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Wednesday, September 24, 2014. Robust Chessboard Recognition Part 4: A Solution. In the Part 1. Of this series, I showed how to turn chessboard recognition into an optimization problem. In Part 2. I discussed different ways of solving this optimization problem, deciding on a custom evolutionary algorithm with tailored mutation operators described in Part 3. In this post, I discuss my solution. A video of the final solution is shown to the right. Each quadrilateral in the population is scored. After one h...

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icubchess | icubchess.blogspot.com Reviews
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Wednesday, September 24, 2014. Robust Chessboard Recognition Part 4: A Solution. In the Part 1. Of this series, I showed how to turn chessboard recognition into an optimization problem. In Part 2. I discussed different ways of solving this optimization problem, deciding on a custom evolutionary algorithm with tailored mutation operators described in Part 3. In this post, I discuss my solution. A video of the final solution is shown to the right. Each quadrilateral in the population is scored. After one h...
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icubchess | icubchess.blogspot.com Reviews

https://icubchess.blogspot.com

Wednesday, September 24, 2014. Robust Chessboard Recognition Part 4: A Solution. In the Part 1. Of this series, I showed how to turn chessboard recognition into an optimization problem. In Part 2. I discussed different ways of solving this optimization problem, deciding on a custom evolutionary algorithm with tailored mutation operators described in Part 3. In this post, I discuss my solution. A video of the final solution is shown to the right. Each quadrilateral in the population is scored. After one h...

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icubchess.blogspot.com icubchess.blogspot.com
1

icubchess: Robust Chessboard Recognition, Part 1: Some Tools

http://icubchess.blogspot.com/2014/08/robust-chessboard-recognition-part-1.html

Tuesday, August 12, 2014. Robust Chessboard Recognition, Part 1: Some Tools. Raw image of chessboard from iCub's left eye. In order for the iCub to play chess, it first needs to see the board. For eyes, the iCub has two Dragonfly cameras. To find the chessboard, we will use computer vision techniques to extract information about the image. We could use more advanced techniques, such as neural nets. Image of chessboard after removing lens distortion. On our raw image and be done with the chessboard recogn...

2

icubchess: Robust Chessboard Recognition, Part 2: Evolutionary Algorithms

http://icubchess.blogspot.com/2014/09/robust-chessboard-recognition-part-2.html

Monday, September 1, 2014. Robust Chessboard Recognition, Part 2: Evolutionary Algorithms. Lines and intersections extracted from the iCub's eyes. What percentage of the expected horizontal and vertical grid lines are matched? What percentage of the grid intersection points are matched? How uniform is the color is the fringe just outside of the warped image? Now we have a fitness function. Also known as an objective function. Black-box optimization was originally named to contrast with the gradient-based.

3

icubchess: September 2014

http://icubchess.blogspot.com/2014_09_01_archive.html

Wednesday, September 24, 2014. Robust Chessboard Recognition Part 4: A Solution. In the Part 1. Of this series, I showed how to turn chessboard recognition into an optimization problem. In Part 2. I discussed different ways of solving this optimization problem, deciding on a custom evolutionary algorithm with tailored mutation operators described in Part 3. In this post, I discuss my solution. A video of the final solution is shown to the right. Each quadrilateral in the population is scored. After one h...

4

icubchess: Robust Chessboard Recognition, Part 3: Tailored Mutation Operators

http://icubchess.blogspot.com/2014/09/robust-chessboard-recognition-part-3.html

Wednesday, September 3, 2014. Robust Chessboard Recognition, Part 3: Tailored Mutation Operators. A correctly detected chessboard. In the last two posts, I discussed the chessboard recognition problem. And the types of algorithms. A randomly generated quadrilateral. Snapping Corners to Points. Leftmost corner snapped to point. Top right snapped to point. After six shortening steps. After three shortening steps. After six more snaps. The images to the right show the progress after three and six steps....

5

icubchess: Robust Chessboard Recognition Part 4: A Solution

http://icubchess.blogspot.com/2014/09/robust-chessboard-recognition-part-4.html

Wednesday, September 24, 2014. Robust Chessboard Recognition Part 4: A Solution. In the Part 1. Of this series, I showed how to turn chessboard recognition into an optimization problem. In Part 2. I discussed different ways of solving this optimization problem, deciding on a custom evolutionary algorithm with tailored mutation operators described in Part 3. In this post, I discuss my solution. A video of the final solution is shown to the right. Each quadrilateral in the population is scored. After one h...

