摘要
由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-调查人员讨论机器人学的新发现-机器人和自动化。根据来自德国汉诺威的新闻报道，由NewsRx记者报道，Research称，“在本文中，”信中，我们解决了构建连续三维模型的挑战，这些模型可以准确地再现不确定性表面，来自噪声激光雷达数据。在我们的pri或工作的基础上，利用高斯函数过程(GP)和高斯混合模型(GM M)对于结构化建筑模型,我们介绍了一种更多的城市场景中复杂曲面的广义逼近tail ored,其中GMM回归与GP应用了决定性的观察结果。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators discuss new findings in Robotics - Robotics and Automation. According tonews reporting originating from Hannover, Germany, by NewsRx correspondents, research stated, “In thisletter, we address the challenge of constructing continuous 3D models that accurately re present uncertainsurfaces, derived from noisy LiDAR data. Building upon our pri or work, which utilized the GaussianProcess (GP) and Gaussian Mixture Model (GM M) for structured building models, we introduce a moregeneralized approach tail ored for complex surfaces in urban scenes, where GMM Regression and GP withderi vative observations are applied.”
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