On-line programming of industrial robots is time consuming and requires experience in robot programming. Due to this fact, small and medium sized enterprises are reserved about the implementation of robots in production. Ongoing research in the field is focused on finding more intuitive interfaces and methods for programming to make the interaction with robots more natural and intuitive. This master thesis presents a method for manipulation of industrial robots utilizing an external device other than the traditional teach pendant. The base of the method is a PC application which handles the program logic and the communication between an external device and an ABB robot. The program logic is designed to be modular in order to allow customization of the method, both in terms of its functions and the type of external device that is used for the method. Since gestures are one of the most common forms of communication between humans, it is interesting to investigate gestures for the purpose to make manipulation of industrial robots more intuitive. Therefore, a Leap Motion controller is presented as an example of an external device which could be used as an alternative to the teach pendant. The Leap Motion controller is specialised on hand and finger position tracking with both good absolute accuracy and precision. Further, its associated Software Development Kit (SDK) has the capabilities which are required to enable implementation of a teach pendants most fundamental functionalities. Results obtained by a user test show that the developed application is both easy and fast to use but has poor robustness.

Kartläggning med robotar är ett område som redan tidigt i robotiken setts somviktigt, med många moderna produkter som möjliggjorts av forskningens framsteg.Särskilt med senare tidens implementation av sannolikhetslära och datoralgoritmer föratt lösa problemet SLAM (Simultaneous Localization And Mapping). Detta projekt harhaft som syfte att konstruera en robot som kan röra sig i ett rum och kartlägga allaväggar och föremål den ser, inspirerat av tidiga SLAM applikationer. Det roboten sermålas sedan upp i en datorapplikation för att ge användaren en bild av rummetsstruktur. Ett flertal moderna men relativt enkla komponenter och metoder haranvänts för konstruktionen och designen av roboten som utvecklats.Friformframställning med 3D-skrivare användes för att skapa robotens chassi, enArduino Nano mikrokontroller styr sensorer och motorer ochBluetooth-kommunikation möjliggör skickande av mätvärden till en dator.Datorapplikationen som skrevs i programmeringsspråket Python använder sedaninbyggda moduler som hjälp för att grafiskt illustrera de mätningar roboten gjort.Resultatet blev slutligen en robot som kan utföra korrekta rumsmätningar då antaletförflyttningar är väldigt få och en datorapplikation med användarvänlig struktur somritar upp dem. Begränsningar i funktionaliteten återstod trots försök att kompenseraför hårdvarufel, dock kan roboten ligga till grund för ytterligare förbättringar ochvidare applikationer.

Motivado pelo fato de que a escolha correta da forma preênsil para mãos robóticas antropomórficas representa aspectos relevantes no planejamento de estratégias de manipulação de objetos, este trabalho: desenvolve um algoritmo de pegas de objetos compatíveis com a tarefa a ser realizada e um método computacional de ajuste de superelipsóides a superfícies de objetos sintéticos 3D para modelar as primitivas resultantes do estágio de segmentação manual do objeto. Essa representação volumétrica contempla as atrativas propriedades de um modelo compacto, controlável e intuitivo, capaz de modelar uma ampla variedade de geometrias simétricas básicas a partir de 11 parâmetros. Tendo em vista que a acomodação de superelipsóides a nuvens de pontos caracteriza desafios típicos de mínimos quadrados, um breve estudo sobre o método numérico de Levenberg-Marquardt, utilizado na minimização da função objetivo adotada, se mostrou necessário para maximizar a sua eficiência. O desempenho e a eficiência do programa computacional desenvolvido foram demonstrados na modelagem experimental de cinco primitivas organizadas em diferentes configurações. As pequenas distorções, consideradas aceitáveis para a proposta do trabalho, evidenciaram a robustez da representação de formas elementares empregando superelipsóides sem deformações. Encerrada a etapa de modelagem das primitivas, um método de auto-aprendizagem supervisionada interpreta as informações de forma e tamanho de tais formas básicas para sugerir a pega de uma das primitivas que compõem o objeto e a forma preênsil compatível com a tarefa desejada. / Motivated by the fact that the correct choice of prehensile form for anthropomorphic robotic hand describes relevant aspects in planning strategies of object manipulation, this work develops an algorithm of grasping objects to match the task requirements and a computational method capable of fitting superellipsoids to surfaces of synthetic 3D objects to model the resulting primitives from the manual segmentation stage of the object. This volumetric representation describes the attractive properties of a compact, controllable and intuitive model, which is capable of modeling a wide variety of standard geometric solids by using eleven parameters. Since the superellipsoid fitting process characterizes typical least squares problems, a brief review about Levenberg-Marquardt numerical method, employed for the adopted objective function minimization, was necessary to maximize its efficiency. The performance and efficiency of the developed program were demonstrated in the experimental modeling of five symmetrical primitives shapes organized in several configurations. The small distortions, considered acceptable to the work proposal, confirm the robustness of representing elementary shapes employing superellipsoids without deformations. After finishing the primitive modeling stage, a supervised learning method interprets the size and shape information of such basic shapes to suggest the grasp of one constituent single parts and the task-compatible prehensile form.

