首页|Findings from Guangdong University of Technology Provides New Data about Robotic s and Automation (Ig-lio: an Incremental Gicpbased Tightly-coupled Lidar-inerti al Odometry)
Findings from Guangdong University of Technology Provides New Data about Robotic s and Automation (Ig-lio: an Incremental Gicpbased Tightly-coupled Lidar-inerti al Odometry)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – A new study on Robotics - Robotics and Automation is now available. Accordingto news reporting from Guangzhou, People ’s Republic of China, by NewsRx journalists, research stated,“This work propose s an incremental Generalized Iterative Closest Point (GICP) based tightly-couple dLiDAR-inertial odometry (LIO), iG-LIO, which integrates the GICP constraints a nd inertial constraintsinto a unified estimation framework. iG-LIO uses a voxel -based surface covariance estimator to estimatethe surface covariances of scans , and utilizes an incremental voxel map to represent the probabilisticmodels of surrounding environments. These methods successfully reduce the time consumptio n of thecovariance estimation, nearest neighbor search, and map management.”
GuangzhouPeople’s Republic of ChinaA siaRobotics and AutomationRoboticsGuangdong University of Technology
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