A Sketch-Based System for Human-Guided Constrained Object Manipulation
This addresses the problem of making robot task planning more accessible and efficient for users, particularly in constrained object manipulation scenarios, though it appears incremental in combining existing sketch tools with human guidance.
The paper presents a sketch-based interface that allows novice users to extract geometries and generate affordance templates from 3D point clouds for robot-object interaction tasks, such as turning door handles and opening drawers, enabling faster and more versatile template generation without unsupervised learning.
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.