On the Application of QR Codes for Robust Self-localization of Mobile Robots in Various Application Scenarios

Rostkowska, Marta; Topolski, Michał

doi:10.1007/978-3-319-15847-1_24

Cited by 14 publications

(8 citation statements)

References 9 publications

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“…Thus, the viewing angle of the landmark never exceeds 15ᵒ. Results of our earlier experiments [21] provide evidence that for such small viewing angles the correction of perspective brings no improvement in the landmark localization, while this procedure is computation intensive.…”

Section: Fig 7 Spatial Distribution Of Errors In Qr Code-based Landmentioning

confidence: 78%

“…the optical axis) and the center of the landmark. The distance at which the landmark can be detected and recognized depends on the camera resolution and the physical size of the landmark [21]. The information about the actual landmark size, as well as the position and orientation in the global reference frame x L = [x L y L θ L ] T is encoded in the QR code of the landmark itself, so the robot doesn't need to keep a map of known landmarks in the memory.…”

Section: Concept and Componentsmentioning

confidence: 99%

“…In such a case the relation between locations of the characteristic points (corners) in 3D and the image plane has to be found in order to properly calculate the landmark's position and rotation. Computations of this relation are described in more details in [21]. We omit these calculations here, because such situations should not occur when self-localization takes place by using both the perspective and omnidirectional cameras, as the perspective camera is set to a proper angular position before taking an image of the landmark.…”

Section: Fig 7 Spatial Distribution Of Errors In Qr Code-based Landmentioning

confidence: 99%

“…In our recent work [21] we evaluated the QR code landmarks as self-localization aids in two very different configurations of the camera-based perception system: an overhead camera that observed a landmark attached on top of a mobile robot, and a frontview camera attached to a robot, which observed landmarks freely placed in the environment. Both solutions enable to localize the robot in real-time with a sufficient accuracy, but both have important practical drawbacks.…”

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confidence: 99%

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Improving Self-Localization Efficiency in a Small Mobile Robot by Using a Hybrid Field of View Vision System

Rostkowska

Skrzypczyński

2015

JAMRIS

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In this article a self-localization system for small mobile robots based on inexpensive cameras and unobtrusive, passive landmarks is presented and evaluated. The main contribution is the experimental evaluation of the hybrid field of view vision system for self-localization with artificial landmarks. The hybrid vision system consists of an omnidirectional, upward-looking camera with a mirror, and a typical, front-view camera. This configuration is inspired by the peripheral and foveal vision co-operation in animals. We demonstrate that the omnidirectional camera enables the robot to detect quickly landmark candidates and to track the already known landmarks in the environment. The front-view camera guided by the omnidirectional information enables precise measurements of the landmark position over extended distances. The passive landmarks are based on QR codes, which makes possible to easily include in the landmark pattern additional information relevant for navigation. We present evaluation of the positioning accuracy of the system mounted on a SanBot Mk II mobile robot. The experimental results demonstrate that the hybrid field of view vision system and the QR code landmarks enable the small mobile robot to navigate safely along extended paths in a typical home environment.

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Section: Fig 7 Spatial Distribution Of Errors In Qr Code-based Landmentioning

confidence: 78%

Section: Concept and Componentsmentioning

confidence: 99%

Section: Fig 7 Spatial Distribution Of Errors In Qr Code-based Landmentioning

confidence: 99%

mentioning

confidence: 99%

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Improving Self-Localization Efficiency in a Small Mobile Robot by Using a Hybrid Field of View Vision System

Rostkowska

Skrzypczyński

2015

JAMRIS

Self Cite

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show abstract

“…Rostkowska et al [20] addressed the application of QR codes as landmarks for mobile robot navigation, but this method of displaying big QR codes on every box is not widely used. Luca et al [21] used QR codes mounted on a ceiling for smart wheelchair navigation.…”

Section: Introductionmentioning

confidence: 99%

A Computer Vision-Based Navigation and Localization Method for Station-Moving Aircraft Transport Platform with Dual Cameras

Tang

Zhu

2020

Sensors

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In order to develop equipment adapted to the aircraft pulse final assembly line, a vision-based aircraft transport platform system is developed. This article explores a guiding method between assembly stations which is low-cost and easy to change routes by using two-dimensional code and two complementary metal oxide semiconductor (CMOS) cameras. The two cameras installed on the front and back of the platform read the two-dimensional code containing station information to guide the platform. In the process of guiding, the theoretical position and posture of the platform at each assembly station are known, but there is a difference between the actual and theoretical values due to motion errors. To reduce the influence of the deviation on the navigation route, a localization method is proposed based on the two-dimensional images captured by the cameras. Canny edge detection is applied to the processed image to obtain the position of the two-dimensional code in the image, which can measure the angle/distance deviation of the platform. Then, the computer can locate the platform precisely by the information in the two-dimensional code and the deviation measured by the image. To verify the feasibility of the proposed method, experiments have been performed on the developed platform system. The results show that the distance and angle errors of the platform are within ±10 mm and ±0.15 • respectively.

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Mobile Robot Applied to QR Landmark Localization Based on the Keystone Effect

Dutta

2016

Mechatronics and Robotics Engineering for Advanced and Intelligent Manufacturing

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On the Application of QR Codes for Robust Self-localization of Mobile Robots in Various Application Scenarios

Cited by 14 publications

References 9 publications

Improving Self-Localization Efficiency in a Small Mobile Robot by Using a Hybrid Field of View Vision System

Improving Self-Localization Efficiency in a Small Mobile Robot by Using a Hybrid Field of View Vision System

A Computer Vision-Based Navigation and Localization Method for Station-Moving Aircraft Transport Platform with Dual Cameras

Mobile Robot Applied to QR Landmark Localization Based on the Keystone Effect

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