Automatic Relational Scene Representation For Safe Robotic Manipulation Tasks

In this paper, we propose a new approach for automatically building symbolic relational descriptions of static configurations of objects to be manipulated by a robotic system. The main goal of our work is to provide advanced cognitive abilities for such robotic systems to make them more aware of the outcome of their actions. We describe how such symbolic relations are automatically extracted for configurations of box-shaped objects using notions from geometry and static equilibrium in classical mechanics. We also present extensive simulation results as well as some real-world experiments aimed at verifying the output of the proposed approach.