Design of an filter-based robust visual servoing system

Kawabata, Akiko; Fujita, Masayuki

doi:10.1016/s0967-0661(98)00010-0

Cited by 14 publications

(3 citation statements)

References 13 publications

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“…Their analyses were based on openloop LTI responses where the filters were designed for a nominal condition and tested for a second off-nominal LTI plant for robustness analysis. An empirical evaluation of an estimation algorithm based on H N filtering techniques was applied in Kawabata and Fujita (1998) to a 2-D visual servoing tracking of a moving target with good results for fast parameters variations.…”

Section: Literature Surveymentioning

confidence: 99%

An application of fault detection and isolation to a transport aircraft

Marcos

Ganguli

Balas

2005

Control Engineering Practice

122

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Section: Literature Surveymentioning

confidence: 99%

An application of fault detection and isolation to a transport aircraft

Marcos

Ganguli

Balas

2005

Control Engineering Practice

122

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“…Some researches have been conducted on the use of vision information in the dynamic feedback loop [3][4]. A few works have been reported toward the use of vision information for tracking [5][6][7][8]. In order to track the motion of the object in uncertain and dynamic environments, the adaptive control approaches are effective to inaccurate and unknown dynamics, and have been studied in the literature [9][10].…”

Section: Introductionmentioning

confidence: 99%

Neural-PID visual tracking of moving object

Cheng

2011

Proceedings of 2011 International Conference on Electronics and Optoelectronics

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In this paper, an adaptive approach is presented to nonlinear system for real-time robotic visual tracking of a moving polyhedral object. A light stripe vision system consists of a laser-stripe sensor and a CCD the camera fixed to robot end-effector, and projects planar light on the polyhedral object.The geometric conditions can be provided to assure location of features of the polyhedral faces. The objective is to predict the location of features of the object on the image plane based on the light stripe vision system and then to determine an optimal control input that will move the camera so that the image features align with their desired positions. We first give the equations of observation and state-space by using the motion rules of the camera and the object. Then, the system can be represented as an MIMO ARMAX model and an efficient estimation model. The estimation model can process on-line estimation of the 3D related parameters between the camera and the object. Those parameters are used as on-line train values of neural network. The control scheme adopts a neural-PID controller that can adjust the PID controller parameters. The paper concludes with the simulation results and the computer simulation shows that the proposed method is effective to visual tracking of combining vision and control.

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“…Since a linear Jacobian matrix is used to describe approximately the nonlinear mapping between the position error in the image space and the robotic control, the Jacobian matrix is changing and needs an online real-time estimation in the whole workspace during the whole task [3], [4]. Although in some cases the changes of the image Jacobian matrix do not affect the task process much so that a constant image Jacobian matrix is acceptable [5], [6], an accurate estimation of the Jacobian matrix online, evidently, is the key to the effectiveness of this kind of approach [7].…”

Section: Introductionmentioning

confidence: 99%

Calibration-free robotic eye-hand coordination based on an auto disturbance-rejection controller

Qiu

et al. 2004

IEEE Trans. Robot.

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Abstract-This paper addresses the calibration-free robotic eye-hand coordination in a way other than the conventional image Jacobian matrix approach that has been studied extensively in literature. A nonlinear mapping rather than the linear mapping used in the image Jacobian matrix between the image space and the robotic control space is proposed. This mapping is regarded as the system's unmodeled dynamics expressed in system state equations. An extended state observer is designed first to estimate the unmodeled dynamics as well as the external disturbance of the system. With the estimation results as the compensation, a system controller is designed based on the nonlinear state-error feedback control strategy. Convergence of the extended state observer as well as the overall controller for a typical eye-hand coordination system is proved. Compared with the conventional calibration-free robotic eye-hand coordination with a Jacobian matrix, the proposed controller is independent of specific tasks and system configurations. Thus, a general design procedure is proposed for the calibration-free robotic eye-hand coordination. Simulation and experiment results demonstrate the satisfactory performance and effectiveness of the proposed approach.

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Design of an filter-based robust visual servoing system

Cited by 14 publications

References 13 publications

An application of fault detection and isolation to a transport aircraft

An application of fault detection and isolation to a transport aircraft

Neural-PID visual tracking of moving object

Calibration-free robotic eye-hand coordination based on an auto disturbance-rejection controller

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