Experimental evaluation of uncalibrated visual servoing for precision manipulation

Jägersand, Martin; Fuentes, Olac; Nelson, Randal C.

doi:10.1109/robot.1997.606723

Cited by 190 publications

(122 citation statements)

References 20 publications

(43 reference statements)

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“…Explicit minimization of image error is also used in visual servoing where instead of a virtual object real objects are aligned in real scenes. These methods can achieve subpixel errors [6], and have recently been transferred to the AR application [8].…”

Section: Discussionmentioning

confidence: 99%

A Comparison of Viewing Geometries for Augmented Reality

Cobzaş

Jägersand

2003

Image Analysis

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Abstract. Recently modern non-Euclidean structure and motion estimation methods have been incorporated into augmented reality scene tracking and virtual object registration. We present a study of how the choice of projective, affine or Euclidean scene viewing geometry and similarity, affine or homography based object registration affects how accurately a virtual object can be overlaid in scene video from varying viewpoints. We found that projective and affine methods gave accurate overlay to a few pixels, while Euclidean geometry obtained by auto calibrating the camera was not as accurate and gave about 15 pixel overlay error.

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Section: Discussionmentioning

confidence: 99%

A Comparison of Viewing Geometries for Augmented Reality

Cobzaş

Jägersand

2003

Image Analysis

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“…This is similar to the trust region method employed by Jagersand [24] to prevent large motions outside of the estimated model's current area of validity.…”

Section: Practical Implementationmentioning

confidence: 94%

“…An alternative is online estimation of the J matrix using iterative methods such as Broyden's method or recursive nonlinear least squares estimation. Such uncalibrated adaptive methods have been successfully implemented in macro-scale manipulators and mobile robots for a variety of applications with more complex nonlinear system models and higher degrees of freedoms (DOF) [23][24][25]. Experimental results in [20] and [26] show that the J matrix (the relationship between actuation and device velocities) is relatively linear for the experimental system used in this paper.…”

Section: Electromagnetic Actuation For Microrobotic Controlmentioning

confidence: 96%

“…This can be achieved via a quasi-Newton method utilizing an iteratively estimated Jacobian as developed for various macro scale robotic systems in [23][24][25]. Here, we use a dynamic recursive least squares (RLS) method presented in [25] for its improved performance in the presence of system noise and ability to follow moving targets.…”

Section: Recursive Least Squares (Rls) Jacobian Estimation and Controlmentioning

confidence: 99%

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Uncalibrated Visual Servo Control of Magnetically Actuated Microrobots in a Fluid Environment

2014

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Abstract:Microrobots have a number of potential applications for micromanipulation and assembly, but also offer challenges in power and control. This paper describes an uncalibrated vision-based control system for magnetically actuated microrobots operating untethered at the interface between two immiscible fluids. The microrobots are 20 μm thick and approximately 100-200 μm in lateral dimension. Several different robot shapes are investigated. The robots and fluid are in a 20 × 20 × 15 mm vial placed at the center of four electromagnets. Pulse width modulation of the electromagnet currents is used to control robot speed and direction. Given a desired position, a controller based on recursive least square estimation drives the microrobot to the goal without a priori knowledge of system parameters such as drag coefficients or intrinsic and extrinsic camera parameters. Results are verified experimentally using a variety of microrobot shapes and system configurations.

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“…In the image-based visual servoing for tracking a target, the image error between the target feature and the end-effector (or desired target feature) is used to control the robot manipulator [1][2][3][4][5][6][7][8]. In this paper, the robot system is controlled using nonlinear least squares optimization method based on unconstrained optimization problem for the image error.…”

Section: Introductionmentioning

confidence: 99%

Uncalibrated Visual Servoing through the Efficient Estimation of the Image Jacobian for Large Residual

Kim¹

2013

Journal of Electrical Engineering and Technology

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-An uncalibrated visual servo control method for tracking a target is presented. We define the robot-positioning problem as an unconstrained optimization problem to minimize the image error between the target feature and the robot end-effector feature. We propose a method to find the residual term for more precise modeling using the secant approximation method. The composite image Jacobian is estimated by the proper method for eye-to-hand configuration without knowledge of the kinematic structure, imaging geometry and intrinsic parameter of camera. This method is independent of the motion of a target feature. The algorithm for regulation of the joint velocity for safety and stability is presented using the cost function. Adaptive regulation for visibility constraints is proposed using the adaptive parameter.

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Experimental evaluation of uncalibrated visual servoing for precision manipulation

Abstract: In this paper we present an experimental evaluation of adaptive and non-adaptive visual servoing in 3,6

Cited by 190 publications

References 20 publications

A Comparison of Viewing Geometries for Augmented Reality

A Comparison of Viewing Geometries for Augmented Reality

Uncalibrated Visual Servo Control of Magnetically Actuated Microrobots in a Fluid Environment

Uncalibrated Visual Servoing through the Efficient Estimation of the Image Jacobian for Large Residual

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