3DガウシアンスプラッティングとAstrobeeを用いた国際宇宙ステーションのその場再構築
In-Situ Reconstruction of the International Space Station Using 3D Gaussian Splatting and Astrobee
Astrobeeロボットの画像データを用いて、国際宇宙ステーション内部を3Dガウシアンスプラッティングで高精細に再構築する手法を提案し、既存手法より高品質かつ高速であることを示した。
著者: Hudson Kim, Ryan Soussan, Brian Coltin, Jordan Kam
分類: cs.RO
原文アブストラクト
This article presents a novel 3D reconstruction and mapping of the interior of the International Space Station (ISS) using 3D Gaussian Splatting (3DGS). Using existing grayscale images from the Astrobee free-flying robot dataset, we construct a full 3D splat of the ISS' Kibō or Japanese Experiment Module (JEM). 3DGS has in recent years shown promise in providing novel view synthesis of scenes captured from many images or videos, this article applies this approach to human spaceflight systems. We compare our 3DGS architecture to existing methods such as Nerfacto and TensoRF and show that reconstruction improves the state-of-the-art in both scene quality and rendering speed. We show that with as little as 500 in-situ images, a high-fidelity map can be constructed using Astrobee's Navigation Camera (NavCam) during free-flight in the JEM. These reconstructions could enable free-flyers to rapidly create and update interior maps for intra-vehicular habitats like the ISS.