多視点融合による多階層ロボットシーン理解
Multi-View Fusion for Multi-Level Robotic Scene Understanding
ハンドカメラのRGB画像列から、障害物回避用の点群、未知物体の形状カテゴリと概略姿勢、既知物体の6DoF姿勢を融合的に推定し、マニピュレーション向けの豊富なシーン表現を実現した。
著者: Yunzhi Lin, Jonathan Tremblay, Stephen Tyree, Patricio A. Vela, Stan Birchfield
分類: cs.RO
原文アブストラクト
We present a system for multi-level scene awareness for robotic manipulation. Given a sequence of camera-in-hand RGB images, the system calculates three types of information: 1) a point cloud representation of all the surfaces in the scene, for the purpose of obstacle avoidance; 2) the rough pose of unknown objects from categories corresponding to primitive shapes (e.g., cuboids and cylinders); and 3) full 6-DoF pose of known objects. By developing and fusing recent techniques in these domains, we provide a rich scene representation for robot awareness. We demonstrate the importance of each of these modules, their complementary nature, and the potential benefits of the system in the context of robotic manipulation.
