Robotics & Machine Learning Daily News2024,Issue(Feb.13) :16-17.DOI:10.1109/LRA.2023.3346757

Findings from Tufts University Update Understanding of Robotics and Automation (Correcting Motion Distortion for Lidar Scan-tomap Registration)

Robotics & Machine Learning Daily News2024,Issue(Feb.13) :16-17.DOI:10.1109/LRA.2023.3346757

Findings from Tufts University Update Understanding of Robotics and Automation (Correcting Motion Distortion for Lidar Scan-tomap Registration)

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Abstract

Research findings on Robotics - Robotics and Automation are discussed in a new report. According to news reporting out of Somerville, Massachusetts, by NewsRx editors, research stated, “Because scanning-LIDAR sensors require finite time to create a point cloud, sensor motion during a scan warps the resulting image, a phenomenon known as motion distortion or rolling shutter. Motion-distortion correction methods exist, but they rely on external measurements or Bayesian filtering over multiple LIDAR scans.” Financial support for this research came from U.S. Department of Transportation Joint Program Office. Our news journalists obtained a quote from the research from Tufts University, “In this letter we propose a novel algorithm that performs snapshot processing to obtain a motion-distortion correction. Snapshot processing, which registers a current LIDAR scan to a reference image without using external sensors or Bayesian filtering, is particularly relevant for localization to a high-definition (HD) map. Our approach, which we call Velocity-corrected Iterative Compact Ellipsoidal Transformation (VICET), extends the wellknown Normal Distributions Transform (NDT) algorithm to solve jointly for both a 6 Degree-of-Freedom (DOF) rigid transform between a scan and a map and a set of 6DOF motion states that describe distortion within the current LIDAR scan.”

Key words

Somerville/Massachusetts/United States/North and Central America/Robotics and Automation/Robotics/Tufts University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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参考文献量34
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