Handing over objects is the foundation of many human-robot interaction and collaboration tasks. In the scenario where a human is handing over an object to a robot, the human chooses where the object needs to be transferred. The robot needs to accurately predict this point of transfer to reach out proactively, instead of waiting for the final position to be presented. We first conduct a human-to-robot handover motion study to analyze the effect of user height, arm length, position, orientation and robot gaze on the object transfer point. Our study presents new observations on the effect of robot's gaze on the point of object transfer. Next, we present an efficient method for predicting the Object Transfer Point (OTP), which synthesizes (1) an offline OTP calculated based on human preferences observed in the human-robot motion study with (2) a dynamic OTP predicted based on the observed human motion. Our proposed OTP predictor is implemented on a humanoid nursing robot and experimentally validated in human-robot handover tasks. Compared to using only static or dynamic OTP estimators, it has better accuracy at the earlier phase of handover (up to 45% of the handover motion) and can render fluent handovers with a reach-to-grasp response time (about 3.1 secs) close to natural human receiver's response. In addition, the OTP prediction accuracy is maintained across the robot's visible workspace by utilizing a user-adaptive reference frame.

Un système robotique distribué et reconfigurable (MSRR) est composé de plusieurs modules ayant certaines fonctions de mouvement, de perception et d'action. Ils peuvent s'adapter à l'environnement et aux objectifs en se connectant et en se déconnectant pour obtenir la configuration et la forme désirées. Les MSRR contiennent souvent deux systèmes : l'un constitué d'actionneurs pour le mouvement, l'autre pour la connexion. A l'heure actuelle, de nombreuses institutions travaillent sur les MSRR ; la conception, la miniaturisation, l'économie d'énergie, les algorithmes de contrôle ont fait l'objet de recherches dans ce domaine. Cependant, il existe peu d'études conjointes sur le matériel et les algorithmes correspondants. Cette thèse décrit la conception, la fabrication, les résultats expérimentaux, l'algorithmique distribuée et un simulateur d'une plate-forme MSRR. En nous appuyant sur le calcul et la simulation numérique, nous présentons un aimant électro-permanent simplifié (SEP) qui ne consomme pas d'énergie lorsque le module est connecté à un autre module. Un nouveau concept de moteur linéaire basé sur les SEP est également proposé. Ensuite, nous présentons DILI, un MSRR cubique, de longueur 1,5cm. Le module DILI peut coulisser sur une surface plane, la vitesse maximale pouvant atteindre 20mm/s. Avec le nouvel actionneur, DILI peut réaliser les fonctions de mouvement et de connexion. Un module DILI peut se connecter avec quatre autres modules. Enfin, un algorithme distribué est proposé et un simulateur est conçu pour permettre de simuler le système distribué, de tester et valider les algorithmes distribués. / A distributed modular self-reconfiguring robotic (MSRR) system is composed of many repeated basic modules with certain functions of motion, perception, and actuation. They can adapt to environment and goals by connecting and disconnecting to achieve the desired configuration and shape. MSRRs often contain two hardware systems: one is for actuation (motion), another one is for connection. At present time many institutions work on MSRRs; structural design, miniaturization, energy saving, control algorithms have been the focus of research in this area. However, only a few of them work on both the hardware and the corresponding algorithms. This thesis describes the design, fabrication, experimental results, distributed algorithm, and simulator of a MSRR platform. Via theoretical calculation and numerical simulation, we present the simplified electro-permanent (SEP) magnet which can change the magnetic field direction and does not require energy consumption while connected. A new concept of linear motor based on SEP is proposed. Then we construct DILI, a cubical MSRR, the length of each module is 1.5cm. DILI module can slide on a flat surface; the maximum speed can reach 20mm/s. With the new actuator, DILI can achieve the functions of motion and connection with only one system inside. Finally, a distributed algorithm is proposed in order to build a smart conveyor, and a simulator is designed that permits one to perform distributed simulations, test and validate distributed algorithms.

