首页|Investigators from Southeast University Zero in on Robotics and Automation (Okr- net: Overlapping Keypoints Registration Network for Large-scale Lidar Point Clou ds)
Investigators from Southeast University Zero in on Robotics and Automation (Okr- net: Overlapping Keypoints Registration Network for Large-scale Lidar Point Clou ds)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on Robotics - Ro botics and Automation have been published. According to news reporting originati ng in Nanjing, People's Republic of China, by NewsRx journalists, research state d, "Point cloud registration is a fundamental task in various intelligence appli cations, including simultaneous localization and mapping as well as scene recons truction. However, in large-scale scenes, the majority of point clouds exhibit p artial overlap, posing a significant challenge to the registration process." Financial support for this research came from Science Fund for Creative Research Groups. The news reporters obtained a quote from the research from Southeast University, "This study introduces a registration network, named OKR-Net, specifically desi gned to efficiently align partially overlapping point clouds. The OKR-Net compri ses two innovative modules: a joint estimation module adept at identifying the k eypoints within the overlapping region; and a coarse-to-fine registration module designed to aggregate the overlap and descriptor information, thereby reducing the outliers and yielding robust corresponding point pairs. In addition, an over lap labeling method for generated keypoints is introduced. The efficiency of the proposed registration network is validated utilizing two large-scale outdoor da tasets: KITTI and NuScenes."
NanjingPeople's Republic of ChinaAsi aRobotics and AutomationRoboticsSoutheast University
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