The main goal of this thesis is to simulate the response of a humanoid robot using a specified control algorithm which can achieve a sustainable biped locomotion with 4 basic locomotion phases. Basic parts for the body of the humanoid robot model are shaped according to the specified basic physical parameters and assumed kinematic model. The kinematic model, which does not change according to locomotion phases and consists of 27 segments including 14 virtual segments, provides a humanoid robot model with 26 degrees of freedom (DOF). Corresponding kinematic relations for the robot model are obtained by recursive formulations. Derivation of dynamic equations is carried out by the Newton-Euler formulation. A trajectory definition algorithm which defines positions, orientations, translational and angular velocities for the hip and its mass center, toe part of the foot and its toe point is created. A control strategy based on predictive optimum command acceleration calculations and computed torque control method is implemented. The simulation is executed in Simulink and the visualization of the simulation is established in a virtual environment by Virtual Reality Toolbox of MATLAB. The simulation results and the user defined reference input are displayed simultaneously in the virtual environment. In this study, a simulation environment for the biped locomotion of humanoid robots is created. By the help of this thesis, the user can test various control strategies by modifying the modular structure of the simulation and acquire necessary information for the preliminary design study of a humanoid robot construction.

In this thesis, the walking of a humanoid system is simulated applying an optimal predictive control algorithm. The simulation is built using Matlab and Simulink softwares. Four separate physical models are developed to represent the single support and the double support phases of a full gait cycle. The models are three dimensional and their properties are analogous to the human&rsquo / s. In this connection, the foot models in the double support phases include an additional joint which connects the toe to the foot. The kinematic relationships concerning the physical models are formulated recursively and the dynamic models are obtained using the Newton &ndash / Euler formulation. The computed torque method is utilized at the level of joints. In the double support phase, the redundancy problem is solved by the optimization of the actuating torques. The command accelerations required to control the gait are obtained by applying an optimal predictive control law. The introduced humanoid walker achieves a sustainable gait by tuning the optimization and prediction parameters. The control algorithm manages the tracking of the predefined walking pattern with easily realizable joint accelerations. The simulation is capable of producing all the reaction forces, reaction moments and the values of the other variables. During these computations, a three dimensional view of the humanoid walker is animated simultaneously. As a result of this study, a suitable simulation structure is obtained to test and improve the mechanical systems which perform bipedal locomotion. The modular nature of the simulation structure developed in this study allows testing the performance of alternative control laws as well.

Cette thèse traite du problème de la locomotion des robots humanoïdes dans le contexte du projet européen KoroiBot. En s'inspirant de l'être humain, l'objectif de ce projet est l'amélioration des capacités des robots humanoïdes à se mouvoir de façon dynamique et polyvalente. Le coeur de l'approche scientifique repose sur l'utilisation du controle optimal, à la fois pour l'identification des couts optimisés par l'être humain et pour leur mise en oeuvre sur les robots des partenaires roboticiens. Cette thèse s'illustre donc par une collaboration à la fois avec des mathématiciens du contrôle et des spécialistes de la modélisation des primitives motrices. Les contributions majeures de cette thèse reposent donc sur la conception de nouveaux algorithmes temps-réel de contrôle pour la locomotion des robots humanoïdes avec nos collégues de l'université d'Heidelberg et leur intégration sur le robot HRP-2. Deux contrôleurs seront présentés, le premier permettant la locomotion multi-contacts avec une connaissance a priori des futures positions des contacts. Le deuxième étant une extension d'un travail réalisé sur de la marche sur sol plat améliorant les performances et ajoutant des fonctionnalitées au précédent algorithme. En collaborant avec des spécialistes du mouvement humain nous avons implementé un contrôleur innovant permettant de suivre des trajectoires cycliques du centre de masse. Nous présenterons aussi un contrôleur corps-complet utilisant, pour le haut du corps, des primitives de mouvements extraites du mouvement humain et pour le bas du corps, un générateur de marche. Les résultats de cette thèse ont été intégrés dans la suite logicielle "Stack-of-Tasks" du LAAS-CNRS. / This thesis covers the topic of humanoid robot locomotion in the frame of the European project KoroiBot. The goal of this project is to enhance the ability of humanoid robots to walk in a dynamic and versatile fashion as humans do. Research and innovation studies in KoroiBot rely on optimal control methods both for the identification of cost functions used by human being and for their implementations on robots owned by roboticist partners. Hence, this thesis includes fruitful collaborations with both control mathematicians and experts in motion primitive modeling. The main contributions of this PhD thesis lies in the design of new real time controllers for humanoid robot locomotion with our partners from the University of Heidelberg and their integration on the HRP-2 robot. Two controllers will be shown, one allowing multi-contact locomotion with a prior knowledge of the future contacts. And the second is an extension of a previous work improving performance and providing additional functionalities. In a collaboration with experts in human motion we designed an innovating controller for tracking cyclic trajectories of the center of mass. We also show a whole body controller using upper body movement primitives extracted from human behavior and lower body movement computed by a walking pattern generator. The results of this thesis have been integrated into the LAAS-CNRS "Stack-of-Tasks" software suit.

