Uncalibrated Image-Based Robotic Visual Servoing (knowdiff.net)
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Visiting Lecturer Program (140) Speaker: Azad Shademan Ph.D. candidate Department of Computing Sciences University of Alberta, Canada Title: Uncalibrated Image-Based Robotic Visual Servoing Local Host: Ms. Nasim Pouraryan Time: Wednesday, November 5, 2008, 12:30-2:00 pm Location: Faculty of Electrical and Computer Engineering, University of Tehran, Tehran Abstract: Design of versatile vision-based robotic systems demands a solution with little or no dependence on system parameters. The problem of real-time vision-based control of robots has been long studied as robotic visual servoing. Most provably stable solutions to this problem require calibrated kinematic and camera models, because in a precisely calibrated system one can model the visual-motor function analytically. The uncalibrated approach has received limited attention mainly because the stability analysis is not as straightforward as that of calibrated image-based architecture. In an uncalibrated system the visual-motor function is not known, but partial derivative information (Jacobian) can be learned by tracking visual measurements during motion. In this talk, we study the uncalibrated image-based visual servoing and present different Jacobian learning methods.
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(2) Location: Room 212, School of Electrical and Computer Engineering of University of Tehran
Abstract:
Investigating low light imaging is of high importance in the field of color science from different perspectives. One of the most important challenges arises at low light levels is the issue of noise, or more generally speaking, low signal to noise ratio. In the present work, effects of different image sensor noises such as: photon noise, dark current noise, read noise, and quantization error are investigated on low light color measurements. In this regard, a typical image sensor is modeled and employed for this study. A detailed model of noise is considered in the process of implementing the image sensor model to guarantee the precision of the results. Several experiments have been performed over the implemented framework and the results show that: first, photon noise, read noise, and quantization error lead to uncertain measurements distributed around the noise free measurements and these noisy samples form an elliptical shape in the chromaticity diagram; second, even for an ideal image sensor, in very dark situations, stable measuring of color is impossible due to the physical limitation imposed by the fluctuations in photon emission rate; third, dark current noise reveals dynamic effects on color measurements by shifting their chromaticities towards the chromaticity of the camera black point; fourth, dark current dominates the other sensor noise types in the image sensor in terms of affecting measurements. Moreover, an SNR sensitivity analysis against the noise parameters is presented over different light intensities.
Sara Afshar: Scheduling and Resource Sharing in Multiprocessor Real-Time Systems
PhD Candidate,
Department of Computer science
Mälardalen University
Time: Tuesday, Dec. 30, 2014, 11:30 a.m.
Location: Computer Engineering Department, Urmia University
Abstract:
The processor is the brain of a computer system. Usually, one or more programs run on a processor where each program is typically responsible for performing a particular task or function of the system. The performance of all the tasks together results in the system functionality. In many computer systems, it is not only enough that all tasks deliver correct output, but it is also crucial that these activities are delivered in a proper time. This type of systems that have timing requirements are known as real-time systems. A scheduler is responsible for scheduling all tasks on the processor, i.e., it dictates which task to run and when to run to ensure that all tasks are carried out on time. Typically, such tasks/programs need to use the computer system’s hardware and software resources to perform their calculation. Examples of such type of resources that are shared among programs are I/O devices, buffers and memories. Technology that is used for the management of shared resources is known as resource sharing synchronization protocol.
In recent years, a shift from single-processor platforms to multiprocessor platforms has become inevitable due to availability of processor chips and requirements on increased performance. Scheduling and resource sharing protocols have been well studied for uniprocessor systems. However, in the context of multiprocessors, still such techniques are not fully mature. The shift towards multi-core technology has revealed the demand for real-time scheduling algorithms along with synchronization protocols to support real-time applications on multiprocessors, both with and without dependencies.
In this talk, we first have an introduction to real-time embedded systems. Next, we look at scheduling and resource sharing policies in uniprocessor platforms. Further, we discuss the extension of scheduling and resource sharing policies for multiprocessor platforms and present the recent challenges arisen in this context.
Biography:
Sara Afshar is a PhD student at Mälardalen University. She has received her B.Sc. degree in Electrical Engineering from Tabriz University, Iran in 2002. She worked at different engineering companies until 2009. In the year 2010 she started her M.Sc. in Embedded Systems at Mälardalen University. She obtained her Master degree in 2012 and at the same year she started her PhD studies in Mälardalen University. Currently she is working on the topic of resource sharing in multiprocessor systems. She is part of the Complex Real-Time Embedded Systems group at Mälardalen University.
