Prepare the Chair for the Bear! Robot Imagination of Sitting Affordance to Reorient Previously Unseen Chairs

Abstract

In this letter, a paradigm for the classification and manipulation of novel objects is established and demonstrated with the example of chairs. Our approach leverages the robot's understanding of object stability, perceptibility, and affordance to prepare previously unseen and randomly oriented chairs on which a teddy bear is to be seated. The teddy bear is a proxy for an elderly person, hospital patient, or child. By autonomously reconstructing a complete model of the object and inserting it into a physical simulator (i.e., the robot's "imagination"), the robot assesses whether or not the object is a chair and, if it is, determines how to reorient it properly to be used. Experimental results show that our method achieves a high success rate on the real robot task of chair preparation. Also, it outperforms several baseline methods on the task of upright pose prediction for chairs. The same methodology can be easily transferred to a wide variety of application scenarios, and illustrates a broader paradigm in affordance-based reasoning.