Cette thèse traite de l'identification des paramètres dynamiques des robots, en s'appuyant sur les méthodes d'identification en robotique, qui utilisent le modèle dynamique inverse, ou le modèle de puissance, ou le modèle d'énergie du robot. Ce travail revisite le modèle d'énergie en exploitant le caractère intégral des fonctions modulatrices appliquées au modèle de puissance du robot. En outre, les procédures d'intégration sont analysées dans le domaine fréquentiel, et certains groupes de fonctions modulatrices sont sélectionnés afin d'offrir un bon comportement de filtre passe-bas. Ensuite, l'introduction d'un différentiateur algèbrique récemment développé est proposé, nommé différentiateurs de Jacobi. L'analyse est effectuée dans le domaine temporel, et dans le domaine fréquenciel, ce qui met en évidence la propriété de filtrage passe bande et permet de sélectionner les paramètres des différentiateurs. Puis, ces différentiateurs sont appliqués avec succès à l'identification de robot, ce qui prouve leur bonne performance. Les comparaisons entre les différents modèles d'identification, les différenciateurs, les techniques des moindres carrés sont présentées et des conclusions sont tirées dans le domaine de l'identification de robot. / This thesis discusses the identification issues of the robot dynamic parameters. Starting with the well-known inverse dynamic identification model, power and energy identification models for robots, it extends the identification model from an energy point of view, by integrating modulating functions with robot power model. This new identification model avoids the computation of acceleration data. As well, the integration procedures are analyzed in frequency domain so that certain groups of modulating functions are selected in order to offer a good low-pass filtering property. Then, a recently developed high order algebraic differentiator is proposed and studied, named Jacobi differentiators. The analyses are done in both the time domain and in the frequency domain, which gives a clear clue about the differentiator filtering property and about how to select the differentiator parameters. Comparisons among different identification models, differentiators, least square techniques are presented and conclusions are drawn in the robot identification issues.

A robot may collect intrinsic and extrinsic properties of targets from the operator, by actively changing its own states, and by actively changing the target states. This thesis studies the robot's exploration of these properties by changing the target states, in order to model objects and scenes. To model the objects, a novel dynamic process is formulated for interactive object segmentation, and a solution based on particle filter and active learning is developed, thus the robot manipulates and learns the object structures incrementally and autonomously. To build abstract object models from the structural object samples, a multilevel part-based object model is developed by applying latent support vector machine to the training of a hierarchical object structure. / To model the scenes, relational semantic mapping method is developed to describe the scenes with both the objects and various object relations. Relational operators are introduced, in order to build relational semantic maps with relational Markov network, where the robot learns object relations actively and incrementally. To find an object in a map, the operator provides the name of target object and the semantic description of the map, and then the robot instantiates a relational Markov network based on the description and learned parameters. After that, it detects the object with the relational Markov network. / This thesis demonstrates the proposed approach on a robot arm, a humanoid robot, and a mobile robot. The results show that the robots learn target information autonomously by manipulating the target models to build sensor-semantics mappings, and use the information to find and manipulate objects accurately. / 一個機器人可以使用多種辦法來獲取物體和場景的語義信息，例如通過和操作對象的交流，通過主動地改變其自身的狀態，或者通過改變目標的狀態。本論文的研究集中于機器人如何通過改變目標模型來學習物體和場景的信息。 / 對於物體的模型，一種新穎的動態過程被提出，以便描述交互式物體分割，並且提出一種基於粒子濾波和主動學習的方案，這樣機器人可以通過操縱和學習物體來自主了解物體結構信息。為了從這些被分割的物體圖片中建立抽象的物體模型，多層次基於物體結構的模型被提出，並且通過將支持向量機應用到分層對象結構的訓練來學習這個模型。 / 對於場景的模型，開係語義地圖被提出，以便描述由物體組成的場景以及其中不同的物體之間的關係。關係還算符被引入到關係馬爾可夫網絡，以便建立基於闕係的語義映射，這樣一個機器人可以自主和主動地學習物體之間的關係。為了地圖找到物體，操作者可以提供目標對象和基於語義的場景描述，然後機器人實例化一個關係語義地圖，通過已經學習到的物體和關係參數。在這之後，機器人通過實例化的關係馬爾科夫網絡來在場景中搜索物體。 / 這種策略被在多種機器人上面被驗證，包括機器手臂，人形機器人，以及移動機器人。結果表明該機器人可以通過操縱目標物體模型來建立傳感器數據和語義之間的影射，並且使用這樣的語義信息來自主和準確地搜尋和操縱對象。 / Li, Kun. / Thesis Ph.D. Chinese University of Hong Kong 2015. / Includes bibliographical references (leaves 151-163). / Abstracts also in Chinese. / Title from PDF title page (viewed on 07, October, 2016). / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only.

Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 2010

The aim of the thesis is to develop a model-based control strategy, namely, the Model Predictive Control (MPC) method, for robot position control using artificial neural networks. MPC is primarily developed for process control. Therefore its application in robot control has been less reported. In addition, conventional MPC uses linear model of the system for prediction which leads to inaccuracy for highly non-linear systems, such as robot. In this thesis a simulation model of a modified PUMA robot is constructed. This model is built using both MATLAB/SIMULINK and FORTRAN languages. In this model, the full robot dynamics is used together with the realistic factors, such as the actuator effects and the gear backlash, to represent the real system accurately. All simulations throughout this thesis are carried out on this model. A model predictive control strategy for robot trajectory tracking is also introduced in this thesis. The feasibility of the proposed MPC control method is studied based on a perfect prediction model, a model with uncertainties, and when the frequency band of the MPC controller is limited. Furthermore, a new method of using neural networks for robot dynamics modelling is introduced. This method is developed on the basis of a numerical differential technique that eliminates the explicit requirement of robot joint accelerations. Therefore, this method can be easily implemented on physical systems. As the measurements of the robot joint positions, velocities, and torques collected from operating the robot can be used to train the neural network, a more accurate dynamic model can be obtained. Finally, the MPC control method and the neural network model are combined together to form a neural network based MPC controller. The validity of this method is verified by using simulation on the simulated robot system / Master of Engineering (Hons)

<p>Nowadays, the polishing process is one of the most important steps of the manufacturing of moulds and dies. Occupying up to 40% of the total production time and cost, it is decisive for the final appearance and quality of a surface. Because of its complexity, the polishing is mainly carried out manually; and the final quality depends of the expertise of the operator. That is why an automation of the polishing process is necessary.</p><p>The purpose of this project was to find out the optimized sequence of polishing for a Mirrax ESR steel (Uddeholm Tooling AB) using the Strecon RAP-200 (robot assisted polishing equipment). Using a Design of Experiment, the machine parameters were tested in order to better understand their influences and interactions. The report starts with a description of general polishing knowledge and ends up with the results from a Design of Experiment.</p><p>The information from this test are a first step in the evaluation of the Strecon RAP-200. Even if many results have been found out, only four parameters have been tested, and to be able to optimize the polishing sequence, further studies need to be carried out.</p>

In this paper we propose an architecture for a new task-level system, which we call TWAIN. Task-level programming attempts to simplify the robot programming process but requiring that the user specify only goals for the physical relationships among objects, rather than the motions needed to achieve those goals. A task-level specification is meant to be completely robot independent; no positions or paths that depend on the robot geometry or kinematics are specified by the user. We have two goals for this paper. Th is first is to present a more unified t reatment of some individual pieces of r esearch in task planning, whose r elationship has not previously been d escribed. The second is to provide a new framework for further research in task-planning. This is a slightly modified version of a paper that appeared in Proceedings of Soli d Modeling by Computers: from Theory to A pplications, Research laboratories Sympo sium Series, sponsored by General Motors, Warren, Michigan, September 1983.

This thesis presents an evolutionarily design change for the Delta parallel robot. The proposed design change increases the useful workspace of the robot and aids in permanently avoiding singularities in the workspace. This is accomplished by means of a new intermediate link parallel to the 4 bar linkage. The addition of the new link simultaneously increases the total workspace volume and decreases the dexterity without significantly affecting the stiffness. The design is analyzed and the inverse kinematics, Jacobian, sti ness and dexterity relations are formulated. The relations are then converted into a form that is usable by MATLAB to calculate di erent workspaces that illustrate the advantages of the new design. Subsequently, an optimization problem is formulated that aims to take advantage of the new attributes to create a balanced robot that further illustrates the benefits of the new design. The results are clearly illustrated by comparing plotted sections of workspace from both the optimized and unoptimized workspace. Lastly, the design is developed into a 3D model which is then fabricated into a working prototype to test and verify functionality. / UOIT

This research builds up on recent results in planar kinematic synthesis with contact direction and curvature constraints on the workpiece. The synthesis of spherical serial chains is considered to guide a rigid body, such that it does not violate normal direction and curvature constraints imposed by contact with objects in the environment. These constraints are transformed into conditions on the velocity and acceleration of points in the moving body to obtain synthesis equations which can be solved by algebraic elimination. Trajectory interpolation formulas yield the movement of the chain with the desired contact properties in each of the task positions. Example shows the application of the developed theory to the failure recovery of a robot manipulator.

Nowadays, the polishing process is one of the most important steps of the manufacturing of moulds and dies. Occupying up to 40% of the total production time and cost, it is decisive for the final appearance and quality of a surface. Because of its complexity, the polishing is mainly carried out manually; and the final quality depends of the expertise of the operator. That is why an automation of the polishing process is necessary. The purpose of this project was to find out the optimized sequence of polishing for a Mirrax ESR steel (Uddeholm Tooling AB) using the Strecon RAP-200 (robot assisted polishing equipment). Using a Design of Experiment, the machine parameters were tested in order to better understand their influences and interactions. The report starts with a description of general polishing knowledge and ends up with the results from a Design of Experiment. The information from this test are a first step in the evaluation of the Strecon RAP-200. Even if many results have been found out, only four parameters have been tested, and to be able to optimize the polishing sequence, further studies need to be carried out.

The purpose of this research is to imitate the motion of the crab, and to propose a new control strategy for hexapod robots. Referring to the proportion of a real crab, we construct a 12- actuator hexapod robot. Walking experiments are achieved by using a tripod gait, a metachronal gait and a paired metachronal gait. We observe the loading of actuators and compare the functionality of the gaits. A special feed-forward gait and the Zero Torque control strategy are added in the climbing experiment. A compressed rubber-wire carpet and wire dactyl claws are used to simulate the non-slip climbing condition. Our experiment results show that the loading condition of the pendulous tripod gait is better than conventional tripod gait, and the paired metachronal gait is better than metachronal gait. During climbing experiments, our robot walks on a vertical, an upside-down, and two transitional terrains.