Conferences related to Visual servoing

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2020 59th IEEE Conference on Decision and Control (CDC)

The CDC is the premier conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.


2020 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and severalco-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students, academics and industry researchers.

  • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conferenceand 27co-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students,academics and industry.

  • 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    computer, vision, pattern, cvpr, machine, learning

  • 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. Main conference plus 50 workshop only attendees and approximately 50 exhibitors and volunteers.

  • 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Topics of interest include all aspects of computer vision and pattern recognition including motion and tracking,stereo, object recognition, object detection, color detection plus many more

  • 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Sensors Early and Biologically-Biologically-inspired Vision, Color and Texture, Segmentation and Grouping, Computational Photography and Video

  • 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics, motion analysis and physics-based vision.

  • 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics,motion analysis and physics-based vision.

  • 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2007 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2006 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2005 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)


2020 IEEE International Conference on Robotics and Automation (ICRA)

The International Conference on Robotics and Automation (ICRA) is the IEEE Robotics and Automation Society’s biggest conference and one of the leading international forums for robotics researchers to present their work.


2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.


2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)

The Conference focuses on all aspects of instrumentation and measurement science andtechnology research development and applications. The list of program topics includes but isnot limited to: Measurement Science & Education, Measurement Systems, Measurement DataAcquisition, Measurements of Physical Quantities, and Measurement Applications.


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Periodicals related to Visual servoing

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Aerospace and Electronic Systems Magazine, IEEE

The IEEE Aerospace and Electronic Systems Magazine publishes articles concerned with the various aspects of systems for space, air, ocean, or ground environments.


Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...


Automation Science and Engineering, IEEE Transactions on

The IEEE Transactions on Automation Sciences and Engineering (T-ASE) publishes fundamental papers on Automation, emphasizing scientific results that advance efficiency, quality, productivity, and reliability. T-ASE encourages interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, operations research, and other fields. We welcome results relevant to industries such as agriculture, biotechnology, healthcare, home automation, maintenance, manufacturing, pharmaceuticals, retail, ...


Circuits and Systems for Video Technology, IEEE Transactions on

Video A/D and D/A, display technology, image analysis and processing, video signal characterization and representation, video compression techniques and signal processing, multidimensional filters and transforms, analog video signal processing, neural networks for video applications, nonlinear video signal processing, video storage and retrieval, computer vision, packet video, high-speed real-time circuits, VLSI architecture and implementation for video technology, multiprocessor systems--hardware and software-- ...


Control Systems Technology, IEEE Transactions on

Serves as a compendium for papers on the technological advances in control engineering and as an archival publication which will bridge the gap between theory and practice. Papers will highlight the latest knowledge, exploratory developments, and practical applications in all aspects of the technology needed to implement control systems from analysis and design through simulation and hardware.


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Xplore Articles related to Visual servoing

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Is 3D useful in stereo visual control?

Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292), 2002

The main goal of this paper, is the study of image-based stereo visual servoing. A pair of cameras is mounted on the end-effector of the manipulator arm. The visual features are the pair of images of an unknown object. The developed control laws use either the raw image points, or the estimated 3D coordinates. The experimental setup is challenging: large ...


Motion control using visual servoing and potential fields for a rover-mounted manipulator

Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C), 1999

Presents the motion control for our mobile robot Hilare2Bis using both visual servoing and potential fields in a, cluttered indoor environment. This function is required in order to execute navigation tasks in a robust way. The camera is mounted on the robot close to the end effector of an arm with 6 DOF, used as a virtual pan and tilt ...


Experimental evaluation of fixed-camera direct visual controllers on a direct-drive robot

Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146), 1998

Addresses the visual servoing of robot manipulators in fixed-camera configuration. We present the experimental evaluation of three direct visual servo controllers on a planar two degrees of freedom direct-drive robot arm. These visual servo controllers belong to the family of transpose Jacobian- based control schemes yielding local asymptotic stability.


Modular neural-visual servoing using a neural-fuzzy decision network

Proceedings of International Conference on Robotics and Automation, 1997

Visual servoing is a growing research area. One of the key problems of feature based visual servoing is calculating the inverse Jacobian, relating change in features to change in robot position. Neural networks can learn to approximate the inverse feature Jacobian. However, the neural network approach can only approximate the feature Jacobian for a small workspace. In order to overcome ...


Visual servoing using image moments and Nonlinear State Error Feedback control law

2010 Chinese Control and Decision Conference, 2010

For the purpose of realizing 6 DOF robot's visual servoing, we choose image moments,which is a kind of global image features, to construct task functions, and present the analytical form of the interaction matrix, also in order to solve the difficulties of acquiring the depth information of the target object, we choose moments of desired image to replace the translation ...


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Educational Resources on Visual servoing

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IEEE-USA E-Books

  • Is 3D useful in stereo visual control?

    The main goal of this paper, is the study of image-based stereo visual servoing. A pair of cameras is mounted on the end-effector of the manipulator arm. The visual features are the pair of images of an unknown object. The developed control laws use either the raw image points, or the estimated 3D coordinates. The experimental setup is challenging: large rotations are involved, images are noisy, and cameras are coarsely calibrated. In this setup, the trajectory of the end-effector differs notably, sometimes leading the arm near its joint range limits. Experimental results demonstrate that using pixel coordinates is disadvantageous, compared with 3D coordinates estimated from the same pixel data.

