712 research outputs found
Discrete-time repetitive optimal control: Robotic manipulators
This paper proposes a discrete-time repetitive optimal control of electrically driven robotic manipulators using an uncertainty estimator. The proposed control method can be used for performing repetitive motion, which covers many industrial applications of robotic manipulators. This kind of control law is in the class of torque-based control in which the joint torques are generated by permanent magnet dc motors in the current mode. The motor current is regulated using a proportional-integral controller. The novelty of this paper is a modification in using the discrete-time linear quadratic control for the robot manipulator, which is a nonlinear uncertain system. For this purpose, a novel discrete linear time-variant model is introduced for the robotic system. Then, a time-delay uncertainty estimator is added to the discrete-time linear quadratic control to compensate the nonlinearity and uncertainty associated with the model. The proposed control approach is verified by stability analysis. Simulation results show the superiority of the proposed discrete-time repetitive optimal control over the discrete-time linear quadratic control
Control Of Rigid Robots With Large Uncertainties Using The Function Approximation Technique
This dissertation focuses on the control of rigid robots that cannot easily be modeled due to complexity and large uncertainties. The function approximation technique (FAT), which represents uncertainties as finite linear combinations of orthonormal basis functions, provides an alternate form of robot control - in situations where the dynamic equation cannot easily be modeled - with no dependency on the use of model information or training data. This dissertation has four aims - using the FAT - to improve controller efficiency and robustness in scenarios where reliable mathematical models cannot easily be derived or are otherwise unavailable. The first aim is to analyze the uncertain combination of a test robot and prosthesis in a scenario where the test robot and prosthesis are adequately controlled by different controllers - this is tied to efficiency. We develop a hybrid FAT controller, theoretically prove stability, and verify its performance using computer simulations. We show that systematically combining controllers can improve controller analysis and yield desired performance. In the second aim addressed in this dissertation, we investigate the simplification of the adaptive FAT controller complexity for ease of implementation - this is tied to efficiency. We achieve this by applying the passivity property and prove controller stability. We conduct computer simulations on a rigid robot under good and poor initial conditions to demonstrate the effectiveness of the controller. For an n degrees of freedom (DOFs) robot, we see a reduction of controller tuning parameters by 2n. The third aim addressed in this dissertation is the extension of the adaptive FAT controller to the robust control framework - this is tied to robustness. We invent a novel robust controller based on the FAT that uses continuous switching laws and eliminates the dependency on update laws. The controller, when compared against three state-of-the-art controllers via computer simulations and experimental tests on a rigid robot, shows good performance and robustness to fast time-varying uncertainties and random parameter perturbations. This introduces the first purely robust FAT-based controller. The fourth and final aim addressed in this dissertation is the development of a more compact form of the robust FAT controller developed in aim~3 - this is tied to efficiency and robustness. We investigate the simplification of the control structure and its applicability to a broader class of systems that can be modeled via the state-space approach. Computer simulations and experimental tests on a rigid robot demonstrate good controller performance and robustness to fast time-varying uncertainties and random parameter perturbations when compared to the robust FAT controller developed in aim 3. For an n-DOF robot, we see a reduction in the number of switching laws from 3 to 1
Discrete time robust control of robot manipulators in the task space using adaptive fuzzy estimator
This paper presents a discrete-time robust control for electrically driven robot manipulators in the task space. A novel discrete-time model-free control law is proposed by employing an adaptive fuzzy estimator for the compensation of the uncertainty including model uncertainty, external disturbances and discretization error. Parameters of the fuzzy estimator are adapted to minimize the estimation error using a gradient descent algorithm. The proposed discrete control is robust against all uncertainties as verified by stability analysis. The proposed robust control law is simulated on a SCARA robot driven by permanent magnet dc motors. Simulation results show the effectiveness of the control approach
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Redesigning the human-robot interface : intuitive teleoperation of anthropomorphic robots
textA novel interface for robotic teleoperation was developed to enable accurate and highly efficient teleoperation of the Industrial Reconfigurable Anthropomorphic Dual-arm (IRAD) system and other robotic systems. In order to achieve a revolutionary increase in operator productivity, the bilateral/master-slave approach must give way to shared autonomy and unilateral control; autonomy must be employed where possible, and appropriate sensory feedback only where autonomy is impossible; and today’s low-information/high feedback model must be replaced by one that emphasizes feedforward precision and minimal corrective feedback. This is emphasized for task spaces outside of the traditional anthropomorphic scale such as mobile manipulation (i.e. large task spaces) and high precision tasks (i.e. very small task spaces). The system is demonstrated using an anthropomorphically dimensioned industrial manipulator working in task spaces from one meter to less than one millimeter, in both simulation and hardware. This thesis discusses the design requirements and philosophy of this interface, provides a summary of prototype teleoperation hardware, simulation environment, test-bed hardware, and experimental results.Mechanical Engineerin
A Brief History of Industrial Robotics in the 20th Century
Industrial robotics is a branch of robotics that gained paramount importance in the last century. The presence of robots totally revolutionized the industrial environment in just a few decades. In this paper, a brief history of industrial robotics in the 20th century will be presented, and a proposal for classifying the evolution of industrial robots into four generations is set forward. The characteristics of the robots belonging to each generation are mentioned, and the evolution of their features is described. The most significant milestones of the history of industrial robots, from the 1950\u2019s to the end of the century, are mentioned, together with a description of the most representative industrial robots that were designed and manufactured in those decades
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The evolution of teleoperated manipulators at ORNL
ORNL has made significant contributions to teleoperator and telerobotics technology for two decades and continues with an aggressive program today. Examples of past projects are: (1) the M2 servomanipulator, which was the first digitally controlled teleoperator; (2) the Advanced Servomanipulator (ASM), which was the first remotely maintainable teleoperator; (3) the CESARm/Kraft dissimilar teleoperated system; and (4) the Laboratory Telerobotic Manipulator (LTM), a 7-Degree-of-Freedom (7-DOF) telerobot built as a prototype for work in space. More recently, ORNL has become heavily involved with Environmental Restoration and Waste Management (ERWM) robotics programs funded by the Department of Energy (DOE). The ERWM program requires high payloads and high dexterity. As a result, a hydraulically actuated, dual-arm system comprised of two 6-DOF arms mounted on a 5-DOF base has been constructed and is being used today for various research tasks and for decontamination and dismantlement activities. All of these teleoperated manipulator systems build upon the experiences gained throughout the almost two decades of development. Each system incorporates not only the latest technology in computers, sensors, and electronics, but each new . system also adds at least one new feature to the technologies already developed and demonstrated in the previous system(s). As a result of this process, a serious study of these manipulator systems is a study in the evolution of teleoperated manipulator the systems in general. This provides insight not only into the research and development paths chosen in the past, but also into the appropriate directions for future teleoperator and telerobotics research. This paper examines each of the teleoperated/telerobotic systems developed at ORNL, summarizes their features and capabilities, examines the state of the most current telerobotic system (the Dual Arm Work Module), PM provides direction for a Next Generation Telerobotic Manipulator system
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