首页|Findings from University of Augsburg Has Provided New Data on Robotics (Selectin g Feasible Trajectories for Robot-based X-ray Tomography By Varying Focus-detect or-distance In Space Restricted Environments)
Findings from University of Augsburg Has Provided New Data on Robotics (Selectin g Feasible Trajectories for Robot-based X-ray Tomography By Varying Focus-detect or-distance In Space Restricted Environments)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Robotics is the subjec t of a report. According to news reporting originating from Augsburg, Germany, b y NewsRx correspondents, research stated, "Computed tomography has evolved as an essential tool for non-destructive testing within the automotive industry. The application of robot-based computed tomography enables high-resolution CT inspec tions of components exceeding the dimensions accommodated by conventional system s." Financial support for this research came from Dr. Ing. h.c. F. Porsche AG. Our news editors obtained a quote from the research from the University of Augsb urg, "However, large-scale components, e.g. vehicle bodies, often exhibit trajec tory-limiting elements. The utilization of conventional trajectories with consta nt Focus-Detector-Distances can lead to anisotropy in image data due to the inac cessibility of some angular directions. In this work, we introduce two approache s that are able to select suitable acquisitions point sets in scans of challengi ng to access regions through the integration of projections with varying Focus-D etector-Distances. The variable distances of the X-ray hardware enable the capab ility to navigate around collision structures, thus facilitating the scanning of absent angular directions. The initial approach incorporates collision-free vie wpoints along a spherical trajectory, preserving the field of view by maintainin g a constant ratio between the Focus-Object-Distance and the Object-Detector-Dis tance, while discreetly extending the Focus-Detector-Distance. The second method ology represents a more straightforward approach, enabling the scanning of angul ar sectors that were previously inaccessible on the conventional circular trajec tory by circumventing the X-ray source around these collision elements."
AugsburgGermanyEuropeEmerging Tech nologiesMachine LearningRobotRoboticsUniversity of Augsburg
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