&lt;title&gt;Mobile robot localization with multiple stationary cameras&lt;/title&gt;

Yoo, Jae Hung; Sethi, Ishwar K.

doi:10.1117/12.135175

Cited by 2 publications

(1 citation statement)

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“…The robot is tracked by the camera by means of a number of LEDs installed on the robot. In [8], the robot is tracked by a network of cameras, which use the information from a circular shape that has been installed on the robot. Fisheye cameras have been used onboard the robots for visual navigation [9].…”

Section: Introductionmentioning

confidence: 99%

Real Time Indoor Robot Localization Using a Stationary Fisheye Camera

Delibasis¹,

Plagianakos²

2013

IFIP Advances in Information and Communication Technology

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A core problem in robotics is the localization of a mobile robot (determination of the location or pose) in its environment, since the robot's behavior depends on its position. In this work, we propose the use of a stationary fisheye camera for real time robot localization in indoor environments. We employ an image formation model for the fisheye camera, which is used for accelerating the segmentation of the robot's top surface, as well as for calculating the robot's true position in the real world frame of reference. The proposed robot localization algorithm does not depend on any information from the robot's sensors and does not require visual landmarks in the indoor environment. Initial results are presented from video sequences and are compared to the ground truth position, obtained by the robot's sensors. The dependence of the average positional error with the distance from the camera is also measured.

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Section: Introductionmentioning

confidence: 99%

Real Time Indoor Robot Localization Using a Stationary Fisheye Camera

Delibasis¹,

Plagianakos²

2013

IFIP Advances in Information and Communication Technology

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Estimation of Robot Position and Orientation Using a Stationary Fisheye Camera

Delibasis

Plagianakos

2015

Int. J. Artif. Intell. Tools

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A core problem in robotics is the determination of the location and pose of a mobile robot in its environment. The localization is a basic operation, which must be successfully carried out in complex environments using imprecise and/or contaminated data and is essential for a broad range of mobile robot tasks, since the robot behavior depends on its position. In this work, we propose the use of a stationary fisheye camera for real time robot localization in indoor environments. We employ a model for the formation of the image by the fisheye camera, which can be used for accelerating the segmentation of the robot's top surface, as well as for calculating the robot's true position in the real world frame of reference. The proposed algorithm for robot localization exploits the calibrated fisheye camera model and the known dimensions of the robot, whereas it does not depend on any information from the robot's sensors and does not require visual landmarks in the indoor environment. Furthermore, the pose (orientation) of the robot is determined using a triangular shape placed on top of the robot's flat top surface, using Hu's moment invariants, appropriately modified using the calibrated fisheye camera model. Initial results are presented from video sequences and are compared to the ground truth position, obtained by the robot's sensors. The dependence of the average positional error with the distance from the camera is also measured.

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<title>Mobile robot localization with multiple stationary cameras</title>

Cited by 2 publications

References 1 publication

Real Time Indoor Robot Localization Using a Stationary Fisheye Camera

Real Time Indoor Robot Localization Using a Stationary Fisheye Camera

Estimation of Robot Position and Orientation Using a Stationary Fisheye Camera

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