REACT: 更新可能な3Dシーングラフのためのリアルタイム効率的属性クラスタリングと転移
REACT: Real-time Efficient Attribute Clustering and Transfer for Updatable 3D Scene Graph
3Dシーングラフの物体ノードを再定位するため、三重項損失で学習した埋め込みモデルによるインスタンスのクラスタリングとマッチングをリアルタイムで行うフレームワークREACTを提案した。
著者: Phuoc Nguyen, Francesco Verdoja, Ville Kyrki
分類: cs.RO
原文アブストラクト
Modern-day autonomous robots need high-level map representations to perform sophisticated tasks. Recently, 3D scene graphs (3DSGs) have emerged as a promising alternative to traditional grid maps, blending efficient memory use and rich feature representation. However, most efforts to apply them have been limited to static worlds. This work introduces REACT, a framework that efficiently performs real-time attribute clustering and transfer to relocalize object nodes in a 3DSG. REACT employs a novel method for comparing object instances using an embedding model trained on triplet loss, facilitating instance clustering and matching. Experimental results demonstrate that REACT is able to relocalize objects while maintaining computational efficiency. The REACT framework's source code will be available as an open-source project, promoting further advancements in reusable and updatable 3DSGs.