De nos jours, les exigences en productivité dans le monde industriel imposent aux robots un comportement optimal en termes de précision géométrique et dynamique, et en termes de temps de réponse. Ainsi, la présence des flexibilités dans les liaisons pivots des structures mécaniques légères se déplaçant à grande vitesse et sous charges importantes peut limiter dynamiquement la précision et le temps de stabilisation sur la pose finale du robot. La problématique traitée dans ces travaux concerne la maîtrise des vibrations des robots sériels à liaisons flexibles durant les opérations de prise et dépose (Pick and Place).Dans ces travaux, nous effectuons une modélisation et une identification expérimentale des paramètres géométriques et dynamique d’un robot à liaisons flexible. Ce modèle sera utilisé dans la synthèse d’une loi de commande basée modèle dédiée aux robots à flexibilité articulaire. Cette stratégie permet de réduire les vibrations lors des phases exigeantes dynamiquement. Des simulations sur un robot Scara sont alors conduites pour valider la pertinence de cette loi de commande qui intègre un modèle des flexibilités présentes dans les liaisons pivots dans le schéma de commande. Nous appliquons sur le même simulateur du robot à liaisons flexibles trois autres stratégies de commande afin de faire une comparaison (commande PD, commande dédiée aux robots rigides et commande ne considérant pas les amortissements). Le schéma de la loi de commande basée modèle permet de respecter la précision de pose finale avec une diminution du temps de stabilisation. Finalement, Le calcul de l’erreur d’asservissement nous a permis de constater l’influence des erreurs de modélisation de la flexibilité sur la précision de la tâche. Dans ce contexte, une analyse de sensibilité aux paramètres influents est établie. / Nowadays, the demand of productivity in the industrial world of robotics require robots to behave optimally in terms of geometric and dynamic accuracy and response time. Thus, the presence of flexibilities in rotational joints can dynamically limit the position control of manipulators having lighter arms, higher payload-to-weight ratio and doing tasks at high speed. The problem addressed in this work concerns the vibration control of serial robots with flexible joints performing Pick and Place tasks. In this work, we carry out modelling and experimental identification of the geometric and dynamic parameters of a robot with flexible joints. This model is then used in the synthesis of a model-based control law dedicated to manipulators with flexible joints. This strategy reduces vibrations resulting from joints sensitivity during dynamically demanding phases. Simulations on a Scara robot are then conducted to validate the relevance of the proposed control law which integrates joint flexibilities in the form of a feedback loop in the control diagram. To this end, three other control strategies (PD control, control dedicated to rigid structures and control not considering damping) are applied to the same simulator in order to make a comparative analysis. The diagram of the model-based control law allows to respect the set point with a reduction in the stabilization time.Finally, the calculation of the servo error allowed us to see the influence of flexibility modeling errors on the accuracy of the task. In this context, the sensitivity of this control law is evaluated through a sensitivity analysis.

