Robust visual servoing in 3-D reaching tasks

Grosso, Enrico; Metta, Giorgio; Oddera, Andrea; Sandini, Giulio

doi:10.1109/70.538977

Cited by 58 publications

(22 citation statements)

References 17 publications

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“…Learning with spatially localized basis function [4], [16], [17] has been studied for many years in contrast to the learning with the global basis function [15]. A lot of applications have been accumulated such as robot control [6], chemical process modeling [7], nonlinear system estimation and control [8], image coding [18] and pattern recognition [9], [12], etc.…”

Section: Incremental Learning With Balanced Update On Receptive Fieldmentioning

confidence: 99%

“…Although online control is easy to implement, the offline calibration process is complicated and error-prone to realize in engineering [20]- [22]. The image Jacobian matrix-based uncalibrated coordination avoids the offline system calibration [16]. All modeling and control rely on online computation [23] and require intelligent estimation and control skills so that the model should be as simple as possible.…”

Section: Introductionmentioning

confidence: 99%

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Nonlinear Visual Mapping Model for 3-D Visual Tracking With Uncalibrated Eye-in-Hand Robotic System

Yang

Hanebeck³

et al. 2004

IEEE Trans. Syst., Man, Cybern. B

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Abstract-A new control scheme for uncalibrated robotic visual tracking problem is proposed that compromises the computational expenses of overall system with offline modeling and online control. A nonlinear visual mapping model for the uncalibrated hand-eye coordination is first proposed with an artificial neural network implementation. An online visual tracking controller is then developed together with a real-time motion planner. To improve the system performance, the control scheme is also integrated with a feedforward controller to compensate unknown object motions. Extensive simulations and experiments demonstrate the effectiveness of the proposed control scheme.Index Terms-Hand/eye coordination, image Jacobian matrix, neural networks, nonlinear mapping.

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Section: Incremental Learning With Balanced Update On Receptive Fieldmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Nonlinear Visual Mapping Model for 3-D Visual Tracking With Uncalibrated Eye-in-Hand Robotic System

Yang

Hanebeck³

et al. 2004

IEEE Trans. Syst., Man, Cybern. B

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show abstract

“…where K = b/sin(θ ), b is the baseline length, α is the focal length of the cameras, and x r − x l the binocular disparity [29]. Note that Eq.…”

Section: Direct Disparity Estimationmentioning

confidence: 99%

Disparity Estimation on Log-Polar Images and Vergence Control

Manzotti

Γαστεράτος

Metta

et al. 2001

Computer Vision and Image Understanding

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An important issue in the realization of an autonomous robot with stereoscopic vision is the control of vergence. Together with version, it determines uniquely the position of the fixation point in space. Vergence control is directly related to both depth perception and binocular fusion. Previous works in this field employed either a measure of correlation of stereo images or some kind of disparity-related estimate. In this paper, we present a new method of extracting a global disparity measure for vergence control, which does not require a priori segmentation of the object of interest. Our method uses images acquired by retina-like sensors and, therefore, the computation is performed in the log-polar plane. The technique we present here is: (i) global, in the sense that it is an integral measure over the whole image, (ii) computationally inexpensive, considering that the goal was to use it in the robot control loop rather than to accurately measure some 3D world features. Moreover, the proposed technique is robust and independent of the average illumination as well as of other features of the target such as size, shape, and direction of motion. It provides a precise and linear estimate of the vergence error, which is the only requirement from the control point of view. Several experimental results on a real robotic setup demonstrate the effectiveness of the proposed technique.

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“…Zhuang [16] and Vischer [17] used a theodolite and a 3D coordinate measuring machine to measure the full pose error of a robot, respectively; however, the measurement process is extremely complex, which leads to a reduction in practicability. Grosso [18] and Hager [19] presented a measurement scheme utilizing two cameras to capture a 3D image, which makes it difficult to meet the accuracy requirements of robot calibration. To complete the full pose error measurement in a simple way with less time cost, the most commonly used method is to measure three or more reference points fixed on the end-effector and then the pose error can be computed [20,21].…”

Section: Introductionmentioning

confidence: 99%

Kinematic Calibration Based on the Multicollinearity Diagnosis of a 6-DOF Polishing Hybrid Robot Using a Laser Tracker

Zhang

Dong

Guo

et al. 2018

Mathematical Problems in Engineering

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A general methodology for ensuring the geometric accuracy of a 6-DOF polishing hybrid robot having a 3UPS and UP parallel mechanism and a 3-DOF wrist is presented. The process is implemented in three steps: formulation of the error model containing complete source errors such as offset errors of the actuated joints and structural errors of the joints and links utilizing product of exponentials formula and screw theory. Measurement of the full pose error twist with a specially designed measurement tool having three reference points was undertaken. Identification of the source errors by a stepwise identification strategy to overcome the ill-conditioned problem arising from the multicollinearity and development of a linearized error compensator was completed. An experiment has been carried out on the prototype, and the results show that, after calibration, a position volumetric error of 0.07 mm and an orientation error of 0.07 degrees can be achieved over the cubic task workspace with repeatability of 0.016 mm and 0.010 degrees.

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Robust visual servoing in 3-D reaching tasks

Cited by 58 publications

References 17 publications

Nonlinear Visual Mapping Model for 3-D Visual Tracking With Uncalibrated Eye-in-Hand Robotic System

Nonlinear Visual Mapping Model for 3-D Visual Tracking With Uncalibrated Eye-in-Hand Robotic System

Disparity Estimation on Log-Polar Images and Vergence Control

Kinematic Calibration Based on the Multicollinearity Diagnosis of a 6-DOF Polishing Hybrid Robot Using a Laser Tracker

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