2014
DOI: 10.1016/j.proeng.2014.12.091
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Visual Localization of Mobile Robot Using Artificial Markers

Abstract: The paper presents localization method for mobile robots with use of artificial markers deployed to an environment. A specialty of the markers is that the position and rotation of the camera relative to the marker can be determined from only one marker. Further in the paper, some experiments are described. The results prove that this system can be reliably employed in visual localization of mobile robots.

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Cited by 78 publications
(33 citation statements)
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“…to represent objects [18] [19], and 3D matching with data from stereo cameras [20] and structured light [21]. In recent years, the augmented reality (AR) markers are widely used to obtain pose information [22] [23], which possess the advantages of easier recognition and higher precision [24].…”
Section: Visual Recognition and Trackingmentioning
confidence: 99%
“…to represent objects [18] [19], and 3D matching with data from stereo cameras [20] and structured light [21]. In recent years, the augmented reality (AR) markers are widely used to obtain pose information [22] [23], which possess the advantages of easier recognition and higher precision [24].…”
Section: Visual Recognition and Trackingmentioning
confidence: 99%
“…Unlike the visual localization done using a single marker reported in [29], we have used ArUco markers map (AMM) for two purposes: one is for the identification of the kinematic parameters of each leg. The other is for the trajectory tracking of the robot.…”
Section: Setupmentioning
confidence: 99%
“…In this work, we have proposed the use of the monocular camera with the AruCo markers to demonstrate it for the identification of Tarantula. Unlike the visual localization which is done using a single marker reported in [29], we have used ArUco markers map (AMM) that resulted in the improved measurement accuracy. The measurement performance of this approach is compared using the standard industrial robot KUKA KR6 R900 robot (KUKA, Augsburg, Germany) [30].…”
Section: Introductionmentioning
confidence: 99%
“…Fiducial tags, or fiducial markers, are used in computer vision (CV) applications for robot localization [1,2], mapping and localization of large environments [3][4][5], or for pose estimation in medical endoscopy [6]. Markers are also used for metric purposes, e.g., for calibration [7] and monitoring changes in distances and orientations in historic structures [8].…”
Section: Introductionmentioning
confidence: 99%