首页|Reports Summarize Robotics and Automation Findings from University of Ljubljana (Center Direction Network for Grasping Point Localization On Cloths)
Reports Summarize Robotics and Automation Findings from University of Ljubljana (Center Direction Network for Grasping Point Localization On Cloths)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Robotics - Robotics and Automation is now available. According to news reporting from Ljubljana, Sloven ia, by NewsRx journalists, research stated, “Object grasping is a fundamental ch allenge in robotics and computer vision, critical for advancing robotic manipula tion capabilities. Deformable objects, like fabrics and cloths, pose additional challenges due to their non-rigid nature.” Financial support for this research came from ARIS. The news correspondents obtained a quote from the research from the University o f Ljubljana, “In this work, we introduce CeDiRNet-3DoF, a deep-learning model fo r grasp point detection, with a particular focus on cloth objects. CeDiRNet-3DoF employs center direction regression alongside a localization network, attaining first place in the perception task of ICRA 2023’s Cloth Manipulation Challenge. Recognizing the lack of standardized benchmarks in the literature that hinder e ffective method comparison, we present the ViCoS Towel Dataset. This extensive b enchmark dataset comprises 8,000 real and 12,000 synthetic images, serving as a robust resource for training and evaluating contemporary data-driven deep-learni ng approaches. Extensive evaluation revealed CeDiRNet-3DoF’s robustness in real- world performance, outperforming state-of-the-art methods, including the latest transformer-based models.”
LjubljanaSloveniaEuropeRobotics an d AutomationRoboticsUniversity of Ljubljana
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