能動的姿勢推定への階層的アプローチ
A Hierarchical Approach to Active Pose Estimation
RGB画像による粗い2D位置推定の後、点群データで高精度な姿勢推定を行う階層的手法を提案し、画像特徴を活用することで探索と推定が高速化することを示した。
著者: Jascha Hellwig, Mark Baierl, Joao Carvalho, Julen Urain, Jan Peters
分類: cs.RO
原文アブストラクト
Creating mobile robots which are able to find and manipulate objects in large environments is an active topic of research. These robots not only need to be capable of searching for specific objects but also to estimate their poses often relying on environment observations, which is even more difficult in the presence of occlusions. Therefore, to tackle this problem we propose a simple hierarchical approach to estimate the pose of a desired object. An Active Visual Search module operating with RGB images first obtains a rough estimation of the object 2D pose, followed by a more computationally expensive Active Pose Estimation module using point cloud data. We empirically show that processing image features to obtain a richer observation speeds up the search and pose estimation computations, in comparison to a binary decision that indicates whether the object is or not in the current image.