Human evolution has been linked to climate change multiple times in the literature. One of the more well-known theories is the ‘savannah’ theory, which states that walking upright became an advantageous character when climate in Africa changed causing drier environments, changing woodlands to savannahs. Human ancestors could cross open fields more easily when walking upright, therefore it was thought that climate change could be a driving factor in the change to bipedal locomotion. Five hominin species were the basis of the study presented here, showing that change towards bipedal locomotion was a mosaic process with gradual change. A review of the relevant literature shows that the timing of change in fossils to bipedal locomotion and climate change do not coincide in the interval 6-3 Ma, therefore suggesting that climate change did not drive human evolution in this case. Changes towards open landscapes with C4 grass dominance peaked at the Pliocene-Pleistocene boundary (2.6 Ma), while the first hominin species already walked completely bipedally before 3.5 Ma.

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The task of modeling and controlling the evolution of dynamical sys- tems is one of the main objectives in mechatronics engineering. When approaching the problem of controlling physical or digital systems, the dynamical models have been historically divided into continuous-time, described by differential equations, and discrete-time, described by difference equations. In the last decade, a new class of models, known as hybrid dynamical systems, has gained popularity in the control community because of its high versatility. This framework combines continuous-time and discrete- time evolution, thus allowing for both the description of a broader class of systems and the achievement of better-performing controllers, compared to the traditional continuous-time alternatives. After the first rigorous introduction of the framework, several Lyapunov-based results were published in the literature, and numerous application areas were shown to benefit from the introduction of a hybrid dynamics, like systems involving impacts or physical systems connected to digital controllers (cyber-physical systems). In this thesis, we use the hybrid framework to study different mechatronics-inspired control problems. The applications we consider are diverse, so we split the presentation into three parts. In the first part we further analyze a particular hybrid control strategy, known as reset control, providing some new theoretical guarantees, together with an application to adaptive control. In the second part we consider two applications of the hybrid framework to the network dynamics field, specifically we analyze the problems of distributed state estimation and of uniform synchronization of nonlinear oscillators. In the third part, we use a hybrid approach to study two applications where this framework has been rarely employed, or not at all, namely smart agriculture and trajectory tracking for a bipedal walking robot. We study these application-inspired problems from a theoretical point of view, giving robust Lyapunov-based stability guarantees. We complement the theoretical analysis with numerical results, obtained from simulations or from experiments.

The aim of this thesis is to recognize a walking person in a sequence of images by defining his or her reference points to compare the course of their movement and then to identify the scanned person. Methods „k-means“ and „mean shift“ are used to obtain the silhouette of the person. However “environment model estimation” method is used here before those mentioned above. It is a type of a difference method and it helps to specify the scanning area and shortens the time of segmentation. During the search for the reference points the thesis focuses on three areas: the centre of the head and both ankle joints. Those points are later determined on the previous image sequence and compared with the real locations of the centre of the head and ankle joints marked by the user. The thesis also focuses on comparing the movement courses of those points and tries to identify the people whose walks are being scanned. Problematic situations which occurred during the whole process are analyzed in the end. The result of the thesis is an algorithm which can locate a moving person in an image sequence (video) and determine the reference points (centre of the head and ankles) to compare them and identify the scanned person.

Biped robots with serial links driven by an electric motor experience problems because the motor and transmission are installed in each joint, causing the legs to become very heavy. Previous solutions involved robots using servo valves, a type of highly responsive proportional valve. However, high supply pressure is necessary to realize high responsiveness and the resulting energy losses are large. To address this problem, we proposed a hydraulic direct-drive system in which the pump controls the cylinder meter-in flow, while a proportional valve controls the meter-out flow. Furthermore, our hydraulic interlocking drive system connects two hydraulic direct-drive systems for biped humanoid robots and concentrates the pump output on one side cylinder. The meter-in flow rate of the other side cylinder is controlled by the meter-out flow rate of the cylinder on which the pump is concentrated. A comparison of the walking simulation performance with that of the conventional independent system shows that our proposed system reduces the motor output power by 24.3%. These results prove the feasibility of constructing a two-legged robot without having to incorporate highly responsive servo valves.