936 resultados para Robot control


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The authors demonstrate that a widely proposed method of robot dynamic control can be inherently unstable, due to an algebraic feedback loop condition causing an ill-posed feedback system. By focussing on the concept of ill-posedness a necessary and sufficient condition is derived for instability in robot manipulator systems which incorporate online acceleration cross-coupling control. Also demonstrated is a quasilinear multivariable control framework useful for assessing the robustness of this type of control when the instability condition is not obeyed.

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Robust climbing in unstructured environments has been one of the long-standing challenges in robotics research. Among others, the control of large adhesion forces is still an important problem that significantly restricts the locomotion performance of climbing robots. The main contribution of this paper is to propose a novel approach to autonomous robot climbing which makes use of hot melt adhesion (HMA). The HMA material is known as an economical solution to achieve large adhesion forces, which can be varied by controlling the material temperature. For locomotion on both inclined and vertical walls, this paper investigates the basic characteristics of HMA material, and proposes a design and control of a climbing robot that uses the HMA material for attaching and detaching its body to the environment. The robot is equipped with servomotors and thermal control units to actively vary the temperature of the material, and the coordination of these components enables the robot to walk against the gravitational forces even with a relatively large body weight. A real-world platform is used to demonstrate locomotion on a vertical wall, and the experimental result shows the feasibility and overall performances of this approach. © 2013 Elsevier B.V. All rights reserved.

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In this paper a new kind of hopping robot has been designed which uses inverse pendulum dynamics to induce bipedal hopping gaits. Its mechanical structure consists of a rigid inverted T-shape mounted on four compliant feet. An upright "T" structure is connected to this by a rotary joint. The horizontal beam of the upright "T" is connected to the vertical beam by a second rotary joint. Using this two degree of freedom mechanical structure, with simple reactive control, the robot is able to perform hopping, walking and running gaits. During walking, it is experimentally shown that the robot can move in a straight line, reverse direction and control its turning radius. The results show that such a simple but versatile robot displays stable locomotion and can be viable for practical applications on uneven terrain.

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This thesis presents methods for implementing robust hexpod locomotion on an autonomous robot with many sensors and actuators. The controller is based on the Subsumption Architecture and is fully distributed over approximately 1500 simple, concurrent processes. The robot, Hannibal, weighs approximately 6 pounds and is equipped with over 100 physical sensors, 19 degrees of freedom, and 8 on board computers. We investigate the following topics in depth: distributed control of a complex robot, insect-inspired locomotion control for gait generation and rough terrain mobility, and fault tolerance. The controller was implemented, debugged, and tested on Hannibal. Through a series of experiments, we examined Hannibal's gait generation, rough terrain locomotion, and fault tolerance performance. These results demonstrate that Hannibal exhibits robust, flexible, real-time locomotion over a variety of terrain and tolerates a multitude of hardware failures.

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Un robot autobalanceado es un dispositivo que, aun teniendo su centro de masas por encima del eje de giro, consigue mantener el equilibrio. Se basa o aproxima al problema del péndulo invertido. Este proyecto comprende el desarrollo e implementación de un robot autobalanceado basado en la plataforma Arduino. Se utilizará una placa Arduino y se diseñará y fabricará con un shield o tarjeta (PCB), donde se incluirán los elementos hardware que se consideren necesarios. Abarca el estudio y montaje del chasis y los sistemas de sensado, control digital, alimentación y motores

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This article introduces an unsupervised neural architecture for the control of a mobile robot. The system allows incremental learning of the plant during robot operation, with robust performance despite unexpected changes of robot parameters such as wheel radius and inter-wheel distance. The model combines Vector associative Map (VAM) learning and associate learning, enabling the robot to reach targets at arbitrary distances without knowledge of the robot kinematics and without trajectory recording, but relating wheel velocities with robot movements.

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This article aims to apply the concepts associated with artificial neural networks (ANN) in the control of an autonomous robot system that is intended to be used in competitions of robots. The robot was tested in several arbitrary paths in order to verify its effectiveness. The results show that the robot performed the tasks with success. Moreover, in the case of arbitrary paths the ANN control outperforms other methodologies, such as fuzzy logic control (FLC).

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A closed-form solution formula for the kinematic control of manipulators with redundancy is derived, using the Lagrangian multiplier method. Differential relationship equivalent to the Resolved Motion Method has been also derived. The proposed method is proved to provide with the exact equilibrium state for the Resolved Motion Method. This exactness in the proposed method fixes the repeatability problem in the Resolved Motion Method, and establishes a fixed transformation from workspace to the joint space. Also the method, owing to the exactness, is demonstrated to give more accurate trajectories than the Resolved Motion Method. In addition, a new performance measure for redundancy control has been developed. This measure, if used with kinematic control methods, helps achieve dexterous movements including singularity avoidance. Compared to other measures such as the manipulability measure and the condition number, this measure tends to give superior performances in terms of preserving the repeatability property and providing with smoother joint velocity trajectories. Using the fixed transformation property, Taylor's Bounded Deviation Paths Algorithm has been extended to the redundant manipulators.

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This research aims to understand the fundamental dynamic behavior of servo-controlled machinery in response to various types of sensory feedback. As an example of such a system, we study robot force control, a scheme which promises to greatly expand the capabilities of industrial robots by allowing manipulators to interact with uncertain and dynamic tasks. Dynamic models are developed which allow the effects of actuator dynamics, structural flexibility, and workpiece interaction to be explored in the frequency and time domains. The models are used first to explain the causes of robot force control instability, and then to find methods of improving this performance.

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This thesis details the development of a model of a seven degree of freedom manipulator for position control. Then, it goes on to discuss the design and construction of a the PHD, a robot built to serve two purposes: first, to perform research on joint torque control schemes, and second, to determine the important dynamic characteristics of the Harmonic Drive. The PHD, is a planar, three degree of freedom arm with torque sensors integral to each joint. Preliminary testing has shown that a simple linear spring model of the Harmonic Drive's flexibility is suitable in many situations.