The role of exploratory movement in visual servoing without calibration

Sutanto, Herry; Sharma, Rajeev; Varma, Venugopal Koikal

doi:10.1016/s0921-8890(97)00052-3

Cited by 24 publications

(14 citation statements)

References 11 publications

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“…From equation (2), the quadratic weighing function can be defined as: (6) which can then be used for expansion in the Taylor series around . After the omission of higher-order terms and the introduction of some approximations (for details, please refer to [9]), the following secant equation is obtained:…”

Section: The Broyden Methodsmentioning

confidence: 99%

Comparison of Uncalibrated Model-Free Visual Servoing Methods for Small-Amplitude Movements: A Simulation Study

Musić

Bonković

Cecić

2014

International Journal of Advanced Robotic Systems

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The paper compares the performance of several methods used for the estimation of an image Jacobian matrix in uncalibrated model-free visual servoing. This was achieved for an eye-in-hand configuration with small-amplitude movements with several sets of system parameters. The tested methods included the Broyden algorithm, Kalman and particle filters as well as the recently proposed population-based algorithm. The algorithms were tested in a simulation environment (Peter Corke's Robotic Toolbox for MATLAB) on a PUMA 560 robot. Several application scenarios were considered, including static point and dynamic trajectory tracking, with several characteristic shapes and three different speeds. Based on the obtained results, conclusions were drawn about the strengths and weaknesses of each method both for a particular setup and in general. Algorithm-switching was introduced and explored, since it might be expected to improve overall robot tracking performance with respect to the desired trajectory. Finally, possible future research directions are suggested.

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Section: The Broyden Methodsmentioning

confidence: 99%

Comparison of Uncalibrated Model-Free Visual Servoing Methods for Small-Amplitude Movements: A Simulation Study

Musić

Bonković

Cecić

2014

International Journal of Advanced Robotic Systems

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“…It shows that adaptively choosing the bandwidth of kernels increases the model estimation accuracy. 6 For the second experiment, we compare the performance of a model-based RL, model-free RL with a conventional linear controller. The problem is defined as visual set-point 6 The result of this experiment is an average of 10 runs.…”

Section: Methodsmentioning

confidence: 99%

“…Several researchers have developed methods for estimating a visual-motor model of the robot (i.e. pose-indexed varying Jacobian) online [4][5] [6] [7]. However, most of these research have been only focused on estimating locally-valid models, and keeping one such at a time.…”

Section: Introductionmentioning

confidence: 99%

Model-based and model-free reinforcement learning for visual servoing

Farahmand

Shademan

Jägersand

et al. 2009

2009 IEEE International Conference on Robotics and Automation

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Abstract-To address the difficulty of designing a controller for complex visual-servoing tasks, two learning-based uncalibrated approaches are introduced. The first method starts by building an estimated model for the visual-motor forward kinematic of the vision-robot system by a locally linear regression method. Afterwards, it uses a reinforcement learning method named Regularized Fitted Q-Iteration to find a controller (i.e. policy) for the system (model-based RL). The second method directly uses samples coming from the robot without building any intermediate model (model-free RL). The simulation results show that both methods perform comparably well despite not having any a priori knowledge about the robot.

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“…In previous work [16], we carried out experiments comparing the results obtained using one of the cameras and those obtained using two cameras: our results showed that using two cameras instead of one improved the behaviour of the all methods we tested. In many applications, improvement on the performance justifies the [18] gathers diverse methods to estimate the image Jacobian, Two of them are described in this section, the first method was designed by the authors and is based on incorporating the epipolar constraint of the system [16], the second method is based on the recursive updating of the Jacobian considering a covariance matrix with a forgetting factor [14], due to its good results in past works [13] [16] [17] this method is included into the tests and is described below. It is worth also mentioning the Kalman method where the system is modelled by its state variables which are updated using Kalman filter equations [15], the Broyden method that recursively update the Jacobian by using the last movement and the previous Jacobian [5].…”

Section: A Multiple View Jacobianmentioning

confidence: 99%

A comparative study between analytic and estimated image Jacobian by using a stereoscopic system of cameras

Pari

Sebastián

Traslosheros

et al. 2010

2010 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-This paper describes a comparative study of performance between the estimated image Jacobian that come from taking into account the epipolar geometry in a system of two cameras, and the well known analytic image Jacobian that is utilized for most applications in visual servoing. Image Based Visual Servoing architecture is used for controlling a 3 DOF articular system using two cameras in eye to hand configuration. Tests in static and dynamic cases were carried out, and showed that the performance of estimated Jacobian by using the properties of the epipolar geometry is such as good and robust against noise as the analytic Jacobian. This fact is considered as an advantage because the estimated Jacobian does not need laborious previous work prior to control task in contrast to the analytic Jacobian does.

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The role of exploratory movement in visual servoing without calibration

Cited by 24 publications

References 11 publications

Comparison of Uncalibrated Model-Free Visual Servoing Methods for Small-Amplitude Movements: A Simulation Study

Comparison of Uncalibrated Model-Free Visual Servoing Methods for Small-Amplitude Movements: A Simulation Study

Model-based and model-free reinforcement learning for visual servoing

A comparative study between analytic and estimated image Jacobian by using a stereoscopic system of cameras

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