A Robot Environment Identification Method: Image Processing Application in Duct Cleaning Robot

2010 ◽  
Author(s):  
Bu-Min Meng ◽  
Wei Sun
Keyword(s):  
Image Processing ◽  
Processing Application ◽  
Identification Method ◽  
Cleaning Robot ◽  
Image Processing Application ◽  
Environment Identification ◽  
Duct Cleaning Robot ◽  
Duct Cleaning

DFOG-Image Processing Application for Real-Time Defogging

2020 ◽  
Author(s):  
Indiketiya I.H.O.H ◽  
Kulasekara K.M.R.A ◽  
J.M. Thomas ◽  
Ishara Gamage ◽  
Thusithanjana Thilakarathna
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Processing Application ◽  
Image Processing Application

scholarly journals Control system design of duct cleaning robot capable of overcoming L and T-shaped ducts

2020 ◽  
Vol 9 (2) ◽  
pp. 123
Author(s):  
Myeong In Seo ◽  
Woo Jin Jang ◽  
Junhwan Ha ◽  
Kyongtae Park ◽  
Dong Hwan Kim
Keyword(s):  
Control Method ◽  
Estimation Algorithm ◽  
Location Estimation ◽  
Positional Error ◽  
Cleaning Robot ◽  
Communication Module ◽  
Duct Cleaning Robot ◽  
Robot Position ◽  
Uwb Communication ◽  
Duct Cleaning

This study introduces the control method of duct cleaning robot that enables real-time position tracking and self-driving over L-shaped and T-shaped duct sections. The developed robot has three legs and is designed to flexibly respond to duct sizes. The position of the robot inside the duct is identified using the UWB communication module and the location estimation algorithm. Although UWB communication has relatively large distance error within the metal, the positional error was reduced by introducing appropriate filters to estimate the robot position accurately. TCP/IP communication allows commands to be sent between the PC and the robot and to receive live images of the camera attached to the robot. Using Haar-like and classifiers, the robot can recognize the type of duct that is difficult to overcome, such as L-shaped and T-shaped duct, and it moves successfully inside the duct according to the corresponding moving algorithms.

Formulation of Fractional Derivative-Based De-Hazing Algorithm and Implementation on Mobile-Embedded Devices

2019 ◽  
Vol 19 (01) ◽  
pp. 1950003
Author(s):  
Uche A. Nnolim
Keyword(s):  
Image Processing ◽  
Fractional Derivative ◽  
Mobile Devices ◽  
Fractional Order ◽  
Spatial Filter ◽  
Embedded Devices ◽  
Processing Application ◽  
Fractional Order Calculus ◽  
Image Processing Application ◽  
Logarithmic Image Processing

This paper presents the modification of a previously developed algorithm using fractional order calculus and its implementation on mobile-embedded devices such as smartphones. The system performs enhancement on three categories of images such as those exhibiting uneven illumination, faded features/colors and hazy appearance. The key contributions include the simplified scheme for illumination correction, contrast enhancement and de-hazing using fractional derivative-based spatial filter kernels. These are achieved without resorting to logarithmic image processing, histogram-based statistics and complex de-hazing techniques employed by conventional algorithms. The simplified structure enables ease of implementation of the algorithm on mobile devices as an image processing application. Results indicate that the fractional order version of the algorithm yields good results relative to the integer order version and other algorithms from the literature.

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