首页|Findings from Chinese Academy of Sciences Has Provided New Data on Robotics and Automation (Lightweight Structured Line Map Based Visual Localization)
Findings from Chinese Academy of Sciences Has Provided New Data on Robotics and Automation (Lightweight Structured Line Map Based Visual Localization)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on Robotics - Roboti cs and Automation are discussed in a new report. According to news originating f rom Beijing, People’s Republic of China, by NewsRx correspondents, research stat ed, “Visual localization, also known as camera pose estimation, is a crucial com ponent of many applications, such as robotics, autonomous driving, and augmented reality. Traditional visual localization algorithms typically run on point clou d maps generated by algorithms such as Structure-from- Motion (SfM) or Simultaneo us Localization and Mapping (SLAM).” Financial support for this research came from National Natural Science Foundatio n of China (NSFC). Our news journalists obtained a quote from the research from the Chinese Academy of Sciences, “However, point features are sensitive to weak textures and illumi nation changes. In addition, the generated 3D point cloud maps often contain mil lions of points, which puts higher demands on device storage and computing resou rces. To address these challenges, we propose a visual localization algorithm ba sed on lightweight structured line maps. Instead of extracting and matching poin t features in the images, we select line segments that represent structured scen e information as image features. These line segments are then used to construct a lightweight line map containing rich structured scene information. The camera pose is then estimated through a series of steps that include line extraction, m atching, initial pose estimation, and pose refinement.”
BeijingPeople’s Republic of ChinaAsi aRobotics and AutomationRoboticsChinese Academy of Sciences
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