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by Lo, Ka-wah. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1995. / Includes bibliographical references (leaves 76-81 (2nd gp.)). / Acknowledgments --- p.i / Abstract --- p.ii / Notations --- p.iii / List of Figures --- p.v / List of Tables --- p.vii / Chapter 1. --- Introduction / Chapter 1.1 --- Motivation --- p.1 / Chapter 1.2 --- Literature Review --- p.4 / Chapter 1.3 --- Objective --- p.10 / Chapter 2. --- Comparison of Different Approaches / Chapter 2.1 --- Sample Manipulator --- p.11 / Chapter 2.1.1 --- Force Decomposition Method --- p.12 / Chapter 2.1.2 --- Forward Rate Kinematics Base Method --- p.15 / Chapter 2.1.3 --- Grassmann Geometry Method --- p.18 / Chapter 2.2 --- Comparison Criteria --- p.20 / Chapter 2.2.1 --- Computational Complexity --- p.20 / Chapter 2.2.2 --- Scope of Application --- p.22 / Chapter 2.3 --- Summary --- p.23 / Chapter 3. --- Enumeration of Configuration Singularity / Chapter 3.1 --- Novel 6 DOF --- p.25 / Chapter 3.1.1 --- Result Analysis --- p.31 / Chapter 3.2 --- A 3 DOF with Symmetric Base --- p.33 / Chapter 3.2.1 --- Result Analysis --- p.35 / Chapter 3.3 --- A 3 DOF with Non-Symmetric Base --- p.36 / Chapter 3.3.1 --- Result Analysis --- p.37 / Chapter 3.4 --- A New Model of 6-SPS Defined by Kong et al --- p.40 / Chapter 3.5 --- A New Class of 6-SPS Platform-Type Parallel Manipulator --- p.45 / Chapter 3.5.1 --- The Hexagonal Base --- p.46 / Chapter 3.5.2 --- The Pentagonal Base --- p.50 / Chapter 3.5.3 --- The Tetragonal Base --- p.52 / Chapter 3.5.4 --- The Triangular Base --- p.55 / Chapter 3.6 --- Summary --- p.59 / Chapter 4. --- Numerical Analysis / Chapter 4.1 --- Parameter Analysis --- p.60 / Chapter 4.1.1 --- One Unknown Variable --- p.61 / Chapter 4.1.2 --- Two Unknown Variables --- p.63 / Chapter 4.2 --- Critical Value of Ratio R/q --- p.69 / Chapter 4.3 --- Summary --- p.72 / Chapter 5. --- Conclusions and Future Work / Chapter 5.1 --- Conclusions --- p.73 / Chapter 5.2 --- Future Work --- p.75 / References --- p.76 / Appendix --- p.82

Chow Ying-ho. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 78-83). / Abstracts in English and Chinese. / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Objectives - Visual Navigation for Legged Robots --- p.1 / Chapter 1.2 --- Summary of Results --- p.3 / Chapter 1.3 --- Hardware Issues --- p.4 / Chapter 1.4 --- Contributions --- p.4 / Chapter 1.5 --- Organization of the Thesis --- p.4 / Chapter Chapter 2 --- Previous Work --- p.6 / Chapter 2.1 --- Vision Based Navigation --- p.6 / Chapter 2.1.1 --- Homography --- p.7 / Chapter 2.1.2 --- Ground Plane Obstacle Detection --- p.9 / Chapter 2.1.3 --- Regression --- p.12 / Chapter 2.2 --- Control Strategy --- p.13 / Chapter Chapter 3 --- System Overview --- p.16 / Chapter Chapter 4 --- Obstacle Detection by Fast Homography Estimation --- p.20 / Chapter 4.1 --- Ground Feature Extraction --- p.21 / Chapter 4.2 --- Ground Feature Correspondence --- p.21 / Chapter 4.3 --- Ground Homography Estimation --- p.24 / Chapter 4.3.1 --- Input point transformation --- p.24 / Chapter 4.3.2 --- Initial estimation --- p.26 / Chapter 4.3.3 --- Robust estimation --- p.27 / Chapter 4.4 --- Obstacle Detection --- p.29 / Chapter 4.5 --- Local Obstacle Map (LOM) on Ground --- p.33 / Chapter 4.5.1 --- Extraction from accumulative evidence --- p.34 / Chapter 4.5.2 --- Time-delay compensation --- p.34 / Chapter Chapter 5 --- Obstacle Avoidance by a Fuzzy Controller --- p.36 / Chapter 5.1 --- Gait Pattern --- p.38 / Chapter 5.2 --- Fuzzy Logic Controller --- p.42 / Chapter 5.2.1 --- Controller Inputs --- p.42 / Chapter 5.2.2 --- Controller Outputs --- p.43 / Chapter 5.2.3 --- Inference mechanism --- p.46 / Chapter Chapter 6 --- Implementation --- p.49 / Chapter 6.1 --- Hardware components --- p.49 / Chapter 6.1.1 --- VisionBug --- p.49 / Chapter 6.1.2 --- RF transmitter / receiver modules: --- p.52 / Chapter 6.2 --- Perception --- p.55 / Chapter 6.3 --- Image Calibration --- p.56 / Chapter 6.4 --- Motion Calibration: --- p.58 / Chapter 6.5 --- Software Programs --- p.66 / Chapter 6.5.1 --- Computational complexity --- p.68 / Chapter Chapter 7 --- Experimental Results --- p.69 / Chapter 7.1 --- Real Navigation Experiments --- p.70 / Chapter 7.2 --- Error Analysis of LOM --- p.73 / Chapter Chapter 8 --- Conclusion and future work --- p.76

Fok Lo Ming. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 133-135). / Abstracts in English and Chinese. / Chapter 1. --- Introduction --- p.1 / Chapter 1.1 --- Multi-fingered Robotic Hands --- p.1 / Chapter 1.2 --- Grasping Force Optimization --- p.2 / Chapter 1.3 --- Neural Networks --- p.6 / Chapter 1.4 --- Previous Work for Grasping Force Optimization --- p.9 / Chapter 1.5 --- Contributions of this work --- p.10 / Chapter 1.6 --- Organization of this thesis --- p.12 / Chapter 2. --- Problem Formulations --- p.13 / Chapter 2.1 --- Grasping Force Optimization without Joint Torque Limits --- p.14 / Chapter 2.1.1 --- Linearized Friction Cone Approach --- p.15 / Chapter i. --- Linear Formulation --- p.17 / Chapter ii. --- Quadratic Formulation --- p.18 / Chapter 2.1.2 --- Nonlinear Friction Cone as Positive Semidefinite Matrix --- p.19 / Chapter 2.1.3 --- Constrained Optimization with Nonlinear Inequality Constraint --- p.20 / Chapter 2.2 --- Grasping Force Optimization with Joint Torque Limits --- p.21 / Chapter 2.2.1 --- Linearized Friction Cone Approach --- p.23 / Chapter 2.2.2 --- Constrained Optimization with Nonlinear Inequality Constraint --- p.23 / Chapter 2.3 --- Grasping Force Optimization with Time-varying External Wrench --- p.24 / Chapter 2.3.1 --- Linearized Friction Cone Approach --- p.25 / Chapter 2.3.2 --- Nonlinear Friction Cone as Positive Semidefinite Matrix --- p.25 / Chapter 2.3.3 --- Constrained Optimization with Nonlinear Inequality Constraint --- p.26 / Chapter 3. --- Recurrent Neural Network Models --- p.27 / Chapter 3.1 --- Networks for Grasping Force Optimization without Joint Torque Limits / Chapter 3.1.1 --- The Primal-dual Network for Linear Programming --- p.29 / Chapter 3.1.2 --- The Deterministic Annealing Network for Linear Programming --- p.32 / Chapter 3.1.3 --- The Primal-dual Network for Quadratic Programming --- p.34 / Chapter 3.1.4 --- The Dual Network --- p.35 / Chapter 3.1.5 --- The Deterministic Annealing Network --- p.39 / Chapter 3.1.6 --- The Novel Network --- p.41 / Chapter 3.2 --- Networks for Grasping Force Optimization with Joint Torque Limits / Chapter 3.2.1 --- The Dual Network --- p.43 / Chapter 3.2.2 --- The Novel Network --- p.45 / Chapter 3.3 --- Networks for Grasping Force Optimization with Time-varying External Wrench / Chapter 3.3.1 --- The Primal-dual Network for Quadratic Programming --- p.48 / Chapter 3.3.2 --- The Deterministic Annealing Network --- p.50 / Chapter 3.3.3 --- The Novel Network --- p.52 / Chapter 4. --- Simulation Results --- p.54 / Chapter 4.1 --- Three-finger Grasping Example of Grasping Force Optimization without Joint Torque Limits --- p.54 / Chapter 4.1.1 --- The Primal-dual Network for Linear Programming --- p.57 / Chapter 4.1.2 --- The Deterministic Annealing Network for Linear Programming --- p.59 / Chapter 4.1.3 --- The Primal-dual Network for Quadratic Programming --- p.61 / Chapter 4.1.4 --- The Dual Network --- p.63 / Chapter 4.1.5 --- The Deterministic Annealing Network --- p.65 / Chapter 4.1.6 --- The Novel Network --- p.57 / Chapter 4.1.7 --- Network Complexity Analysis --- p.59 / Chapter 4.2 --- Four-finger Grasping Example of Grasping Force Optimization without Joint Torque Limits --- p.73 / Chapter 4.2.1 --- The Primal-dual Network for Linear Programming --- p.75 / Chapter 4.2.2 --- The Deterministic Annealing Network for Linear Programming --- p.77 / Chapter 4.2.3 --- The Primal-dual Network for Quadratic Programming --- p.79 / Chapter 4.2.4 --- The Dual Network --- p.81 / Chapter 4.2.5 --- The Deterministic Annealing Network --- p.83 / Chapter 4.2.6 --- The Novel Network --- p.85 / Chapter 4.2.7 --- Network Complexity Analysis --- p.87 / Chapter 4.3 --- Three-finger Grasping Example of Grasping Force Optimization with Joint Torque Limits --- p.90 / Chapter 4.3.1 --- The Dual Network --- p.93 / Chapter 4.3.2 --- The Novel Network --- p.95 / Chapter 4.3.3 --- Network Complexity Analysis --- p.97 / Chapter 4.4 --- Three-finger Grasping Example of Grasping Force Optimization with Time-varying External Wrench --- p.99 / Chapter 4.4.1 --- The Primal-dual Network for Quadratic Programming --- p.101 / Chapter 4.4.2 --- The Deterministic Annealing Network --- p.103 / Chapter 4.4.3 --- The Novel Network --- p.105 / Chapter 4.4.4 --- Network Complexity Analysis --- p.107 / Chapter 4.5 --- Four-finger Grasping Example of Grasping Force Optimization with Time-varying External Wrench --- p.109 / Chapter 4.5.1 --- The Primal-dual Network for Quadratic Programming --- p.111 / Chapter 4.5.2 --- The Deterministic Annealing Network --- p.113 / Chapter 4.5.3 --- The Novel Network --- p.115 / Chapter 5.5.4 --- Network Complexity Analysis --- p.117 / Chapter 4.6 --- Four-finger Grasping Example of Grasping Force Optimization with Nonlinear Velocity Variation --- p.119 / Chapter 4.5.1 --- The Primal-dual Network for Quadratic Programming --- p.121 / Chapter 4.5.2 --- The Deterministic Annealing Network --- p.123 / Chapter 4.5.3 --- The Novel Network --- p.125 / Chapter 5.5.4 --- Network Complexity Analysis --- p.127 / Chapter 5. --- Conclusions and Future Work --- p.129 / Publications --- p.132 / Bibliography --- p.133 / Appendix --- p.136