Active stereo platform: online epipolar geometry update

Mohamed, Abdulla; Culverhouse, Phil F.; Cangelosi, Angelo; Yang, Chenguang

doi:10.1186/s13640-018-0292-8

Cited by 12 publications

(4 citation statements)

References 35 publications

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“…Many applications developed stereo vision systems to determine the position of objects for robot grasping [43][44][45][46][47][48]. Chen et al [49] develop the picking robot system based on a Fuzzy Neural Network Sliding Mode Algorithms.…”

Section: IImentioning

confidence: 99%

Development of Multi-Robotic Arm System for Sorting System Using Computer Vision

Dang²,

Le³

2022

Journal of Robotics and Control

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This paper develops a multi-robotic arm system and a stereo vision system to sort objects in the right position according to size and shape attributes. The robotic arm system consists of one master and three slave robots associated with three conveyor belts. Each robotic arm is controlled by a robot controller based on a microcontroller. A master controller is used for the vision system and communicating with slave robotic arms using the Modbus RTU protocol through an RS485 serial interface. The stereo vision system is built to determine the 3D coordinates of the object. Instead of rebuilding the entire disparity map, which is computationally expensive, the centroids of the objects in the two images are calculated to determine the depth value. After that, we can calculate the 3D coordinates of the object by using the formula of the pinhole camera model. Objects are picked up and placed on a conveyor branch according to their shape. The conveyor transports the object to the location of the slave robot. Based on the size attribute that the slave robot receives from the master, the object is picked and placed in the right position. Experiment results reveal the effectiveness of the system. The system can be used in industrial processes to reduce the required time and improve the performance of the production line.

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Section: IImentioning

confidence: 99%

Development of Multi-Robotic Arm System for Sorting System Using Computer Vision

Dang²,

Le³

2022

Journal of Robotics and Control

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“…We can achieve this by setting the 2D sensors values (calibration matrix, distortion factor) and "mutual spacing and 2D sensors orientation". Furthermore, epipolar geometry (which addresses two sensor issues) is needed for the statement of the number of 3D points that we can estimate based on the positions at 2D sensors [20]. During the determination of the search points m = [x , y , 1] using the obtained picture, the following equation applies:…”

Section: D Sensorsmentioning

confidence: 99%

Center of Gravity Coordinates Estimation Based on an Overall Brightness Average Determined from the 3D Vision System

Holubek

Vagaš

2021

Applied Sciences

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In advanced manufacturing technologies (including complex automated processes) and their branches of industry, perception and evaluation of the object parameters are the most critical factors. Many production machines and workplaces are currently equipped as standard with high-quality special sensing devices based on vision systems to detect these parameters. This article focuses on designing a reachable and fully functional vision system based on two standard CCD cameras usage, while the emphasis is on the RS 232C communication interface between two sites (vision and robotic systems). To this, we combine principles of the 1D photogrammetric calibration method from two known points at a stable point field and the available packages inside the processing unit of the vision system (as filtering, enhancing and extracting edges, weak and robust smoothing, etc.). A correlation factor at camera system (for reliable recognition of the sensed object) was set from 84 to 100%. Then, the pilot communication between both systems was proposed and then tested through CREAD/CWRITE commands according to protocol 3964R (used for the data transfer). Moreover, the system was proven by successful transition of the data into the robotic system. Since research gaps in this field still exist and many vision systems are based on PC processing or intelligent cameras, our potential research topic tries to provide the price–performance ratio solution for those who cannot regularly invest in the newest vision technology; however, they could still do so to stay competitive.

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“…The SVS obtains 3-D information from two images captured from two different cameras separated by a known distance. Similar design of SVS can be found in the literature, [27][28][29] The developed computer program for 3-D point localization using SVS can be divided into five steps: images capture, camera calibration, pattern match, computing pixel coordinates to angles, and triangulation. Figure 4 shows the localization of a 3-D point in the scene using the developed SVS.…”

Section: Svs Implementationmentioning

confidence: 99%

Improve three-dimensional point localization accuracy in stereo vision systems using a novel camera calibration method

Ramírez-Hernández

Rodríguez-Quiñonez

Castro-Toscano

et al. 2020

International Journal of Advanced Robotic Systems

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Computer vision systems have demonstrated to be useful in applications of autonomous navigation, especially with the use of stereo vision systems for the three-dimensional mapping of the environment. This article presents a novel camera calibration method to improve the accuracy of stereo vision systems for three-dimensional point localization. The proposed camera calibration method uses the least square method to model the error caused by the image digitalization and the lens distortion. To obtain particular three-dimensional point coordinates, the stereo vision systems use the information of two images taken by two different cameras. Then, the system locates the two-dimensional pixel coordinates of the three-dimensional point in both images and coverts them into angles. With the obtained angles, the system finds the three-dimensional point coordinates through a triangulation process. The proposed camera calibration method is applied in the stereo vision systems, and a comparative analysis between the real and calibrated three-dimensional data points is performed to validate the improvements. Moreover, the developed method is compared with three classical calibration methods to analyze their advantages in terms of accuracy with respect to tested methods.

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Active stereo platform: online epipolar geometry update

Cited by 12 publications

References 35 publications

Development of Multi-Robotic Arm System for Sorting System Using Computer Vision

Development of Multi-Robotic Arm System for Sorting System Using Computer Vision

Center of Gravity Coordinates Estimation Based on an Overall Brightness Average Determined from the 3D Vision System

Improve three-dimensional point localization accuracy in stereo vision systems using a novel camera calibration method

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