scholarly journals 2A1-N-095 Visualizing Sensor History for a Mobile Robot by Image Based Rendering(Robot Vision 1,Mega-Integration in Robotics and Mechatronics to Assist Our Daily Lives)

2005 ◽  
Vol 2005 (0) ◽  
pp. 153
Author(s):  
KUNIAKI OTSUKA ◽  
KANJI TANAKA ◽  
NOBUHIRO OKADA ◽  
EIJI KONDO
Keyword(s):  
Mobile Robot ◽  
Robot Vision ◽  
Daily Lives ◽  
Image Based Rendering

Research on SLAM Algorithm of Mobile Robot Vision Based on Deep Learning

2021 ◽  
Author(s):  
Haili Song ◽  
Bin Ren ◽  
Zengxu Zhao ◽  
Jianyuan Cui
Keyword(s):  
Deep Learning ◽  
Mobile Robot ◽  
Robot Vision ◽  
Mobile Robot Vision ◽  
Slam Algorithm

scholarly journals Experiments on mobile robot stereo vision system calibration under hardware imperfection

2018 ◽  
Vol 161 ◽  
pp. 03020 ◽  
Author(s):  
Ramil Safin ◽  
Roman Lavrenov ◽  
Subir Kumar Saha ◽  
Evgeni Magid
Keyword(s):  
Mobile Robot ◽  
Stereo Vision ◽  
Experimental Approach ◽  
Vision System ◽  
Robot Vision ◽  
System Calibration ◽  
Stereo Vision System ◽  
Calibration Methods ◽  
Vertical Level ◽  
Grid Based

Calibration is essential for any robot vision system for achieving high accuracy in deriving objects metric information. One of typical requirements for a stereo vison system in order to obtain better calibration results is to guarantee that both cameras keep the same vertical level. However, cameras may be displaced due to severe conditions of a robot operating or some other circumstances. This paper presents our experimental approach to the problem of a mobile robot stereo vision system calibration under a hardware imperfection. In our experiments, we used crawler-type mobile robot «Servosila Engineer». Stereo system cameras of the robot were displaced relative to each other, causing loss of surrounding environment information. We implemented and verified checkerboard and circle grid based calibration methods. The two methods comparison demonstrated that a circle grid based calibration should be preferred over a classical checkerboard calibration approach.

Mobile robot vision tracking system using Unscented Kalman Filter

2011 ◽  
Author(s):  
Muhammad Muneeb Shaikh ◽  
Wook Bahn ◽  
Changhun Lee ◽  
Tae-il Kim ◽  
Tae-jae Lee ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Mobile Robot ◽  
Unscented Kalman Filter ◽  
Tracking System ◽  
Robot Vision ◽  
Mobile Robot Vision

Improved Hough Transform Applying in Mobile Robot Vision Navigation

2012 ◽  
Vol 232 ◽  
pp. 408-413
Author(s):  
Yin Ping Jiang ◽  
Xian Xian Zhang ◽  
Xiao Peng Fu
Keyword(s):  
Mobile Robot ◽  
Hough Transform ◽  
Robot Vision ◽  
Geometric Figure ◽  
Vision Navigation ◽  
Line Extraction ◽  
Local Threshold ◽  
Global Threshold ◽  
Image Quality Reduction ◽  
Mobile Robot Vision

This paper mainly discusses that in mobile robot vision navigation system, by using the improved Hough transform, we can improve the accuracy of line extraction and therefore avoid the image quality reduction caused by noise points. Considering the limitations of the standard Hough transform, we come up with a method with which we will accumulates the H (ρ, θ) through distributing the increment value, set a global threshold to shun the pointless measurements, eliminate the false lines by comparing θ difference between tow arbitrary lines, find the peaks by using rectangle window, and set a local threshold to eliminate false peaks. In this way, we can gain a method superior to the standard Hough transform which works better in extracting lines in application. The experiments show that this method can not only extract line features of geometric figure effectively in brief background, but also eliminate the iterative lines efficiently.

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