A multi-depth camera capture system for point cloud library

Rogge, Stephan; Hentschel, Christian

doi:10.1109/icce-berlin.2014.7034277

Cited by 3 publications

(3 citation statements)

References 8 publications

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“…Through our constant attempts, the average and the standard deviation of the angular absolute errors become small when the constant value c Com is about 7.96875. Due to the fact that 1 2p in equation (20) and 7.96875 are constants, this article combines the two constants to a constant value c EV , and the fixed equation is shown as below…”

Section: Normal Vectors Of Point Cloud Surfacementioning

confidence: 99%

“…This may not only affect the use of robot arms but also cause safety problems when people work. [1][2][3] Therefore, this article proposes a method of posture measurement by RGB-D cameras as sensory devices for articulated manipulators. The method combines the captured images from two opposite RGB-D cameras, filters, and segments the point cloud data (PCD) of each cylindrical link.…”

Section: Introductionmentioning

confidence: 99%

“…and P 1 P 3 ! shown as equation (2) to get the three coefficients a; b, and c in equation (1). The next step is to substitute P 1 into equation (1) to get the fourth coefficient d. Finally, the number of the inliers which fit the planar model is calculated by the planar equationÑ…”

Section: Introductionmentioning

confidence: 99%

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A posture measurement approach for an articulated manipulator by RGB-D cameras

Shi

Meng

Hwang

et al. 2019

International Journal of Advanced Robotic Systems

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The objective of this article aims at the safety problems where robots and operators are highly coupled in a working space. A method to model an articulated robot manipulator by cylindrical geometries based on partial cloud points is proposed in this article. Firstly, images with point cloud data containing the posture of a robot with five resolution links are captured by a pair of RGB-D cameras. Secondly, the process of point cloud clustering and Gaussian noise filtering is applied to the images to separate the point cloud data of three links from the combined images. Thirdly, an ideal cylindrical model fits the processed point cloud data are segmented by the random sample consensus method such that three joint angles corresponding to three major links are computed. The original method for calculating the normal vector of point cloud data is the cylindrical model segmentation method, but the accuracy of posture measurement is low when the point cloud data is incomplete. To solve this problem, a principal axis compensation method is proposed, which is not affected by number of point cloud cluster data. The original method and the proposed method are used to estimate the three joint angular of the manipulator system in experiments. Experimental results show that the average error is reduced by 27.97%, and the sample standard deviation of the error is reduced by 54.21% compared with the original method for posture measurement. The proposed method is 0.971 piece/s slower than the original method in terms of the image processing velocity. But the proposed method is still feasible, and the purpose of posture measurement is achieved.

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Section: Normal Vectors Of Point Cloud Surfacementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%