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Vision Calibration and Processing on a Humanoid Soccer Robot

Piyush Khandelwal, Matthew Hausknecht, Juhyun Lee, Aibo Tian, and Peter Stone. Vision Calibration and Processing on a Humanoid Soccer Robot. In The Fifth Workshop on Humanoid Soccer Robots at Humanoids 2010, December 2010.

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Abstract

In RoboCup, the problem of quickly and accurately processing visual data continues to pose a significant challenge. The Aldebaran Nao, currently used by the Standard Platform League, has two cameras for visual input, of which only one has been typically used. The integration of both cameras presents a new opportunity but also a challenge. While it is possible to obtain better information using both cameras, more cameras require more work to calibrate. We propose a novel camera calibration algorithm which automatically tunes a camera such that its color perceptions match those of another camera. Additionally, recent vision challenges introduced in RoboCup have necessitated the use of higher resolution images. We build on existing work in color based segmentation and present novel extensions to facilitate the move to higher resolution images, including memory optimizations, fast line and curve detection, and differentiation via robot pose based transformations. All work presented in this paper was successfully used by the UT Austin Villa Robot Soccer team, which secured 3rd place overall and 2nd place in the technical challenges at RoboCup 2010.

BibTeX

@InProceedings{HUMANOIDS10-khandelwal,
	author = "Piyush Khandelwal and Matthew Hausknecht and Juhyun Lee and Aibo Tian and Peter Stone",
   title = "Vision Calibration and Processing on a Humanoid Soccer Robot",
	booktitle = "The Fifth Workshop on Humanoid Soccer Robots at Humanoids 2010",
   location = "Nashville, TN",
	month = "December",
	year = "2010",
	abstract = {
		In RoboCup, the problem of quickly and accurately processing visual data continues to pose a significant
		challenge. The Aldebaran Nao, currently used by the Standard
		Platform League, has two cameras for visual input, of which
		only one has been typically used. The integration of both
		cameras presents a new opportunity but also a challenge.
		While it is possible to obtain better information using both
		cameras, more cameras require more work to calibrate. We
		propose a novel camera calibration algorithm which automatically tunes a camera such that its color perceptions match
		those of another camera. Additionally, recent vision challenges
		introduced in RoboCup have necessitated the use of higher
		resolution images. We build on existing work in color based
		segmentation and present novel extensions to facilitate the move
		to higher resolution images, including memory optimizations,
		fast line and curve detection, and differentiation via robot pose
		based transformations. All work presented in this paper was
		successfully used by the UT Austin Villa Robot Soccer team,
		which secured 3rd place overall and 2nd place in the technical
		challenges at RoboCup 2010.
	},
}

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