In this paper, we present an easy to use sketch-based interface to extract geometries and generate affordance files from 3D point clouds for robot-object interaction tasks. Using our system, even novice users can perform robot task planning by employing such sketch tools. Our focus in this paper is employing human-in-the-loop approach to assist in the generation of more accurate affordance templates and guidance of robot through the task execution process. Since we do not employ any unsupervised learning to generate affordance templates, our system performs much faster and is more versatile for template generation. Our system is based on the extraction of geometries for generalized cylindrical and cuboid shapes, after extracting the geometries, affordances are generated for objects by applying simple sketches. We evaluated our technique by asking users to define affordances by employing sketches on the 3D scenes of a door handle and a drawer handle and used the resulting extracted affordance template files to perform the tasks of turning a door handle and opening a drawer by the robot.

中文翻译：

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一种基于草图的人类引导约束对象操作系统

在本文中，我们提出了一个易于使用的基于草图的界面来提取几何图形并从 3D 点云生成可供机器人对象交互任务的可供性文件。使用我们的系统，即使是新手用户也可以通过使用此类草图工具来执行机器人任务计划。我们在本文中的重点是采用人在环方法来帮助生成更准确的可供性模板和机器人在任务执行过程中的指导。由于我们不使用任何无监督学习来生成可供性模板，因此我们的系统执行速度更快，并且在模板生成方面更加通用。我们的系统基于提取广义圆柱和长方体形状的几何形状，在提取几何形状后，通过应用简单的草图为对象生成可供性。