1P1-L16 Exhibits Identification using Marker Recognition and Decision Making for Tour Guide Robot(Vision System for Mobile Robot)

2011 ◽  
Vol 2011 (0) ◽  
pp. _1P1-L16_1-_1P1-L16_4
Author(s):  
Yuki KATOH ◽  
Masayuki OKUGAWA
2018 ◽  
Vol 161 ◽  
pp. 03020 ◽  
Author(s):  
Ramil Safin ◽  
Roman Lavrenov ◽  
Subir Kumar Saha ◽  
Evgeni Magid

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.


2010 ◽  
Vol 455 ◽  
pp. 42-46 ◽  
Author(s):  
C.Z. Wang ◽  
Xiao Dong Zhang ◽  
Xue Zhi Wu

The robot vision technology designed to help the elderly and the disabled people are studied on a mobile robot in the thesis, and its robot vision system based on ARM and DSP is mainly designed, respectively. After hardware construction and software design, the experiments are taken to verify the feasibility of the application of the robot vision technology on the age and disabled helping robot.


Author(s):  
Yun Ji ◽  
Rajeev Kumar ◽  
Daljeet Singh ◽  
Maninder Singh

In this paper, an agricultural robot vision system is proposed for two typical environments—farmland and orchard—combined with weeding between crops. The system includes orchard production monitoring and prediction tasks, the target information recognition approach, and visual servo decision making. The results obtained from the proposed system show that using the region combination features of image 2D histogram as the decision-making basis, the accurate and rapid indirect identification and positioning of crop seedlings can be accomplished while skipping the complex process of accurately identifying crops and weeds. The algorithm performs reasonably good as the time of target recognition in the prototype system is found to be less than 16 ms, and the average accurate recognition rate of 97.43% is achieved. The benefits of the proposed system are the continuous improvement of the quality of agricultural products, the rise of production efficiency, and the increase of economic benefits.


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