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alockett.com alockett.com

Alan J Lockett's Optimization Research

http://www.alockett.com/en/software/pyec

Alan J. Lockett's Research Pages. PyEC v0.3.0. PyEC is an open-source Python package that implements several popular evolutionary algorithms in the terms of the formal theory described in the Research. Section. PyEC is listed in the Python Package Index (PyPi - go to http:/ pypi.python.org/pypi/PyEC. Documentation for PyEC is provided on this site at http:/ www.alockett.com/pyec/docs/0.3/index.html. The current version of PyEC provides:. Correlated Matrix Adaptation Evolution Strategies (CMA-ES). Easy co...

alockett.com alockett.com

Alan J Lockett's Optimization Research

http://www.alockett.com/en/resume

Alan J. Lockett's Research Pages. PyEC v0.3.0. Postdoctoral Researcher, Optimization and Control for Autonomous Systems. Seeking to start a research lab as a tenure-track assistant professor. Email: alan.lockett@gmail.com. Phone: 41 77 419 1761. Optimization and Control in Autonomous Systems. Probability Theory, Statistical Models. Deep Neural Networks for Perception and Control. Postdoctoral Fellow with a US NSF grant to use deep neural networks for control of a humanoid robot. MA in Middle Eastern Stud...

alockett.com alockett.com

Alan J Lockett's Optimization Research

http://www.alockett.com/en/software

Alan J. Lockett's Research Pages. PyEC v0.3.0. At present, I only have one software package, but I expect others to follow, and in the future this page may also provide links to other researchers' software as well. I have lots of plans for improvement, but very little free time to spend on them, so feel free to donate via the link on the left! PyEC is an open-source Python package that implements several popular evolutionary algorithms in the terms of the formal theory described in the Research. In Lugan...

alockett.com alockett.com

Alan J Lockett's Optimization Research

http://www.alockett.com/en/publications

Alan J. Lockett's Research Pages. PyEC v0.3.0. Here are my current publications listed by year, with links to each where the paper is publicly available. Lockett, Alan. Beyond Newton's Method: Functional Analysis of Optimization. To Appear, 2015. Springer-Verlag. Stollenga, Marijn, Lockett, Alan, and Schmidhuber, Juergen. The Natural Gradient as a Control Signal for a Humanoid Robot. Submitted October 2014. Draft. Submitted October 2014. Draft. Aberystwyth, Wales. ACM Press. Adelaide, Australia. ACM ...

alockett.com alockett.com

Alan J Lockett's Optimization Research

http://www.alockett.com/en/about

Alan J. Lockett's Research Pages. PyEC v0.3.0. This is the personal research site of Alan J. Lockett. My main research interest is to develop feedback controllers for complex autonomous systems. I'm a postdoctoral fellow at the Dalle Molle Institute for Artificial Intelligence Studies. I received a Ph.D in Artificial Intelligence from the University of Texas at Austin. In May 2012. For my thesis, I did a mathematical analysis. You can find my resume here. And a CV here. You can contact me directly at:.

alockett.com alockett.com

Alan J Lockett's Optimization Research

http://www.alockett.com/en

Alan J. Lockett's Research Pages. PyEC v0.3.0. For generic research and teaching statements, see the links to the left. Please contact me about potential research positions at alan.lockett@gmail.com. October 21, 2014. My paper Insights from Adversarial Fitness Functions. Has been accepted for publication in FOGA 2015. A draft is available on my publications page, but still needs some corrections and a bit of reorganization. October 1, 2014. July 12-16, 2014. In the theory track. March 12, 2014. My paper ...

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Wednesday, September 24, 2014. Robust Chessboard Recognition Part 4: A Solution. In the Part 1. Of this series, I showed how to turn chessboard recognition into an optimization problem. In Part 2. I discussed different ways of solving this optimization problem, deciding on a custom evolutionary algorithm with tailored mutation operators described in Part 3. In this post, I discuss my solution. A video of the final solution is shown to the right. Each quadrilateral in the population is scored. After one h...

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