Design and Implementation of a Miniature Intelligent Vehicle Test Platform

Li, Ning; Xiong, Guangming; Song, Wei; Gong, Jianwei; Chen, Huiyan

doi:10.14257/ijsh.2013.7.5.35

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2016

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(2 citation statements)

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“…The segmentation threshold between background and object is t, background 0 C is pixels which gray level [1,t] and object 1 C is pixels which gray level [t+1,L]. The probability of 0 C and 1 C :…”

Section: Background Extractionmentioning

confidence: 99%

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Obstacle Avoidance for AGV with Kinect Sensor

Han

Wang²

2016

IJSH

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This paper aims the development of autonomous obstacle avoidance algorithm for automated guided vehicle with a Kinect sensor. To do this task, the followings are executed. Firstly, depth data is obtained from the Kinect sensor, and the mean filter approach is developed to filter out noises. Secondly, Otsu and U-V parallax based method is designed to identify background and obstacles. Finally, According to barrier information, corresponding fuzzy control rules is generated for the path planning. Our experiments show that the proposed method is fast, and gives promising results.

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Section: Background Extractionmentioning

confidence: 99%

“…Then along came electromagnetism which is used to realize the automatic guidance of AGV through laying underground cable onto the course. According to source [1], the car can travel freely and position accurately with laser guidance. Article [2] uses inertial navigation to design control system implementing path identification.…”

Section: Introductionmentioning

confidence: 99%