Coordinated controller design for position based robot visual servoing in Cartesian coordinates

Bell, Gregory; Wilson, William J.

doi:10.1109/robot.1996.506949

Cited by 9 publications

(1 citation statement)

References 9 publications

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“…Position-Based Visual Servoing approaches determine the Cartesian position and/or orientation of the TCP with respect to the target pose ( [10], [11], [12], [13]). Different configurations (camera-in-hand, fixed camera, active head, mono or multi camera system) lead to varying formulations of the control scheme.…”

Section: B Position-based Visual Servoing (Pbvs)mentioning

confidence: 99%

Visual servoing for humanoid grasping and manipulation tasks

Vahrenkamp

Wieland

Azad

et al. 2008

Humanoids 2008 - 8th IEEE-RAS International Conference on Humanoid Robots

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Abstract-Using visual feedback to control the movement of the end-effector is a common approach for robust execution of robot movements in real-world scenarios. Over the years several visual servoing algorithms have been developed and implemented for various types of robot hardware. In this paper, we present a hybrid approach which combines visual estimations with kinematically determined orientations to control the movement of a humanoid arm. The approach has been evaluated with the humanoid robot ARMAR III using the stereo system of the active head for perception as well as the torso and arms equipped with five finger hands for actuation. We show how a robust visual perception is used to control complex robots without any hand-eye calibration. Furthermore, the robustness of the system is improved by estimating the hand position in case of failed visual hand tracking due to lightning artifacts or occlusions. The proposed control scheme is based on the fusion of the sensor channels for visual perception, force measurement and motor encoder data. The combination of these different data sources results in a reactive, visually guided control that allows the robot ARMAR-III to execute grasping tasks in a real-world scenario.

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Section: B Position-based Visual Servoing (Pbvs)mentioning

confidence: 99%

Visual servoing for humanoid grasping and manipulation tasks

Vahrenkamp

Wieland

Azad

et al. 2008

Humanoids 2008 - 8th IEEE-RAS International Conference on Humanoid Robots

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Untitled

Tonko

Nagel

2000

International Journal of Computer Vision

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Learning to grasp by using visual information

Anglani

Taurisano²,

Giuseppe³

et al.

Proceedings 1999 IEEE International Symposium on Computational Intelligence in Robotics and Automation. CIRA'99 (Cat. No.99EX37

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This paper presents a solution to the problem of manipulation control: target identification and grasping.The proposed controller is designed for a real platform in combination with a monocular vision system. The objective of the controller is to learn an optimal policy to reach and to grasp a spherical object of known size, randomly placed in the environment. In order to accomplish this, the task has been treated as a reinforcement problem, in which the controller learns by a trial and error approach the situation-action mapping. The optimal policy is found by using the &-Learning algorithm, a model free reinforcement learning technique, that rewards actions that move the arm closer to the target.The vision system uses geometrical computation to simplify the segmentation of the moving target (a spherical object) and determines an estimate of the target parameters. To speed-up the learning time, the simulated knowledge has been ported on the real platform, an industrial robot manipulator PUMA 560. Experimental results demonstrate the effectiveness of the adaptive controller that does not require an explicit global target position using direct perception of the environment.

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Coordinated controller design for position based robot visual servoing in Cartesian coordinates

Cited by 9 publications

References 9 publications

Visual servoing for humanoid grasping and manipulation tasks

Visual servoing for humanoid grasping and manipulation tasks

Untitled

Learning to grasp by using visual information

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