Augmented Imaged Based Visual Servoing controller for a 6 DOF manipulator using acceleration command

Keshmiri, Mohammad; Xie, Wen

doi:10.1109/cdc.2012.6426890

Cited by 12 publications

(9 citation statements)

References 17 publications

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“…Usually the depth parameter Z in the image Jacobian matrix is assumed to be known [27]. However, in the mono-camera eye-in-hand configuration, it is difficult to measure the depth on-line.…”

Section: Tp Model Transformationmentioning

confidence: 99%

On–Line Model Predictive Control for Constrained Image Based Visual Servoing of a Manipulator

Hajiloo¹,

Keshmiri²,

Xie³

2015

2015 Proceedings of the Conference on Control and Its Applications

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This paper presents an on-line image based visual servoing (IBVS) controller for a 6 DOF robotic system based on the robust model predictive control (RMPC) method. The controller is designed considering the robotic visual servoing system's input and output constraints, such as robot physical limitations and visibility constraints. The proposed IBVS controller avoids the inverse of the image Jacobian matrix and hence can solve the intractable problems for the classical IBVS controller, such as large displacements between the initial and the desired positions of the camera. To verify the effectiveness of the proposed algorithm, real-time experimental results on a 6 Degrees-of-Freedom (DOF) robot manipulator with eye-in-hand configuration are presented and discussed.

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Section: Tp Model Transformationmentioning

confidence: 99%

On–Line Model Predictive Control for Constrained Image Based Visual Servoing of a Manipulator

Hajiloo¹,

Keshmiri²,

Xie³

2015

2015 Proceedings of the Conference on Control and Its Applications

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“…A controller is required to follow the desired path. A PD controller with acceleration output is used to ensure both the position matching and the velocity matching of the object [21]. To design the controller, the relation between the robots end effector acceleration and the features is required.…”

Section: Problem Description and Modellingmentioning

confidence: 99%

“…We will take the advantage of the navigation guidance speed to track and catch a fast manoeuvring moving object smoothly in viusal seroving. The path created by the navigation guidance will be followed by an augmented image based visual servoing system called AIBVS [21] which can achieve smooth and linear feature trajectory in image space and owns the robustness with respect to camera and robots calibration errors. Finally, the simulation results are presented to validate the effectiveness of the proposed controller.…”

Section: Introductionmentioning

confidence: 99%

Catching moving objects using a Navigation Guidance technique in a robotic Visual Servoing system

Keshmiri

Xie

2013

2013 American Control Conference

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In this paper, a combination of Navigation Guidance algorithm with an Augmented Imaged Based Visual Servoing (AIBVS) strategy is proposed to perform a moving object catching with fast manoeuvrability. An eye-in-hand vision system is utilized with a 6DOF robotic manipulator. Navigation guidance algorithms are usually exploited in moving object interceptions specially for military purposes such as following and colliding with missile and aircraft. In this paper, we have modified and applied these methods to a robotic system to catch a moving object with different motions. An imaged based catching controller is proposed using a modified navigation guidance algorithm in a robotic visual servoing system. The simulation results are presented for catching a moving object with three different motions of constant velocity, sinusoidal and a thrown object.

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“…Visual servoing uses visual feedback to control a robot to accomplish some tasks such as stabilization [1][2][3], trajectory tracking [4,5], eye-hand coordination [6], and grasping [7]. Traditional visual servoing is mainly for industrial manipulators [8][9][10] in which the characteristics of vision sensors, such as the unknown depth information and low sampling rate, are considered in a background of control design for holonomic systems.…”

Section: Introductionmentioning

confidence: 99%

Visual servoing of mobile robots for posture stabilization: from theory to experiments

Zhang

Sun

2013

Intl J Robust & Nonlinear

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On the basis of the kinematic model of a unicycle mobile robot in polar coordinates, an adaptive visual servoing strategy is proposed to regulate the mobile robot to its desired pose. By regarding the unknown depth as model uncertainty, the system error vector can be chosen as measurable signals that are reconstructed by a motion estimation technique. Then, an adaptive controller is carefully designed along with a parameter updating mechanism to compensate for the unknown depth information online. On the basis of Lyapunov techniques and LaSalle's invariance principle, rigorous stability analysis is conducted. Because the control law is elegantly designed on the basis of the polar-coordinate-based representation of error dynamics, the consequent maneuver behavior is natural, and the resulting path is short. Experimental results are provided to verify the performance of the proposed approach.The vision-based robotic system is composed of a mobile robot and an onboard camera fixed on a pan motion platform. As shown in Figure 1, the robot frame F R is attached to the center of the wheel axis, which is defined as the Y R axis, while the Z R axis is perpendicular to the motion plane of the mobile robot, and the X R axis can be then obtained easily for a standard right-handed coordinate system. The camera frame F C is defined such that the camera center O C lies in the Z R axis and the frames F R and F C are parallel to each other when the rotation angle of the pan camera is zero. The From the previous analysis, it is clear that the largest invariant set M only consists of the equilibrium point in the sense that‡ It should be noted that although P O c 0 .t/ is, as can be seen from (15), merely piecewise smooth because of the usage of the projection function, it is however continuous with respect to initial conditions. Then, on the basis of Lemma 1 in [32], we can conclude that the positive limit L C of P O c 0 .t/ is invariant, which thus makes LaSalle's invariance principle applicable to the closed-loop error system of (20).

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Augmented Imaged Based Visual Servoing controller for a 6 DOF manipulator using acceleration command

Cited by 12 publications

References 17 publications

On–Line Model Predictive Control for Constrained Image Based Visual Servoing of a Manipulator

On–Line Model Predictive Control for Constrained Image Based Visual Servoing of a Manipulator

Catching moving objects using a Navigation Guidance technique in a robotic Visual Servoing system

Visual servoing of mobile robots for posture stabilization: from theory to experiments

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