The Analysis of the Effect of the Parameters on Indirect Distance Measurement using a Digital Camera

Bui, Minh Tuan; Doskocil, Radek; Křivánek, Václav

doi:10.1109/miltechs.2019.8870101

Cited by 6 publications

(2 citation statements)

References 12 publications

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“…The recognition accuracy rate was above 85% and could adapt to 30~70% of the lighting brightness changes, significantly improving the drilling and riveting efficiency. Bui et al [ 18 , 19 ] used the parallax method to calculate two images at two different optical axis positions. They measured any object using the parallax generated between the images.…”

Section: Positioning Equipment and Algorithmsmentioning

confidence: 99%

A Review of Intelligent Assembly Technology of Small Electronic Equipment

Tian

Ding

Du³

et al. 2023

Micromachines

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Electronic equipment, including phased array radars, satellites, high-performance computers, etc., has been widely used in military and civilian fields. Its importance and significance are self-evident. Electronic equipment has many small components, various functions, and complex structures, making assembly an essential step in the manufacturing process of electronic equipment. In recent years, the traditional assembly methods have had difficulty meeting the increasingly complex assembly needs of military and civilian electronic equipment. With the rapid development of Industry 4.0, emerging intelligent assembly technology is replacing the original “semi-automatic” assembly technology. Aiming at the assembly requirements of small electronic equipment, we first evaluate the existing problems and technical difficulties. Then, we analyze the intelligent assembly technology of electronic equipment from three aspects: visual positioning, path and trajectory planning, and force–position coordination control technology. Further, we describe and summarize the research status and the application of the technology and discuss possible future research directions in the intelligent assembly technology of small electronic equipment.

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Section: Positioning Equipment and Algorithmsmentioning

confidence: 99%

A Review of Intelligent Assembly Technology of Small Electronic Equipment

Tian

Ding

Du³

et al. 2023

Micromachines

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“…Traditional methods such as the use of Bluetooth, laser, ultrasonic and IR sensors have been used in the past to estimate the object's distance [3]- [5] but with the advent of vision sensors, stereo vision and monocular vision are the only two predominant methods used for estimating the object's distance in image-based visual servoing. The stereo vision, which is also known as the computerbased passive approach uses two cameras in the form of binocular structure or human eyes to estimate the depth information of the object [6]- [8]. This can be achieved by placing two cameras horizontally apart and at equal distances from their center points to capture 2D images of the object in their views [9].…”

Section: Introductionmentioning

confidence: 99%

Object distance estimation using a monovision camera

Idohen,

Afolayan,

Umar

2023

IJRA

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In computer vision, most monovision cameras used for estimating the position of an object only estimate the 2D information of the object without the depth information. Estimating the depth information, which is the distance between the target object and the camera is quite challenging but, in this paper, a less computationally intensive method was used to estimate the object’s distance to complete the 3D information needed to determine the object’s location in cartesian space. In this method, the object was positioned in front of the camera at a sequential distance and was measured directly. The distances measured in the experiment with a set of training data obtained from the image were fitted into a curve using the least-square framework to derive a non-linear function that was used for estimating the object’s distance also known as the z-coordinate. The result from the experiment showed that there was an average error of 1.33 mm between the actual distance and the estimated distance of the object. Hence, this method can be applied in many robotic and autonomous systems applications.

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