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Wyszukujesz frazę "Lee, M." wg kryterium: Autor


Wyświetlanie 1-2 z 2
Tytuł:
A New 3D Sensor System by Using Virtual Camera Model and Stereo Vision for Mobile Robots
Autorzy:
Lee, H.
Kim, M. N.
Cho, H.
Powiązania:
https://bibliotekanauki.pl/articles/384962.pdf
Data publikacji:
2008
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
virtual camera model
stereo vision
Opis:
So many researches have been conducted to develop 3D sensing method for mobile robots. Among them, the optical triangulation, a well-known method for 3D shape measurement, is also based on active vision sensing principle for mobile robot sensor system, so that the measurement result is robust to illumination noises from environments. Due to this advantage it has been popularly used. However, to obtain the 3D information of environment needs a special scanning process and scanning actuators need. To omit this scanning process multi-line projection methods have been widely researched. However, they suffer from an inherent limitation: The results of multi-line projection method commonly have measurement errors because of 2 -ambiguity caused by regularly repeated multiline laser pattern. In this paper, to overcome 2 -ambiguity effectively, we introduce a novel sensing method for a 3D sensing system using multi-line projection and stereo cameras, based on the virtual camera model and stereovision algorithm. To verify the efficiency and accuracy of the proposed method, a series of experimental tests is performed.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2008, 2, 4; 38-44
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Bayesian model for multimodal sensory information fusion in humanoid
Autorzy:
Wong, W. K.
Loo, L. C.
Neoh, T. M.
Liew, Y. W.
Lee, E. K.
Powiązania:
https://bibliotekanauki.pl/articles/384986.pdf
Data publikacji:
2011
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
multimodal
Bayesian fusion
fixation
saccade
humanoid robot
Opis:
In this paper, the Bayesian model for bimodal sensory information fusion is presented. It is a simple and biological plausible model used to model the sensory fusion in human’s brain. It is adopted into humanoid robot to fuse the spatial information gained from analyzing auditory and visual input, aiming to increase the accuracy of object localization. Bayesian fusion model requires prior knowledge on weights for sensory systems. These weights can be determined based on standard deviation (SD) of unimodal localization error obtained in experiments. The performance of auditory and visual localization was tested under two conditions: fixation and saccade. The experiment result shows that Bayesian model did improve the accuracy of object localization. However, the fused position of the object is not accurate when both of the sensory systems were bias towards the same direction.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2011, 5, 1; 16-22
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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