论文标题
概率3D多标记实时映射用于多对象操作
Probabilistic 3D Multilabel Real-time Mapping for Multi-object Manipulation
论文作者
论文摘要
概率3D映射已应用于具有多个摄像机视点的对象分割，但是，传统方法缺乏多标签对象映射的实时效率和功能。在本文中，我们提出了一种实时生成具有多标签占用率的三维图的方法。扩展我们以前仅映射目标标签占用率的工作，我们将在单一观察中实现多标签对象细分。我们通过使用39个不同对象测试分割精度来评估我们的方法，并将其应用于实验中多个对象的操作任务。我们的基于映射的方法优于40-96 \％相对（12.6平均$ iu_ {3d} $）的传统方法，并且在具有沉重遮挡的环境中，机器人成功识别（86.9 \％），并操纵多个对象（60.7 \％）。
Probabilistic 3D map has been applied to object segmentation with multiple camera viewpoints, however, conventional methods lack of real-time efficiency and functionality of multilabel object mapping. In this paper, we propose a method to generate three-dimensional map with multilabel occupancy in real-time. Extending our previous work in which only target label occupancy is mapped, we achieve multilabel object segmentation in a single looking around action. We evaluate our method by testing segmentation accuracy with 39 different objects, and applying it to a manipulation task of multiple objects in the experiments. Our mapping-based method outperforms the conventional projection-based method by 40 - 96\% relative (12.6 mean $IU_{3d}$), and robot successfully recognizes (86.9\%) and manipulates multiple objects (60.7\%) in an environment with heavy occlusions.
