首页|Data on Robotics Reported by Researchers at York University (Visual Control for Robotic 3d Printing On a Moving Platform)
Data on Robotics Reported by Researchers at York University (Visual Control for Robotic 3d Printing On a Moving Platform)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on Robotics are disc ussed in a new report. According to news reporting from Toronto, Canada, by News Rx journalists, research stated, "In recent years, there has been significant pr ogress in developing specialized 3D printing techniques that cater to various de manding applications. However, the current state of this technology is challenge d when it comes to complex in situ printing scenarios, which require a controlle d printing platform." Financial support for this research came from Natural Sciences and Engineering R esearch Council of Canada (NSERC). The news correspondents obtained a quote from the research from York University, "The lack of a stable printing platform is a fundamental limitation of its use in in situ applications. To address this issue, we present a novel platform-inde pendent 3D fabrication process that enables printing on platforms with non-coope rative movement. The process overcomes the challenge of high-speed tracking, mot ion compensation, and real-time printing by developing a closed-loop visual feed back-controlled robotic printing process. The proposed process incorporates a ma rker-based visual detection and tracking controller setup, which is discussed in detail. The algorithm consists of two loops running asynchronously: a high-spee d inner control loop and an outer measurement loop. This setup enables precise a nd accurate tracking of the printing platform, compensating for any disturbances during the printing process. Our experimental results demonstrate the successfu l printing of simple linear geometries, even with low-disturbing platform veloci ties. Moreover, the tracking controllers' ability to handle measurement occlusio n is validated, showing the proposed process's robustness and effectiveness."
TorontoCanadaNorth and Central Ameri caEmerging TechnologiesMachine LearningRoboticsRobotsYork University
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