نتایج جستجو برای Task-Space Control

تعداد نتایج: 1407281  

Actuators of robot operate in the joint-space while the end-effect or of robot is controlled in the task-space. Therefore, designing a control system for a robotic system in the task-space requires the jacobian matrix information for transforming joint-space to task-space, which suffers from uncertainties. This paper deals with the robust task-space control of electrically driven robot manipula...

In this paper, a task-space controller for electrically driven robot manipulators is developed using a robust control algorithm. The controller is designed using voltage control strategy. Based on the nominal model of the robotic arm, the desired signals for motor currents are calculated and then the voltage control law is proposed based on the current errors and motor nominal electrical model....

In this paper, a task-space controller for electrically driven robot manipulators is developed using a robust control algorithm. The controller is designed using voltage control strategy. Based on the nominal model of the robotic arm, the desired signals for motor currents are calculated and then the voltage control law is proposed based on the current errors and motor nominal electrical model....

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 estimat...

Journal: :Automatica 2013
Xiang Li, Chien Chern Cheah,

Task-space feedback information such as visual feedback is used in many modern robot control systems as it improves robustness to model uncertainty. However, existing task-space feedback control schemes are only valid locally in a finite task space within a limited sensing zone where the singularity of the Jacobian matrix can be avoided. The global stability problem of task-space control system...

2011
Nikolay Jetchev, Marc Toussaint,

Learning complex skills by repeating and generalizing expert behavior is a fundamental problem in robotics. A common approach is learning from demonstration: given examples of correct motions, learn a policy mapping state to action consistent with the training data. However, the usual approaches do not answer the question of what are appropriate representations to generate motions for specific ...

2009
Mohammad Mehdi Fateh, Mohammad Reza Soltanpour,

Robust control approaches have been extensively developed to control robot manipulators in joint-space. Even though they can present perfect tracking performances in joint-space, they cannot provide satisfactory performances in workspace under imperfect transformation of control space. In addition, many task-space approaches have assumed the perfect transformation, which is not real with presen...

Journal: :journal of ai and data mining 2015
m. m. fateh, s. azargoshasb,

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 estimat...

2011
Jörg Stückler, Sven Behnke,

In this paper, we propose a new approach to compliant taskspace control for high degree-of-freedom manipulators driven by positioncontrolled actuators. The actuators in our approach are back-drivable and allow to limit the torque used for position control. Traditional approaches frequently achieve compliance through redundancy resolution. Our approach not only allows to adjust compliance in the...

2017
Karim Bouyarmane, Joris Vaillant, Kévin Chappellet, Abderrahmane Kheddar,

We extend the task-space multi-objective controllers that write as quadratic programs (QP) to handle multi-robot systems as a single centralized control. The idea is to assemble all the ‘robots’ models and their interaction task constraints into a single QP formulation. By multi-robot we mean that whatever entities a given robot will interact with (solid or articulated systems, actuated or not ...

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