Visual simultaneous localisation and map-building supported by structured landmarks

Bączyk, Robert; Kasiński, Andrzej

doi:10.2478/v10006-010-0021-7

Cited by 11 publications

(4 citation statements)

References 18 publications

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“…The cyber layer makes the calculations according to the customer order and the sensor data to produce appropriate commands for machines in physical layer. After the production of product, it is shipped by autonomous vehicles, which is a study field of smart city [10,11]. Hereby, the production process from ordering to shipping can be done without any human interaction.…”

Section: Methodsmentioning

confidence: 99%

A Cyberphysical System Based Mass-Customization Approach with Integration of Industry 4.0 and Smart City

Karaköse

Yetiş

2017

Wireless Communications and Mobile Computing

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Smart city is a city which is designed to meet the people's demands. In addition to use of sources efficiently, trends of people are also a need that smart city should meet. Buying personalized products in a cheap and fast way is a demand of people of today. Mass customization, which is defined as the personalization of products, achieves making the tailor-made products cheaper. In this study, we propose a new approach for mass customization with the integration of smart retail and smart production. With removing the operators and actualizing the progress autonomously, it is aimed to reduce the waiting time of customers. Because less waiting time means that there are more mass-customization customers, and this is expected to increase the popularity of mass customization. Thus, reducing wastes and increasing productivity are aimed. This study also constitutes the infrastructure that enables a production system to autonomously perform all stages from order to delivery. With the given scenarios, challenges and advantages of desired approach are discussed.

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Section: Methodsmentioning

confidence: 99%

A Cyberphysical System Based Mass-Customization Approach with Integration of Industry 4.0 and Smart City

Karaköse

Yetiş

2017

Wireless Communications and Mobile Computing

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“…Although this assumption was also removed in some earlier 2-D self-localization solutions (Skrzypczyński, 2009), in walking and humanoid robots or micro aerial vehicles (Engel et al, 2012) reliable odometry from proprioceptive sensing is not available at all or is extremely poor, making these robots dependent on self-localization with exteroceptive sensors. Passive vision has many practical limitations (Davison et al, 2007;Bączyk and Kasiński, 2010), whereas 3-D laser range finders with mechanical scanning are bulky, heavy, and often slow. Thus, compact, fast-frame-rate RGB-D cameras are the sensors of choice…”

Section: Introductionmentioning

confidence: 99%

Efficient RGB–D data processing for feature–based self–localization of mobile robots

Kraft

Nowicki

Penne³

et al. 2016

International Journal of Applied Mathematics and Computer Science

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The problem of position and orientation estimation for an active vision sensor that moves with respect to the full six degrees of freedom is considered. The proposed approach is based on point features extracted from RGB-D data. This work focuses on efficient point feature extraction algorithms and on methods for the management of a set of features in a single RGB-D data frame. While the fast, RGB-D-based visual odometry system described in this paper builds upon our previous results as to the general architecture, the important novel elements introduced here are aimed at improving the precision and robustness of the motion estimate computed from the matching point features of two RGB-D frames. Moreover, we demonstrate that the visual odometry system can serve as the front-end for a pose-based simultaneous localization and mapping solution. The proposed solutions are tested on publicly available data sets to ensure that the results are scientifically verifiable. The experimental results demonstrate gains due to the improved feature extraction and management mechanisms, whereas the performance of the whole navigation system compares favorably to results known from the literature.

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“…The acquired data allows reliable benchmarking of the algorithms performing the task of simultaneous localization and mapping (SLAM) [21] [22] or visual odometry [23] [24]. As shown in [25], the presence of additional structured markers placed throughout the environment improves the accuracy of navigation in single robot scenarios. We believe that the introduction of additional unique artificial markers associated with individual robots, as presented in this article, will allow us to improve the accuracy in scenarios in which external cameras are used or in the case of collaborative SLAM.…”

Section: Introductionmentioning

confidence: 99%

Calibration of the Multi-camera Registration System for Visual Navigation Benchmarking

Schmidt

Kasiński

Kraft

et al. 2014

International Journal of Advanced Robotic Systems

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This paper presents the complete calibration procedure of a multi-camera system for mobile robot motion registration. Optimization-based, purely visual methods for the estimation of the relative poses of the motion registration system cameras, as well as the relative poses of the cameras and markers placed on the mobile robot were proposed. The introduced methods were applied to the calibration of the system and the quality of the obtained results was evaluated. The obtained results compare favourably with the state of the art solutions, allowing the use of the considered motion registration system for the accurate reconstruction of the mobile robot trajectory and to register new datasets suitable for the benchmarking of indoor, visual-based navigation algorithms.

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Visual simultaneous localisation and map-building supported by structured landmarks

Cited by 11 publications

References 18 publications

A Cyberphysical System Based Mass-Customization Approach with Integration of Industry 4.0 and Smart City

A Cyberphysical System Based Mass-Customization Approach with Integration of Industry 4.0 and Smart City

Efficient RGB–D data processing for feature–based self–localization of mobile robots

Calibration of the Multi-camera Registration System for Visual Navigation Benchmarking

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