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University College London (UCL)
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Location: Energy Engineering Dept., Ghasemi Ave., (North wing of Sharif University of Technology). - Ground Floor - Seminar Room 1
Abstract:
The topic of “sustainability” need to be analyzed by considering the impact of such diverse sectors as energy, material, natural resources and climate systems. The important point is that due to the “hyperconnectivity” among these sectors, ignoring their interactions, dependencies, and links in transition pathways can produce catastrophic results. For this reason, some recent studies have suggested the “nexus” approach for analyzing and modelling low-carbon future scenarios. In general, in a large-scale “nexus” approach, the system deals with complexities and feedback mechanisms resulting from the interactions of diverse sectors such as climate, energy, materials, land and water. However, for this project, the primary focus is on the interaction of material and energy as an inter-sectoral segment of the nexus approach.
In this project, the goals are to (a) model the use of materials within the transition pathways generated for a low-carbon future and (b) compare the required material flow in these low-carbon pathways with the material flow in the based projections.
Some of the applications and advantages of this research include:
• Providing science-based support for policy makers regarding the required materials for low-carbon energy systems.
• Considering realistic uncertainties associated with the material flow inside energy systems and applying appropriate probabilistic methods.
• Advancing TIAM-UCL by adding the material flow module. TIAM-UCL encompasses 16 global regions and this additional module could provide a more complete analysis regarding the distribution of required material resources within energy systems, which would generate favorable options for trade and also reduce the cost of welfare.
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knowdiff.net
Design of versatile vision-based robotic systems demands a solution with little or no dependence on system parameters. The problem of real-time vision-based control of robots has been long studied as robotic visual servoing. Most provably stable solutions to this problem require calibrated kinematic and camera models, because in a precisely calibrated system one can model the visual-motor function analytically. The uncalibrated approach has received limited attention mainly because the stability analysis is not as straightforward as that of calibrated image-based architecture. In an uncalibrated system the visual-motor function is not known, but partial derivative information (Jacobian) can be learned by tracking visual measurements during motion. In this talk, we study the uncalibrated image-based visual servoing and present different Jacobian learning methods.
Mehran Shaghaghi: Quantum Mechanics Dilemmas
Speaker: Mehran Shaghaghi
Ph.D. Candidate
Department of Physics and Astronomy, University of British Columbia, Canada
Title: Quantum Mechanics Dilemmas
Organized by the Knowledge Diffusion Network
Time: Tuesday, December 11th , 2007.
Location: Department of Physics, Sharif University of Technology, Tehran
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This document provides an overview of coding theory and recent advances in low-density parity-check (LDPC) codes. It discusses Shannon's channel coding theorem and how modern error-correcting codes achieve rates close to channel capacity. LDPC codes are described as having sparse parity-check matrices and being decoded iteratively using message passing. The performance of LDPC codes can be analyzed using density evolution and threshold calculations. Linear programming decoding is introduced as an alternative decoding approach that has connections to message passing decoding.
Dr. Amir Nejat
This document summarizes research on developing an efficient higher-order accurate unstructured finite volume algorithm for inviscid compressible fluid flows. The algorithm uses an ILU preconditioned GMRES method to solve the Euler equations on unstructured meshes. Higher-order solutions of up to fourth-order accuracy were obtained. Results show the third-order solution was 1.3-1.5 times more expensive than second-order, while fourth-order was 3.5-5 times more expensive, demonstrating the efficiency of the higher-order approach. Test cases included supersonic and transonic flows, with results agreeing well with structured solvers.
Alborz
Knowledge Diffusion Network
Visiting Lecturer Program (114)
Speaker: Alborz Geramifard
Ph.D. Candidate
Department of Computing Science, Edmonton, University of Alberta, Canada
Title: Incremental Least- Squares Temporal Difference Learning
Time: Tuesday, Sep 11, 2007, 12:00-1:00 pm
Location: Department of Computer Engineering, Sharif University of Technology, Tehran
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- 2. Vision-Based Control A A A B B B current desired Left Image Right Image
- 3. Vision-Based Control Left Image Right Image B B B
- 8. Position-Based Desired pose Estimated pose
- 9. Position-Based Measurement noise State variable Process noise yaw pitch roll Measurement equation (projection) is nonlinear and must be linearized.
- 10. K x k-1,k-1 z k R k P k,k P k,k-1 C k Q k-1 x k,k x k,k-1 P k-1,k-1 Kalman Gain Measurement noise covariance A priori error cov. @ k-1 Process noise covariance Initial/previous state Linearization Measurement State update State prediction Error cov. prediction Error cov. update
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- 15. Image-Based Control Law Desired Image feature Extracted image feature
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- 40. Thank you!
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