions and overcomes the robot's mechanical deficiencies is discussed. We develop and implement two kinds of feedback controllers; one is the gait feedback controller and the other is the joint feedback controller. Both feedback controllers use proportional-derivative of the angle of the pelvis from an inertial measurement unit. The results of the experiments are presented the efficacy of our proposed walking engine. / Master of Science

Dans cette thèse nous nous intéressons à deux types d'approches pour la planification de pas pour robots humanoïdes : d'une part les approches discrètes où le robot n'a qu'un nombre fini de pas possibles, et d'autre part les approches où le robot se base sur des zones de faisabilité continues. Nous étudions ces problèmes à la fois du point de vue théorique et pratique. En particulier nous décrivons deux méthodes originales, cohérentes et efficaces pour la planification de pas, l'une dans le cas discret (chapitre 5) et l'autre dans le cas continu (chapitre 6). Nous validons ces méthodes en simulation ainsi qu'avec plusieurs expériences sur le robot HRP-2. / In this thesis we investigate two types of approaches for footstep planning for humanoid robots: on one hand the discrete approaches where the robot has only a finite set of possible steps, and on the other hand the approaches where the robot uses continuous feasibility regions. We study these problems both on a theoretical and practical level. In particular, we describe two original, coherent and efficient methods for footstep planning, one in the discrete case (chapter 5), and one in the continuous case (chapter 6). We validate these methods in simulation and with several experiments on the robot HRP-2.