DOAJ Open Access 2023

Accurate Covariance Estimation for Pose Data From Iterative Closest Point Algorithm

Rick H. Yuan Clark N. Taylor Scott L. Nykl

Abstrak

One of the fundamental problems of robotics and navigation is the estimation of the relative pose of an external object with respect to the observer. A common method for computing the relative pose is the iterative closest point (ICP) algorithm, where a reference point cloud of a known object is registered against a sensed point cloud to determine relative pose. To use this computed pose information in downstream processing algorithms, it is necessary to estimate the uncertainty of the ICP output, typically represented as a covariance matrix. In this paper, a novel method for estimating uncertainty from sensed data is introduced.

Topik & Kata Kunci

Canals and inland navigation. Waterways Naval Science

Penulis (3)

Rick H. Yuan

Clark N. Taylor

Scott L. Nykl

Format Sitasi

APA MLA BibTeX

Yuan, R.H., Taylor, C.N., Nykl, S.L. (2023). Accurate Covariance Estimation for Pose Data From Iterative Closest Point Algorithm. https://doi.org/10.33012/navi.562

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Informasi Jurnal

Tahun Terbit: 2023
Sumber Database: DOAJ
DOI: 10.33012/navi.562
Akses: Open Access ✓