  • Motion control using visual servoing and potential fields for a rover-mounted manipulator

    Presents the motion control for our mobile robot Hilare2Bis using both visual servoing and potential fields in a, cluttered indoor environment. This function is required in order to execute navigation tasks in a robust way. The camera is mounted on the robot close to the end effector of an arm with 6 DOF, used as a virtual pan and tilt platform: only two DOFs are controlled (/spl theta//sub pan/, /spl theta//sub tilt/) by the visual servoing process. The mobile platform is controlled according to the position of some features in an image, and to the distance to the obstacles detected by a 2D laser range finder.

  • Experimental evaluation of fixed-camera direct visual controllers on a direct-drive robot

    Addresses the visual servoing of robot manipulators in fixed-camera configuration. We present the experimental evaluation of three direct visual servo controllers on a planar two degrees of freedom direct-drive robot arm. These visual servo controllers belong to the family of transpose Jacobian- based control schemes yielding local asymptotic stability.

  • Modular neural-visual servoing using a neural-fuzzy decision network

    Visual servoing is a growing research area. One of the key problems of feature based visual servoing is calculating the inverse Jacobian, relating change in features to change in robot position. Neural networks can learn to approximate the inverse feature Jacobian. However, the neural network approach can only approximate the feature Jacobian for a small workspace. In order to overcome this problem, we propose using a modular approach, where several networks are trained over a small area. Furthermore, we use a neural-fuzzy counterpropagation network to decide which subspace the robot is currently occupying. The neural fuzzy network provides smoother transitions between subspaces than hard switching. Preliminary results of the system's operation are also presented.

  • Visual servoing using image moments and Nonlinear State Error Feedback control law

    For the purpose of realizing 6 DOF robot's visual servoing, we choose image moments,which is a kind of global image features, to construct task functions, and present the analytical form of the interaction matrix, also in order to solve the difficulties of acquiring the depth information of the target object, we choose moments of desired image to replace the translation part of the interaction matrix. Then the robustness of the Nonlinear State Error Feedback control law was analysed theorically. Finally the simulation experimental results we present show the effectiveness of moment features and the robustness of Nonlinear State Error Feedback(NLSEF) control law.

  • Improving visual servoing using fuzzy filters

    A new approach to improve visual servoing based on fuzzy filters is proposed in this paper. In visual servoing the speed of convergence depends on a constant gain, that directly influences the velocity of the robot manipulator joints. This velocity can achieve undesired behavior due to the intrinsically discrete visual servoing and when regulator control is used. In this paper, the image features error is filtered by means of fuzzy filters, to improve the behavior of the robot joint velocities. Simulation results are presented for a 6 degrees of freedom (DOF) eye-in-hand system, that demonstrates the efficiency of the proposed approach. Experimental results are also presented when a 2 DOF robot manipulator performs kinematic visual servoing, moving to a pre-defined image features position.

  • Visual Servoing Control Based on EGM Interface of an ABB Robot

    This paper introduces a new visual servoing controller based on the (External Guided Motion, EGM) interface of ABB robots, with the emphasis on its adaptability to different feedback frequency without sacrificing cycle time and accuracy. Previous researches on visual servoing focused primarily on improving controllers range of stability and robustness to system errors. However, in industrial applications, besides the accuracy and stability of the system, the cost and the efficiency should also be taken into consideration. In practice, the cost of a camera is closely related to its frame rate. Hence, a visual servoing controller is expected to work with an image stream of low frame rate to save cost, while the speed and the accuracy of an operation are still maintained. With the feedback of robot's information from an External Guided Motion (EGM) interface, the performances of the visual servoing controller for the ABB robots under different camera frame rate can be maintained on an optimal level. The cycle times of picking operation and accuracies of tracking with different camera frame rate (from 16Hz to 200Hz) are compared in experiments to validate the effectiveness of the newly proposed controller.

  • Robot vision tracking with a hierarchical CMAC controller

    Vision has extensively expanded robots' capabilities, making the robot control problem more complex. To track a target with a robot arm in a three- dimensional space involves the use of precise commands. We propose to insert a hierarchical neurocontroller based on CMAC (cerebellar model articulation controller) networks in a visual servoing loop. This hierarchical structure splits the robot's workspace and assigns different CMAC controllers imposing thus a specialized region CMAC. Compared to a single CMAC with the same number of weights, the neurocontroller's sensitivity and precision is increased. Robot positioning and target tracking with visual feedback can then be done with a better precision.

  • Visual servoing utilizing zoom mechanism

    A camera, which is used as an artificial vision in visual servoing control, often has a zoom mechanism. A zoom mechanism cannot realize fast motion while an arm mechanism can, and it has only one degree of freedom. On the other hand the arm mechanism cannot cover wide range of change of images while the zoom mechanism can. In this paper, we propose a complementary visual servoing controller of zoom and arm mechanisms. First we discuss on the condition that camera position and zoom setting are considered as redundant. Then a visual servoing controller is proposed making use of complementary characteristics of the both mechanisms. To show the effectiveness of the proposed controller, experimental results are shown.

  • An experimental study of predictors for visual servoing

    In order to perform visual servoing tasks in a robotic system, one is confronted with the low sampling rate of standard cameras and the time delay introduced by image acquisition and processing. One way to circumvent the above problems is to estimate future positions of a moving object employing prediction techniques. In this work, three prediction techniques, namely Kalman filtering and two adaptive techniques employing least squares with forgetting factor and the projection algorithm respectively, are evaluated in terms of their prediction error and speed of convergence. Experimental results show that the adaptive technique employing the projection algorithm gives best results.



Standards related to Visual servoing

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